Skip to main content
RSC Advances logoLink to RSC Advances
. 2026 Aug 6;16(39):43161–43186. doi: 10.1039/d6ra05954f

Catalytic and photocatalytic reduction/degradation of methyl red dye by metal nanoparticles, metal oxides, and their composites: a critical review

Muhammad Arif a,✉
PMCID: PMC13446455  PMID: 42565156

Abstract

Methyl red (MR) is a widely used azo dye in various industries, and its uncontrolled discharge into aquatic ecosystems poses serious health and environmental concerns owing to its persistence, toxicity, and resistance to conventional treatment methods. Therefore, the development of efficient and sustainable technologies for MR removal has become an important research priority. This review critically summarizes recent advances in the catalytic reduction and photocatalytic degradation of MR using metal nanoparticles and semiconductor-based materials. The synthesis strategies and characterization techniques employed for metal nanoparticles and photocatalysts are discussed which emphasis on their structural, morphological, optical, and electronic properties. Various catalytic systems like mono-metallic, bi-metallic, tri-metallic, and tetra-metallic nanoparticles are comprehensively evaluated for NaBH4-assisted reduction of MR, while semiconductor photocatalysts and hybrid nanocomposites are examined for photocatalytic and oxidative degradation applications. The fundamental mechanisms governing electron transfer, hydrogen atom transfer, reactive oxygen species generation, and azo bond cleavage are critically analyzed. Moreover, the influence of operational parameters like catalyst composition, light intensity, pH, catalyst loading, particle size, dye concentration, temperature, and oxidant dosage on reaction efficiency is systematically discussed. Particular attention is given to catalyst stability, recyclability, thermodynamic aspects, and the role of support materials in enhancing catalytic performance. Current challenges like incomplete mineralization, metal leaching, nanoparticle aggregation, and limitations associated with real wastewater treatment which are also highlighted. Finally, future perspectives focusing on multifunctional nanomaterials, solar-driven processes, green synthesis approaches, and scalable treatment technologies are presented. This review provides a comprehensive framework for the rational design of highly efficient and sustainable catalysts for MR remediation in wastewater treatment systems.


This review critically evaluates metal nanoparticles/metal oxides for methyl red degradation/reductions through electron transfer, hydrogenation, and oxidative mechanisms.graphic file with name d6ra05954f-ga.webp

1. Introduction

The extensive use of synthetic dyes in industrial applications has emerged as a major environmental concern owing to their toxicity, chemical stability, and resistance to biodegradation.1–3 Dyes are extensively utilized in textile,4 printing,5 cosmetics,6 plastics,7 leather,8 and pharmaceutical9 industries because of their strong coloring ability and durability. However, nearly 15–20% of the total dyes produced annually are released as effluents into aquatic systems without adequate treatment.10 These dye-loaded wastewaters not only impart intense coloration but also severely disrupt aquatic ecosystems by reducing sunlight penetration, lowering photosynthetic activity, and altering dissolved oxygen levels. Consequently, they degrade water quality and threaten aquatic biodiversity. Organic dyes have several classes, from which azo dyes is one class from them.11,12 Among synthetic dyes, azo dyes represent the largest class, accounting for more than 60% of total consumption, and are recognized as persistent organic pollutants owing to their strong aromatic structures and azo (–N Created by potrace 1.16, written by Peter Selinger 2001-2019 N–) linkages that are resistant to natural degradation.13,14

Methyl Red (MR) is one such azo dye which is widely applied in textile dyeing, printing inks, and laboratory analysis as an acid–base indicator because of its pH-sensitive color change.15–17 Despite its industrial significance, MR poses serious risks to environmental and human health. The dye is highly soluble in water and resists microbial degradation which allows it to persist in aquatic environments for extended periods.18,19 More critically (under reductive conditions) MR undergoes cleavage of its azo bond and produces aromatic amines like dimethyl-p-phenylenediamine and anthranilic acid, which are mutagenic, carcinogenic, and toxic to aquatic organisms. MR can be detected from water even though it has very low concentration which generates aesthetic concerns20 while simultaneously interfering with the growth and metabolism of aquatic plants and microorganisms. Prolonged exposure to MR-contaminated water has been associated with liver damage, gastrointestinal irritation, and genotoxic effects in humans, underscoring its harmful nature.21,22

Several conventional techniques have been employed for the treatment of MR like adsorption,23 coagulation–flocculation,24 biological degradation,25 membrane filtration,26 photolysis,27 or catalytic reduction.28 While adsorption is simple and cost-effective, it merely transfers the dye from liquid to solid phase which generates secondary disposal problems. Biological methods are inefficient due to the structural stability of azo dyes and their resistance to enzymatic breakdown. Similarly, coagulation generates large volumes of sludge, membrane processes are energy-intensive and prone to fouling, and photolytic methods require high energy input with limited efficiency. Therefore, these conventional approaches are either incomplete or unsustainable which highlights the urgent need for more effective strategies for MR removal.

In recent years, nanotechnology has opened new opportunities for the treatment of dye pollutants.29–31 Inorganic metal nanoparticles (IMNPs) like silver (Ag),32 gold (Au),33 palladium (Pd),34 cobalt (Co),35 and metal oxides (semiconductors) such as Fe2O3,36 and ZnO37 have gained attention as efficient catalysts for the reduction/degradation of azo dyes like MR. Their unique physicochemical properties like high surface area, small size, tunable morphology, and enhanced electron-transfer capability make them far superior to their bulk counterparts. The photocatalytic degradation of MR by semiconductors takes some for complete mineralization. But catalytic reduction of MR using nanoparticles and reducing agents like sodium borohydride (NaBH4) has shown remarkable efficiency in transforming the dye into less toxic and colorless products within a very short time.38 Complete mineralization during photocatalytic degradation maintains sustainability but it takes hours to complete, while the excess amount of NaBH4 produces toxicity during catalytic reduction but it occurs rapidly. Usage of very small amount of NaBH4 during reduction can minimize their toxicity. Therefore, both catalytic and photocatalytic degradation/reduction methods of MR are also environmentally friendly which produces a sustainable alternative to conventional processes.

Researchers have demonstrated that the catalytic performance of NPs can be significantly improved by forming bimetallic39 or tri-metallic40 systems in both MNPs and metal oxide/sulfide forms, where synergistic effects between different metals enhance stability, reactivity, and electron transfer rates. The main challenge for metal nanoparticles is instability in nano-range. These nanoparticles start to coagulate to form large products, resulting in a decrease in the surface-active site and hence decreases the catalytic performance of nanoparticles. Various capping agents (supporting materials) have been used to resolve this instability issue. Additionally, immobilization of nanoparticles on supporting materials like graphene oxide,41 mesoporous silica,42 polymers,43 and metal–organic frameworks (MOFs)44 enhances dispersion, prevents agglomeration, and improves recyclability. These advancements underscore the growing role of nano-catalysts in the solution to the global challenge of dyes pollution.

Several review articles have examined the removal of azo dyes from wastewater through adsorption, photocatalysis, advanced oxidation processes, and biological treatments.45–50 Furthermore, a number of reviews have focused on specific dyes like methyl orange (MO), methylene blue (MB), Congo red (CR), rhodamine B (RhB), and other synthetic dyes.51–54 Recent reviews have also discussed nanoparticle-mediated catalytic reduction/degradation of organic pollutants. Nevertheless, these studies focus either on broad classes of dyes, individual treatment technologies, or specific photocatalytic systems. A comprehensive analysis dedicated exclusively to methyl red (MR) remediation through both catalytic reduction and photocatalytic degradation using metal nanoparticles, metal oxides, and their composites remains lacking.

Although MR belongs to the azo dye family, its chemical structure, reduction intermediates, degradation pathways, protonation behavior, and catalyst–dye interactions differ significantly from those of other commonly studied dyes such as MO, CR, and MB. Therefore, conclusions derived from reviews on other dyes cannot be directly extrapolated to MR. Furthermore, most previous reviews emphasize photocatalytic degradation, while catalytic reduction mechanisms, thermodynamic aspects, electron-transfer pathways, catalyst recyclability, and the comparative performance of mono-, bi-, tri-, and tetra-metallic nanoparticles receive limited attention.

The present review distinguishes itself from previous literature by providing a dedicated and critical assessment of inorganic nanoparticles for both catalytic reduction and photocatalytic degradation of MR. In addition to discussing degradation and reduction mechanisms, this review critically evaluates the role of catalyst composition, reaction parameters, supporting materials, morphology, catalyst recovery, thermodynamic considerations, and recyclability. Furthermore, mono-metallic, bi-metallic, tri-metallic, and tetra-metallic nanoparticle systems are comparatively analyzed within a single framework. Particular emphasis is also placed on the advantages and limitations of inorganic, carbon-based, polymeric, and metal–organic framework supporting materials, as well as on challenges related to catalyst stability, nanoparticle leaching, scale-up, and real wastewater applications. Therefore, this review establishes a comprehensive MR-centered perspective rather than providing a general overview of azo dye treatment that integrates catalytic reduction and photocatalytic degradation pathways and identifies future directions for the development of efficient and sustainable nanoparticle-based remediation technologies.

2. Methyl red: synthesis, sources, and applications

Methyl red (C15H15N3O2) (a member of the azo dye family) is one of the most widely studied synthetic dyes owing to its extensive use in laboratories and industries. Structurally, it contains an azo linkage (–N Created by potrace 1.16, written by Peter Selinger 2001-2019 N–) connecting aromatic rings substituted with a dimethylamino group and a carboxylic acid group.55 This molecular framework imparts strong resonance stabilization which makes the dye resistant to natural degradation processes. Furthermore, the azo bond is responsible for the vivid red–orange coloration of the dye, while its ionizable groups enable protonation–deprotonation depending on pH which gives methyl red its characteristic application as an acid–base indicator.56

The synthesis of methyl red typically involves the diazotization of anthranilic acid followed by azo coupling with dimethylaniline as shown in Fig. 1.57–59 This process (widely used in dye manufacturing industries) is inexpensive and scalable, which partly explains the large availability of MR and its incorporation into various applications. While industrial-scale production makes methyl red economically attractive, it also increases the likelihood of improper discharge into wastewater streams which raises environmental and public health concerns.

Fig. 1. Synthesis of methyl red through diazotization.

Fig. 1

Methyl red has found widespread use in textile industries, where it is employed for dyeing cotton, silk, and wool fabrics owing to its intense coloration and good fastness properties.60 Beyond textiles, MR is a critical component in printing inks, plastics, and cosmetics, and in analytical laboratories it is extensively used as a pH indicator which changes color from red in acidic conditions (pH < 4.4) to yellow in alkaline conditions (pH > 6.2)56,61 (the change in structure during changing the pH of medium is shown in Fig. 2) While these applications highlight its versatility, they also contribute to its large-scale release into industrial effluents, particularly from dyeing and printing sectors, which are considered major contributors to azo dye pollution.

Fig. 2. Effect of pH of medium on structure of methyl red.

Fig. 2

The environmental implications of methyl red are particularly alarming. Its high solubility in water and chemical stability make it persistent in aquatic systems, where it can accumulate over time. Unlike some other dyes, MR is resistant to microbial degradation, and under anaerobic conditions, it undergoes reductive cleavage of the azo bond to yield aromatic amines like dimethyl-p-phenylenediamine and anthranilic acid.62 These compounds are not only toxic but also mutagenic, teratogenic, and carcinogenic, and their accumulation in food chains poses long-term health risks to humans and aquatic organisms alike. Even at trace concentrations, MR imparts visible coloration to water bodies, reducing sunlight penetration, limiting photosynthetic activity, and decreasing dissolved oxygen, thereby disturbing aquatic ecosystems.

Thus, the widespread industrial use, ease of synthesis, and chemical stability of methyl red collectively explain its extensive presence in wastewater effluents and its classification as a priority pollutant. While its applications are economically valuable, the severe environmental and health hazards associated with MR and its by-products make it a persistent issue for wastewater treatment technologies.55,63 Understanding its structure, synthesis, and environmental behavior is therefore crucial to developing efficient and sustainable strategies for its removal.

3. Synthesis of catalytic (metal nanoparticles) and photocatalytic (semiconductors) materials

Various methods are used to synthesize the metal nanoparticles and semiconductors.

3.1. Synthesis of photocatalyst

Photocatalysts can be synthesized through a variety of physical, chemical, and biological methods. The choice of synthesis route strongly influences the catalyst's particle size, morphology, crystallinity, surface area, band-gap energy, and ultimately its photocatalytic performance. An ideal synthesis method should produce highly crystalline materials with large surface areas, controlled morphology, and minimal defects while remaining cost-effective and environmentally friendly.

The sol–gel method is one of the most widely used techniques for synthesizing metal oxide photocatalysts.64 In this process, metal alkoxides or metal salts are hydrolyzed and condensed to form a colloidal sol, which gradually transforms into a gel network. The gel is subsequently dried and calcined to obtain crystalline photocatalyst particles as shown in Fig. 3A. This method shows excellent control over particle size, composition, and homogeneity. Furthermore, dopants and secondary semiconductors can be easily incorporated into the gel matrix.65 However, the method requires prolonged aging, drying, and high-temperature calcination, which can increase energy consumption and induce particle agglomeration. The microwave-assisted calcination and the use of surfactants have been proposed to reduce synthesis time and improve particle dispersion. In this way, the challenges of sol–gel methods can be resolved.

Fig. 3. Synthesis of photocatalysts by (A) sol–gel method, (B) hydrothermal method, (C) co-precipitation method, and (D) chemical reduction method.

Fig. 3

Another important method of synthesis of photocatalyst is hydrothermal/solvothermal method. Hydrothermal synthesis involves the crystallization of precursor materials in a sealed autoclave under elevated temperature and pressure in an aqueous medium as shown in Fig. 3B.66 The process is called solvothermal synthesis if organic solvents are used instead of water during synthesis. These methods allow the preparation of highly crystalline photocatalysts with controlled morphologies like nanorods, nanowires, nanotubes, and nanoflowers.67 The hydrothermal approach is useful for producing excellent photocatalysts by enhancing the charge separation ability as well as increasing the surface area.68 In this way, synthesized photocatalyst have high active sites and low electron–hole recombination. Therefore, excellent photocatalysts can be synthesized by hydrothermal/solvothermal methods.

Hydrothermal and solvothermal synthesis produce highly crystalline materials compared to the sol–gel method without requiring extremely high calcination temperatures. However, hydrothermal synthesis requires expensive autoclaves and long reaction times. Recent studies suggest that microwave-assisted hydrothermal synthesis can significantly reduce reaction time while maintaining high crystallinity and morphology control.

Co-precipitation is also a method to synthesis the photocatalysts.69 It is a simple and economical technique in which metal ions are simultaneously precipitated from solution by adjusting pH through the addition of precipitating agents like NH4OH or NaOH as shown in Fig. 3C. The resulting precipitates are filtered, washed, dried, and calcinated to produce photocatalysts.70 This method is widely employed for synthesizing mixed metal oxides and doped semiconductor materials owing to its simplicity, scalability, and low cost.

The co-precipitation method is considered highly attractive for industrial-scale production because of its scalability, simplicity, and low cost. Doped and two semiconductor-based photocatalysts can easily be synthesized by this method. But poor control over particle size distribution and phase purity limits its effectiveness. Optimization of precursor concentration, precipitation rate, pH, and post-calcination treatment can substantially improve material uniformity and photocatalytic performance.

Chemical reduction is also commonly used for synthesizing metal nanoparticles and metal–semiconductor composites.71 Metal ions are reduced using reductants like sodium borohydride, hydrazine, or citrate which result to form the nanoscale particles as shown in Fig. 3D. The method provides rapid synthesis and good control over nanoparticle formation.

Chemical reduction methods show rapid nanoparticle formation and excellent control over metal loading in semiconductor-based photocatalysts. These methods are particularly suitable for preparing noble metal-decorated photocatalysts that exhibit enhanced visible-light activity through surface plasmon resonance effects. Nevertheless, conventional reductants like hydrazine and sodium borohydride can be toxic and environmentally hazardous. Green reducing agents derived from plant extracts, amino acids, and biopolymers are increasingly being explored as sustainable alternatives.

Microwave-assisted synthesis is also an important approach to synthesis the photocatalysts. It utilizes microwave irradiation to rapidly heat reaction mixtures which accelerate nucleation and crystal growth.72 Microwave methods significantly reduce reaction time and energy consumption compared with conventional heating and produce highly uniform particles.73 Photocatalysts synthesized through microwave irradiation exhibits improved crystallinity and enhanced photocatalytic activity owing to reduced particle agglomeration.

Among modern synthesis approaches, microwave-assisted synthesis stands out because of its rapid heating, reduced reaction time, energy efficiency, and ability to produce highly uniform nanoparticles. The method minimizes particle agglomeration and enhances crystallinity. The scaling up microwave reactors for industrial production remains challenging even after these advantages. Development of continuous-flow microwave systems has been proposed as a promising solution for large-scale applications.

In sono-chemical synthesis, ultrasonic waves generate acoustic cavitation which leads to localized high temperatures and pressures that promote nanoparticle formation.74 This method enables the synthesis of photocatalysts with small particle sizes, high surface areas, and unique morphologies. Sono-chemical techniques are particularly useful for preparing nanocomposites and doped photocatalysts with enhanced catalytic properties.75

Sono-chemical synthesis also shows rapid nanoparticle formation through acoustic cavitation which generates localized hot spots that promote nucleation and crystal growth.76 But maintaining uniform ultrasonic energy distribution in large reaction volumes remains difficult. Hybrid ultrasonic-hydrothermal systems have been developed to improve synthetic uniformity and scalability.

The combustion method involves a self-sustaining exothermic reaction between metal precursors and fuels like glycine, urea, or citric acid. The rapid release of heat produces highly porous and crystalline photocatalysts. This approach is attractive because it is simple, fast, and energetically efficient.77

The combustion method is highly attractive due to simplicity, rapidity, and energetically efficient. It produces porous photocatalysts with large surface areas which make them highly suitable for pollutant degradation. Nonetheless, the intense exothermic reaction causes particle agglomeration and poor morphology control. The use of controlled fuel-to-oxidizer ratios and template-assisted combustion synthesis can help regulate particle growth and improve structural uniformity.

Green synthesis has gained a significant attention now-a-days due to its environmentally friendly nature which is an alternative to conventional methods.78 Plant extracts, algae, microorganisms, and biopolymers are employed as reductant and stabilizing agents during photocatalyst preparation. The phytochemicals present in plant extracts facilitate nanoparticle formation without the need for hazardous chemicals. Green-synthesized photocatalysts exhibit enhanced biocompatibility and sustainability which make them attractive for environmental remediation applications.79

Green synthesis methods eliminate the need for toxic chemicals. Green synthesis aligns well with sustainable development goals and generates biocompatible photocatalysts. But reproducibility remains a major challenge because biological materials vary in composition depending on species, growth conditions, and extraction procedures. Standardization of extraction protocols and reaction parameters is essential to improve reproducibility and scalability.

The synthesis method plays a critical role in determining the physicochemical properties and photocatalytic performance of semiconductor materials. Among the various approaches, sol–gel and hydrothermal methods remain the most widely adopted methods owing to their ability to produce highly crystalline and homogeneous photocatalysts. Meanwhile, green synthesis and microwave-assisted methods are emerging as sustainable and energy-efficient alternatives. Future research should focus on developing scalable, low-cost, and environmentally benign synthesis strategies capable of producing photocatalysts with enhanced light absorption, efficient charge separation, and long-term stability for environmental remediation applications.

3.2. Synthesis of metal nanoparticles

The catalytic reduction of methyl red (MR) using inorganic nanoparticles has become a subject of growing interest owing to the limitations of conventional treatment methods. Nanoparticles offer unique physicochemical properties like high surface area-to-volume ratio, tunable size, and the ability to accelerate electron transfer reactions which makes them highly efficient in promoting the cleavage of the azo bond in MR. In the presence of reducing agents like sodium borohydride (NaBH4), nanoparticles act as electron mediators, transferring electrons from the donor (BH4−) to dye molecules, thus achieving rapid decolorization and detoxification.80,81 Their performance is strongly influenced by particle size, morphology, composition, and the synthesis route employed.

3.2.1. Mono-metallic nanoparticles

Mono-metallic nanoparticles like Ag,82 Au,83 Pd,84 Fe,29 Ni,85 Cu,86 and Pt87 have been widely studied for MR reduction. They provide a simple yet powerful platform to study structure-activity relationships and fundamental reduction mechanisms. Nanoparticles of noble metals (Ag,88 Au,30 Pd89) and transition metals (Fe,90 Ni,91 Cu92) are especially attractive owing to their high electron conductivity, large surface-to-volume ratios, and tunable surface chemistry. Their ability to adsorb both BH4− ions and dye molecules onto the same surface allows them to function as efficient electron mediators which accelerates the cleavage of the azo bond in MR.

The synthetic methods for mono-metallic nanoparticles strongly influence their catalytic performance, since particle size, morphology, and surface defects are critical determinants of electron transfer and hydrogenation efficiency. Among the most widely used approaches is chemical reduction, in which metal salts (like AgNO3, HAuCl4, or NiCl2) are reduced by reducing agents like sodium borohydride (NaBH4),93 hydrazine,94 or citrate in aqueous95 or organic media.96 This method is popular because of its simplicity and ability to produce small, well-dispersed nanoparticles. However, the use of strong reducing agents can introduce impurities or toxicity issues, and stabilizers like polyvinylpyrrolidone (PVP) or polyethylene glycol (PEG) are needed to prevent aggregation. For example, Arif et al.97 have synthesized Ag NPs in microgel system through in situ reduction method as shown in Fig. 4. During this synthesis, microgels are used for capping agent and NaBH4 as reductant.

Fig. 4. Synthesis of Ag NPs in microgels (capping agent) through in situ reduction method.97 Figures adapted from ref. 97 with permission from RSC, copyright 2025.

Fig. 4

Another synthetic route is thermal decomposition, where metal precursors are decomposed at elevated temperatures in the presence of stabilizing agents. This method provides better control over particle size and crystallinity but requires higher energy input and sometimes organic solvents, which can limit environmental friendliness. Electrochemical synthesis has also been reported which offers precise control over particle growth and morphology by adjusting applied potential and electrolyte composition. Similarly, microwave-assisted synthesis accelerates nucleation and growth which produces uniform nanoparticles within min. It highlights its potential for scalable production. For example, Punnoose et al.98 have synthesized Ag NPs loaded Coleus amboinicus through microwave irradiation as shown in Fig. 5. Here Coleus amboinicus acts as stabilizer in this synthesis and irradiation of microwave oven reduced the Ag+ ions into Ag NPs. Banu et al.99 have also synthesized Au NPs loaded carboxymethyl cashew gum by microwave irradiation.

Fig. 5. Synthesis of Ag NPs loaded in capping agent through microwave irradiation.98 Figures adapted from ref. 98 with permission from Springer, copyright 2023.

Fig. 5

In recent years, green synthesis methods have attracted growing attention as sustainable alternatives. Plant extracts, microbial metabolites, or biopolymers (e.g., chitosan, starch, alginate) act as reducing and capping agents which enable eco-friendly synthesis without toxic chemicals.100 For example, silver nanoparticles synthesized using plant polyphenols or polysaccharides not only display high catalytic activity but also exhibit enhanced biocompatibility and stability.101 Such approaches align with the principles of green chemistry and are increasingly preferred for environmental applications like dye remediation. For example, Saba et al.102 have synthesized Ag NPs by using Keratinase from Pseudomonas aeruginosa-C1M. It acts as reducing agent as well as stabilizer. It donates the electron to the Ag+ ions and converts it into neutral Ag0 atoms which coagulate to form cluster in nano-range. Similarly, Zahran et al.88 have also synthesized Ag NPs by using mucilage as shown in Fig. 6. They obtained mucilage from Opuntia ficus-indica (plant) and used then for conversion of Ag+ ions into Ag NPs.

Fig. 6. Synthesis of Ag NPs through green method.88 Figures adapted from ref. 88 with permission from Elsevier, copyright 2025.

Fig. 6

The catalytic efficiency of mono-metallic nanoparticles in MR reduction is highly dependent on their structural attributes. Smaller particles provide higher surface area and more active sites, but they are more prone to aggregation. Morphology also plays a decisive role as anisotropic shapes like nanorods, nanoplates, and nanostars expose high-energy facets that facilitate faster electron transfer compared to spherical particles.103 Surface defects, grain boundaries, and crystallographic orientation further influence electron mobility and adsorption strength of MR molecules. Therefore, tailoring synthetic conditions to produce nanoparticles with optimized size, shape, and surface chemistry remains central to improving their performance.

Their practical application is limited by stability and reusability issues even after their mono-metallic nanoparticles demonstrate significant activity. For example, silver nanoparticles readily oxidize, while Ni and Cu nanoparticles are prone to corrosion in aqueous media. To overcome these drawbacks, researchers immobilize mono-metallic nanoparticles onto supporting materials like graphene oxide,104 mesoporous silica,105 or polymeric hydrogels.106 This not only prevents aggregation but also makes hybrid systems that combine adsorption with catalysis and enhanced their overall efficiency.

Mono-metallic nanoparticles provide a valuable foundation for understanding the reduction of MR due to their simple synthesis and well-defined catalytic behavior. However, their limitations in stability and recyclability have motivated the development of advanced multi-metallic and supported systems. Future efforts should focus on refining eco-friendly synthesis techniques and engineering mono-metallic nanoparticles with controlled morphology and surface functionality to maximize their catalytic potential while minimizing environmental risks.

3.2.2. Bimetallic nanoparticles

Although mono-metallic nanoparticles are effective, their catalytic performance is limited by issues like surface oxidation, aggregation, and deactivation over multiple cycles. To overcome these challenges, bimetallic nanoparticles have been developed, which exhibit synergistic effects owing to the combination of two different metals.34,107–111 The interaction between two metals can modify the electronic structure, increase active surface sites, and improve catalytic stability. One of us has written a review article on bimetallic systems which explains all parameters of high catalytic activity during reduction reactions. The readers can learn complete knowledge from that review article.50

Bimetallic nanocomposites have shown significant potential in MR reduction, where one metal facilitate the other to show catalytic performance during catalytic reduction reactions. For example, Ag–Cu nanoparticles exhibit superior performance owing to the combined redox properties of Ag and the electron relay efficiency of Cu.112 Other bimetallic systems such as Au–Ag,113 Cu–Ag,114 and Ir–Cu115 have also been reported to accelerate azo bond cleavage and enhance reaction kinetics. These catalysts not only show faster reduction rates but also demonstrate improved recyclability and resistance to poisoning by dye intermediates which makes them more practical for repeated applications in wastewater treatment.

Lin et al.116 have reported the synthesis of bimetallic (Au–Ag) nanoparticles through microwave-assisted green route as shown in Fig. 7. For this purpose, they used Melaleuca quinquenervia leaf as plant extraction and then added the AgNO3 and HAuCl4 salts into it. This mixture was then irradiated with microwaves. During this method, bimetallic (Au–Ag) alloy was formed. While for the synthesis of core–shell formation, one type of metal nanoparticles is formed first followed by second type metal nanoparticles around the first formed metal nanoparticles.

Fig. 7. Synthesis of bimetallic (Au–Ag) nanoparticles by microwave-assisted green method.116 Figures adapted from ref. 116 with permission from MDPI, copyright 2025.

Fig. 7

The identification of their morphology is the main issue. They can make core–shell morphologies or alloy form. This morphology is confirmed by TEM or HRTEM but still the percentage in core region and shell region of metal nanoparticles remain an issue still. The percentage composition of metal nanoparticles in bimetallic systems greatly affects catalytic performance. Therefore, it is very important to find the percentage composite in core and shell region of each metal. This identification is a challenge for future research.

3.2.3. Tri-metallic nanoparticles

The design of tri-metallic nanoparticles represents the latest advancement in nano-catalyst research for dye reduction. By incorporating three different metals, these catalysts exploit multi-metallic synergy which provides multiple electron transfer pathways and enhanced stability compared to mono- or bimetallic systems. The presence of three metals allows fine-tuning of catalytic activity through electronic and geometric effects which results in superior reduction kinetics and durability.117–119

Ag–Cu–Zn nanoparticles are one such example which indicate superior performance of MR reduction compared to their bimetallic counterparts.120 The combined presence of Zn and Cu promotes rapid electron transfer, while Ag enhances catalytic stability and prevents nanoparticle deactivation. Similarly, tri-metallic combinations of noble metals such as Pd–Au–Cu have been reported to provide exceptional catalytic efficiency, although their high-cost limits large-scale applications.121 Despite these limitations, tri-metallic nanoparticles represent a promising avenue for future research, particularly if their synthesis can be achieved through cost-effective and environmentally friendly methods. Gupta et al.122 have synthesized tri-metal (Ag/Fe/Ni) nanoparticles from orange peels extraction as shown in Fig. 8. The orange peels act as reducing agent as well as stabilizer for these metal nanoparticles. Their metal salts are simultaneously mixed into the extracted solution of orange peels and stirred with heating. The trimetallic nanoparticles were then used for degradation of MR in aqueous medium.

Fig. 8. Synthesis of trimetallic (Ag/Fe/Ni) nanoparticles by using extraction of orange peels.122 Figures adapted from ref. 122 with permission from Elsevier, copyright 2024.

Fig. 8

Nanoparticles play a central role in the catalytic reduction of MR. While mono-metallic systems provide a foundation for understanding the mechanism of dye reduction, bimetallic and tri-metallic nanoparticles show superior performance due to synergistic effects and enhanced stability. These advancements highlight the potential of engineered nano-catalysts as powerful tools for efficient and sustainable dye remediation.

Their morphological identification is more complicated compared to bimetallic nanoparticles due to more mixing components. Their morphologies can be core–shell–shell or alloy(core)–shell or alloy from. To find the percentage of metal nanoparticles at different places is a challenge because some content of each metal will be present in each section due to metallic interactions. The percentage of each metal depends on their reduction potential and coagulating capacity. The percentage composition of metal nanoparticles in trimetallic systems greatly controls the synergistic effect which enhances catalytic performance. Consequently, it is an empty space for the new researcher working on such systems.

3.2.4. Tetra-metallic nanoparticles

Tetra-metallic nanoparticles represent a new frontier in catalytic systems for dye remediation like reduction of MR. Unlike mono-, bi-, or tri-metallic systems, tetra-metallic nanostructures integrate the synergistic effects of four different metals which offer unique electronic, structural, and surface properties that cannot be achieved by simpler alloys. The presence of multiple metals enhances electron density, modifies surface plasmon resonance, and generates heterogeneous active sites. In this way, they accelerate electron transfer from reducing agents like NaBH4 to the azo group of MR.123

A critical advantage of tetra-metallic nanoparticles is their tunable composition, which allows optimization of catalytic activity by adjusting the proportion of each component. The presence of multiple metals reduces the risk of catalyst deactivation, as different elements stabilize the surface against oxidation, leaching, or aggregation. Additionally, lattice strain induced by alloying improves adsorption of MR molecules and facilitates cleavage of the azo bond (–N Created by potrace 1.16, written by Peter Selinger 2001-2019 N–).124 However, despite their promise, these systems face important challenges. The synthesis of well-defined tetra-metallic nanoparticles with controlled size and composition is complex, requiring precise methods such as co-reduction, seed-mediated growth, or polyol synthesis. Cost and scalability are also concerns, especially when noble metals are heavily used. Moreover, while tetra-metallic nanoparticles demonstrate outstanding efficiency in laboratory conditions, their long-term stability, recyclability, and environmental safety in real wastewater systems remain underexplored. Haque et al.125 have synthesized Ag–Ni–Mn–Zn tetra-metallic nanoparticles. This system consists of Ag, Ni, Mn, and Zn atoms. They found that their catalytic performance was excellent and degraded 97.67% of MR even in 60 min. This effect is due to the synergistic effect of four metals.

Tetra-metallic nanoparticles provide a highly efficient catalytic platform for MR reduction due to their multi-metal synergy, enhanced electron transfer from reductant to pollutant, and structural robustness. Yet, the complexity of synthesis, potential cost barriers, and limited real-world validation highlight the need for further research to translate their exceptional laboratory performance into scalable, environmentally sustainable applications.

4. Supporting materials for stabilizing nanoparticles

One of the major limitations of nanoparticles in catalytic applications is their tendency to agglomerate owing to high surface energy, which reduces the number of accessible active sites and diminishes their catalytic performance. Moreover, bare nanoparticles suffer various issues as discussed in previous sections. To resolve these challenges, researchers have developed various supporting matrices to immobilize nanoparticles, which not only prevent aggregation but also enhance dispersibility, stability, and reusability. Supporting materials also provide additional functionalities like adsorption of dye molecules, electron shuttling, and stimuli-responsive behavior.126–129 These parameters improve their overall efficiency of the catalytic reduction of MR.

4.1. Inorganic and carbon-based supporting materials

Inorganic and carbon-based supporting materials have been extensively employed to stabilize nanoparticles for the catalytic reduction of MR. Nanoparticles in their pristine form tend to cluster owing to high surface energy, which decreases the availability of active sites and reduces catalytic performance. Immobilizing nanoparticles on stable inorganic or carbonaceous matrices not only preserves their dispersion but also enhances durability, recyclability, and catalytic selectivity. Beyond stabilization, supporting materials actively contribute to dye degradation by providing adsorption sites, facilitating electron transfer, and in some cases, exhibiting photocatalytic or redox activity of their own.

Graphene oxide (GO)130 and reduced graphene oxide (RGO)131 are among the most widely investigated carbon-based supporting materials because of their high surface area, excellent electrical conductivity, and abundant oxygen-containing functional groups as shown in Fig. 9a. These properties enable efficient immobilization of nanoparticles through electrostatic interactions or covalent bonding, while also promoting π–π stacking interactions with aromatic structures of MR.132,133 Such interactions concentrate dye molecules near catalytic sites, improving reaction kinetics. Moreover, RGO enhances electron shuttling between NaBH4 and MR and thus accelerating the reduction process. However, a critical limitation of GO-based supporting materials is their tendency to restack during synthesis, which can reduce accessible surface area and hinder dye diffusion. Strategies such as doping with heteroatoms (N, S) or combining GO with polymers are being explored to overcome this drawback.

Fig. 9. Metal nanoparticles (blue circle) stabilized with various supporting materials like (a) graphene oxide sheet, (b) porous silica, (c) doped ZnO, (d) MOFs, and (e) chitosan sheet.

Fig. 9

Activated carbon (AC)134 and carbon nanotubes (CNTs)135 also serve as excellent supporting materials because of their highly porous structure, large surface-to-volume ratio, and chemical inertness. Activated carbon is particularly effective in pre-concentrating MR molecules due to strong adsorption, while CNTs offer unique one-dimensional conductivity that enhances electron transfer.136,137 Nevertheless, both materials are expensive to produce in highly pure forms, and regeneration of activated carbon after dye adsorption can require harsh conditions which limit it to large-scale applications. Despite these challenges, their ability to combine strong adsorption with catalytic activity makes them attractive supports in hybrid nanocomposites.

Mesoporous silica138 materials have received significant attention owing to their ordered pore structures, tunable surface functionality, and ability to confine nanoparticles within nanoscale pores among inorganic supporting materials as shown in Fig. 9b. This confinement not only prevents aggregation but also provides a uniform environment for catalytic reactions.29 Furthermore, silica is chemically stable, non-toxic, and inexpensive which makes it a practical choice for wastewater treatment. However, silica itself is not conductive, which can limit electron transport, and hence functionalization with conductive polymers or carbon is necessary to improve catalytic efficiency.

Metal oxides like TiO2,139 Al2O3,140 CeO2,141 and Fe3O4 (ref. 142) also play an important role as nanoparticle supports. TiO2 and CeO2 can participate directly in photocatalytic reactions, generating reactive oxygen species that complement nanoparticle-driven reduction pathways.141,143,144 Fe3O4 provides the unique advantage of magnetic recovery, allowing rapid separation of catalysts from treated water using external magnets which enhance their reusability.145 Metal oxide support faces issues like photo-corrosion, leaching under acidic/basic conditions, or limited light absorption in the visible range, which restricts their practical utility. Therefore, recent research has focused on doping or coupling metal oxides with carbon-based materials to improve stability and extend activity under broader operating conditions.146 The doped materials like metal doped ZnO (Fig. 9c) show better performance under visible light irradiation due to decreasing the band gap energy.

Inorganic and carbon-based supporting materials enhance nanoparticle stability and efficiency, while their own synthesis and modification involve energy-intensive or chemical-heavy processes, which may reduce their overall environmental friendliness. Furthermore, balancing adsorption capacity with catalytic activity is a continuing challenge: excessive adsorption may sequester MR molecules without enabling efficient reduction, while insufficient adsorption reduces the probability of dye–catalyst interactions. Therefore, future research must focus on developing hybrid supports that integrate the conductivity of carbon materials, the porosity of silica, and the magnetic/photocatalytic properties of oxides to produce multifunctional systems. Such integrated supporting materials could address the individual limitations of each material, offering superior performance for MR remediation in complex wastewater environments.

4.2. Metal–organic frameworks (MOFs)

Metal–organic frameworks (MOFs) have emerged as one of the most versatile classes of materials for stabilizing nanoparticles and enhancing catalytic processes for dye degradation like the reduction of MR as shown in Fig. 9d. MOFs are crystalline porous materials composed of metal ions or clusters coordinated with organic linkers which generate highly ordered, tunable three-dimensional networks. Their main advantages are exceptionally high surface area, adjustable pore sizes, and the possibility of functionalizing organic linkers with specific chemical groups. These properties make MOFs attractive hosts for nanoparticle incorporation, as they not only prevent aggregation but also provide uniform distribution of catalytic sites within well-defined channels.147

The integration of nanoparticles into MOFs can occur through various strategies. In the “ship-in-bottle” method, nanoparticles are synthesized inside the pores of the MOF which ensure excellent confinement and size control.148 In contrast, the “bottle-around-ship” method involves growing the MOF around pre-synthesized nanoparticles which encapsulate them in a protective porous shell.149 A third approach is surface immobilization, where nanoparticles are deposited on the outer surface of MOFs.150 Each method has its own advantages: pore confinement ensures stability and prevents agglomeration, while surface loading allows easier accessibility of active sites to MR molecules. By tailoring the synthesis approach, researchers can control the distribution, size, and catalytic accessibility of nanoparticles in MOF-nanocomposites.

A critical advantage of MOFs lies in their ability to adsorb dye molecules within their porous channels, effectively pre-concentrating MR near catalytic sites. This local enrichment enhances the probability of electron transfer and accelerates reduction kinetics. Furthermore, the modular design of MOFs allows the introduction of functional groups (e.g., –NH2, –COOH, –SO3H) on linkers, which can improve interactions with MR molecules through hydrogen bonding, electrostatic forces, or π–π interactions.151 For example, amine-functionalized MOFs have been reported to improve MR adsorption and subsequent catalytic reduction when loaded with noble metal nanoparticles such as Ag or Au.152,153

MOFs themselves can exhibit catalytic or photocatalytic activity along with adsorption and stabilization of nanoparticles. Transition metal-based MOFs (e.g., Ni-MOF, Cu-MOF, Fe-MOF) can participate directly in redox reactions or act as photoactive centers under visible light irradiation.44 These frameworks show synergistic effects when coupled with nanoparticles, where MOFs provide structural stability and adsorption capacity, while nanoparticles facilitate electron transfer and azo bond cleavage.154 For instance, Zn-loaded Cu-MOF composites have been reported to achieve rapid MR reduction due to this dual functionality.151

MOFs also face critical challenges during the degradation of MR process. Many MOFs suffer from poor stability in aqueous media (especially under acidic or alkaline conditions) which limits their long-term use in wastewater treatment. Furthermore, large-scale synthesis of MOFs is expensive and energy-intensive, involving toxic organic solvents and lengthy crystallization processes. The regeneration and recyclability of MOF-nanocomposites also require further investigation, as repeated use can lead to pore blockage, structural collapse, or nanoparticle leaching. These challenges highlight the need for designing more robust, water-stable MOFs, such as zirconium- or titanium-based frameworks, which have demonstrated superior chemical stability.

The future of MOFs as supporting materials for nanoparticle-based MR reduction lies in the development of hybrid materials. Combining MOFs with carbon-based supports, polymers, or hydrogels could overcome their stability issues while preserving their high porosity and tunability. Furthermore, the design of stimuli-responsive MOFs, capable of adjusting their porosity or catalytic activity in response to changes in pH, temperature, or light, represents an exciting opportunity for creating “smart” nanocatalysts tailored for complex wastewater environments.155 If issues of scalability and durability can be addressed, MOF-based nanocomposites have the potential to play a transformative role in sustainable dye remediation technologies.

4.3. Polymeric supporting materials

Polymeric materials have emerged as versatile and effective supporting materials for stabilizing nanoparticles used in the catalytic reduction of MR. Unlike rigid inorganic supporting materials, polymers provide flexibility, tunability, and functional diversity, which allow for strong interactions with metal nanoparticles and enhanced dispersion within the matrix. Polymers like chitosan156 (as shown in Fig. 9e), polyvinyl alcohol (PVA),157 polydopamine (PDA),158 and synthetic hydrogels/microgels127,159 (as shown in Fig. 9f) have been widely studied as hosts for nanoparticles in dye remediation. Their key advantage lies in the abundance of functional groups (–NH2, –OH, –COOH, –CONH2) that can chelate or coordinate metal ions which control uniform nucleation and growth of nanoparticles within the polymer network. This strong interaction prevents nanoparticle aggregation, reduces leaching, and significantly enhances catalyst stability during repeated use.

Chitosan (a naturally derived polysaccharide) has gained particular importance owing to its biocompatibility, biodegradability, and environmental safety. The amino and hydroxyl groups of chitosan provide active sites for NP immobilization, while its film-forming and gel-forming abilities allow for the fabrication of stable nanocomposite membranes or beads.28 In MR reduction, chitosan-based nanocomposites not only stabilize catalytic nanoparticles but also contribute to dye adsorption through electrostatic interactions between the negatively charged MR molecules and protonated amino groups of chitosan. This dual function of adsorption and catalysis enhances the overall efficiency of dye removal.160,161 However, chitosan suffers from limitations like poor solubility in neutral water and susceptibility to swelling, which can reduce mechanical strength during prolonged use. Crosslinking or blending synthetic polymers has been suggested to overcome these drawbacks.

Polydopamine (PDA) has recently emerged as a multifunctional polymeric supporter with unique advantages. Inspired by the adhesive properties of mussel proteins, PDA can coat almost any surface and provide abundant catechol and amine groups for nanoparticle anchoring.162 More importantly, PDA can actively participate in redox reactions, serving as an electron mediator during catalytic processes. In MR reduction, PDA-supported nanoparticles demonstrate enhanced electron transfer between NaBH4 and dye molecules which accelerate azo bond cleavage.163 The simplicity of PDA coating and its multifunctionality make it a promising support material for next-generation nano-catalysts.

Hydrogels and microgels provide another important class of polymeric supporting materials. Their three-dimensional, porous, and water-swollen structures act as nano-reactors that trap and stabilize nanoparticles while allowing free diffusion of dye molecules and reducing agents. This structural confinement minimizes nanoparticle leaching, improves recyclability, and offers stimuli-responsive behavior, where changes in pH or temperature can tune the swelling properties of the gel and regulate catalytic activity.164 For instance, pH-sensitive hydrogels can swell in acidic media, increasing dye uptake and enhancing reduction kinetics.39 Despite these advantages, hydrogels may suffer from poor mechanical strength and slow response times, which can limit their industrial applicability.165 Research is ongoing to reinforce hydrogels with inorganic fillers or graphene derivatives to overcome these issues.

Polymeric supporting materials address many of the shortcomings of inorganic materials by offering tunability, flexibility, and multifunctionality, but they also present new challenges. Many polymers are sensitive to temperature,166 pH,39 or enzymatic degradation, which can control catalyst stability under harsh wastewater conditions. Furthermore, large-scale fabrication of polymer-nanoparticle composites often requires crosslinkers or stabilizing agents that cannot be environmentally benign. To advance this field, future work should focus on developing hybrid polymeric supporting materials that combine natural and synthetic polymers, engineering stimuli-responsive gels for smart catalysis, and improving the long-term mechanical and chemical stability of polymer–nanoparticle composites.

Polymeric supporting materials play a dual role in MR reduction: they provide structural stabilization for nanoparticles and actively enhance catalytic activity through adsorption, electron mediation, or responsive behavior. By combining biocompatibility, functional versatility, and structural tunability, polymer-based supporting materials hold strong potential for developing next-generation, sustainable nano-catalysts for dye remediation.

5. Characterization techniques

Characterization plays a crucial role in understanding the physicochemical properties of metal nanoparticles and semiconductor photocatalysts. The catalytic and photocatalytic performance of these materials is strongly influenced by their surface area, morphology, particle size, crystal structure, charge transfer behavior, elemental composition, optical properties, and thermal stability. Therefore, various analytical techniques are employed to establish structure–property relationships and explain catalytic performance. Transmission electron microscopy (TEM), X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence spectroscopy (PL), energy dispersive X-ray spectroscopy (EDS/EDX), X-ray photoelectron spectroscopy (XPS), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET),167 raman spectroscopy (RS),168 thermogravimetric analysis (TGA), and electrochemical impedance spectroscopy (EIS) techniques are used to characterization the catalytic and photocatalytic materials as given in Table 1.

Table 1. Characterization technique used for identification of catalytic and photocatalytic materials.

Systems Nanoparticles Supporting agents Catalytic reduction/photocatalytic degradation Characterization techniques References
TiO2–Fe2O3 TiO2 Fe2O3 Photocatalytic degradation FE-SEM, RS, EDS, and DRX 168
ZnS–NiS ZnS, NiS — Photocatalytic degradation UV-vis, XRD, TEM, FTIR, SEM, BET, and RS 178
Ag-ML Ag ML Catalytic reduction UV-vis, SEM, square wave voltammetry (SWV), TEM, and cyclic voltammetry (CV) 171
CeO2-g-C3N4 CeO2 g-C3N4 Photocatalytic degradation TEM, TGA, XRD, SEM, FTIR, and BET 167
Ni–Au Ni, Au — Catalytic reduction TEM, XRD, SEM, HR-TEM 172
MgO-SA MgO SA Catalytic reduction SEM, EDX, XRD, FTIR, XPS, and UV-vis 173
UiO-66-MoS2 MoS2 UiO-66 Photocatalytic degradation HRTEM, FTIR, XRD, EDX, and BET 68
Ag–CaO, Ag–CaO-PAni, Ag–CaO-SA-PAni Ag, CaO PAni, SA Catalytic reduction XRD, SEM, FTIR, EDX, and BET 169
Ag Ag — Catalytic reduction SEM, UV-vis, TEM, DLS, Zeta-sizer FTIR, and XRD. 175
Cu Cu — Catalytic reduction FTIR, TGA-DTA, SEM-EDX, XRD, VSM, and UV-vis 170
Ag–Cu–TiO2 Ag, Cu, TiO2 — Catalytic reduction FTIR, zeta potential analysis, FE-SEM, XRD, EDX, and UV-vis 174
Bi–ZnO Bi, ZnO — Photocatalytic degradation XRD, BET, UV-vis, SEM, EDX, FTIR 64
Ag–ZnO-GO Ag, ZnO GO Photocatalytic degradation UV-vis DRS, XRD, PL, SEM, TEM, EDX 176
ZnO ZnO — Photocatalytic degradation TEM, FTIR, XRD, EDS, SEM, UV-vis 78
α-Fe2O3 α-Fe2O3 — Photocatalytic degradation RS, XRD, EDX, FESEM, UV-vis, EIS 177

XRD is one of the most widely used techniques for determining the crystalline structure, crystallite size, phase composition, and purity of nanoparticles and semiconductor photocatalysts.169 The diffraction peaks obtained in XRD patterns are compared with standard reference databases to identify crystalline phases. The average crystallite size can be estimated using the Scherrer equation. Sharp and intense diffraction peaks generally indicate high crystallinity, which is beneficial for charge transport and photocatalytic activity.

SEM is employed to investigate surface morphology, porosity, particle distribution, and aggregation behavior.170 SEM images provide information about the shape and texture of synthesized materials like spherical nanoparticles, nanosheets, nanowires, nanorods, nanotubes, and flower-like structures. This technique is useful for evaluating catalyst surface roughness and porosity, which directly influence adsorption capacity and catalytic efficiency. SEM reveals whether nanoparticles are uniformly distributed or aggregated within a supporting matrix.

TEM provides high-resolution images that allow direct observation of particle size, crystal lattice fringes, shape, and nanoparticle dispersion. TEM is one of the most powerful tools for nanomaterial characterization because it can reveal individual nanoparticles and heterojunction interfaces.171 High-resolution TEM (HRTEM) can further determine interplanar spacing and crystal orientation which confirm the formation of specific crystalline phases.172 TEM analysis demonstrates successful nanoparticle immobilization on supporting materials like GO, carbon nanotubes, polymers, and MOFs.

EDS is coupled with SEM or TEM to determine elemental composition and elemental distribution. The technique confirms the presence of constituent elements in mono-metallic, bi-metallic, tri-metallic, and tetra-metallic nanoparticles.68 Elemental mapping generated through EDS analysis provides evidence of homogeneous distribution of metals within nanocomposites. The absence of unexpected elemental peaks indicates successful synthesis and high purity of the catalyst.

XPS is used to investigate surface elemental composition, oxidation states, and chemical bonding environments.173 Since catalytic reactions primarily occur on the catalyst surface, XPS provides critical information regarding active sites. Changes in binding energy indicate electron transfer between catalyst components which provide evidence for strong metal-supporter interactions and heterojunction formation.

FTIR is employed to identify functional groups, chemical bonds, and surface interactions between nanoparticles and supporting materials.174 Characteristic absorption bands reveal the presence of amine groups, carboxyl groups, metal–oxygen bonds, hydroxyl groups, and polymeric functionalities. In supported catalysts, FTIR confirms successful incorporation of nanoparticles into polymeric matrices, microgels, hydrogels, or carbon-based supports. Surface hydroxyl groups detected by FTIR are particularly important because they participate in the generation of hydroxyl radicals during photocatalysis.

UV-vis DRS is extensively used to evaluate optical properties and band-gap energy of semiconductor photocatalysts.175,176 The absorption spectrum indicates the wavelength range over which a photocatalyst can utilize light. Band-gap values are calculated using Tauc plots. A shift in absorption toward the visible-light region indicates improved solar-light utilization. In metal–semiconductor composites, surface plasmon resonance peaks of noble metals such as Ag and Au can also be observed which confirm successful metal deposition and enhanced visible-light absorption.

Photoluminescence spectroscopy is used to evaluate the recombination behavior of photogenerated electron–hole pairs.176 Lower PL intensity indicates reduced charge carrier recombination and more efficient charge separation. Since efficient charge separation is essential for photocatalytic reactions, PL analysis is used to compare the photocatalytic potential of different materials. Doped semiconductors and heterojunction photocatalysts exhibit lower PL intensity than pristine materials.

BET analysis provides information regarding specific surface area, pore volume, and pore size distribution.167 Higher surface areas provide more active sites for adsorption and catalytic reactions. Mesoporous photocatalysts exhibit large surface areas and well-defined pore structures which enhance pollutant adsorption and degradation efficiency. BET results help explain differences in catalytic activity among materials with similar compositions but different textural properties.

Raman spectroscopy provides information about crystal structure, molecular vibrations, defects, and phase composition.168 It is particularly useful for characterizing carbon-based materials such as graphene oxide, reduced graphene oxide, and carbon nanotubes. The D-band and G-band intensities provide insights into structural defects and graphitization. In semiconductor photocatalysts, Raman spectra can identify crystalline phases and detect structural distortions resulting from doping or defect engineering.

TGA evaluates thermal stability, decomposition behavior, and composition of nanomaterials.170 TGA is important for polymer-supported catalysts, hydrogels, microgels, and MOF-based composites. Weight loss profiles reveal the removal of adsorbed water, decomposition of organic components, and thermal stability of the catalyst. High thermal stability is desirable for catalyst regeneration and long-term applications.

EIS is used to investigate charge-transfer resistance and electron transport properties.177 Smaller semicircle diameters in Nyquist plots indicate lower charge-transfer resistance and more efficient electron mobility. Photocatalysts exhibiting low charge-transfer resistance demonstrate superior photocatalytic performance because photogenerated electrons can migrate more effectively to reaction sites.

Photocurrent analysis evaluates the separation and migration efficiency of photogenerated charge carriers. Higher photocurrent density indicates more efficient charge separation and lower recombination rates. This technique is frequently used to assess the effectiveness of heterojunction formation, doping, and cocatalyst loading in semiconductor photocatalysts.

6. Catalytic treatment of methyl red

The catalytic treatment of MR has gained significant attention as an efficient and sustainable strategy for dye remediation. Unlike conventional methods that often suffer from incomplete degradation or secondary pollution, catalytic approaches using nanoparticles promote rapid and selective cleavage of the azo bond which leads to effective decolorization and detoxification. Two major pathways are commonly reported for MR treatment: (i) chemical reduction in the presence of reducing agents like sodium borohydride (NaBH4),39 and (ii) photocatalytic degradation under light irradiation.179

6.1. Chemical reduction

Chemical reduction using NaBH4 alone is thermodynamically favorable but kinetically slow because of the large activation energy barrier between borohydride ions and MR molecules. In this context, nanoparticles act as electron-transfer mediators which provide an active surface for adsorption of both MR molecules and BH4− ions as shown in Fig. 10. After adsorption of both, the interactions are generated between hydride and MR. Gradually the old bonds of dye and hydride are broken, and new bonds are formed which produce the amines in the final product.102 These amines are now detached from the surface of metal nanoparticles to the bulk region. During this mechanism, BH4− donates the hydride to the dye molecules through the surface of metal nanoparticles and MR gets protons from water during same time. In this way, one hydrogen atom is attached to one nitrogen atom of azo group and second hydrogen with other nitrogen atom of same azo group. In this way, two hydrogen atoms are attached with each nitrogen atom of azo group to form diamine derivatives. The solution of diamine derivates is colorless. The eqn (1) is used to calculate the apparent rate constant (kapp) of pseudo 1st order kinetics.

6.1. 1

here, Co stands for initial concentration of MR, Ct denotes to the MR concentration at time t, t represents the reaction time, and kapp is the rate constant which is called apparent rate constant (kapp). Eqn (12) can also be expressed in terms of absorbance (A) using the Beer–Lambert law, as follows:

6.1. 2

Fig. 10. Catalytic reduction of methyl red by metal nanoparticles loaded microgels.

Fig. 10

The reaction is described by Langmuir–Hinshelwood kinetics or pseudo-first-order kinetics, depending on the concentration of MR and the availability of active sites.39,180

The eqn (3) was used for pseudo 2nd order kinetic reactions.

6.1. 3

The suitability of pseudo 1st and pseudo 2nd order catalytic reaction is determined by the comparison of R2 values. If the value of R2 of pseudo 2nd order is greater than R2 of pseudo 1st order catalytic reaction. It means that the pseudo 2nd order is more suitable than pseudo 1st order catalytic reaction for mechanism. And if the R2 value of pseudo 2nd order is less than R2 of pseudo 1st order then pseudo 1st order reaction is more suitable for reaction mechanism. In this way, the most suitable order for catalytic reaction can be found by comparison of R2 values of pseudo 1st and 2nd order reactions.

The rate constant is strongly dependent on the nature of the catalyst, where smaller nanoparticles with high surface-to-volume ratios exhibit faster electron transfer. Additionally, anisotropic shapes like nanorods or nanosheets expose high-energy facets that further enhance the reaction kinetics. For example, silver nanoparticles supported by reduced graphene oxide have been shown to accelerate MR reduction within min, owing to synergistic adsorption and electron-shuttling effects.181

Another critical advantage of nanoparticle-mediated reduction is the selectivity of the process. While other treatment methods can partially degrade MR into intermediate compounds that are still toxic, chemical reduction often results in complete cleavage of the azo bond which leads to less harmful amines. However, the toxicity of these by-products cannot be completely ignored, and their further mineralization can be necessary to ensure safe discharge. In addition, catalyst recyclability and stability remain important challenges, as nanoparticles can undergo leaching or surface fouling after repeated cycles.

They can also lead to the formation of aromatic amines as intermediate products, while hydrogenation pathways accelerate azo bond cleavage. Although these intermediates are less colored and less stable than the parent dye, they can still exhibit toxicity which raises environmental issues. Therefore, combining hydrogenation-driven reduction with subsequent oxidative or photocatalytic mineralization is often necessary to ensure complete detoxification of MR-contaminated water.

6.2. Photocatalytic degradation

Photocatalytic degradation has emerged as a complementary pathway for MR treatment. In this process, semiconductor nanoparticles like TiO2,182 ZnO,183 CdS,184 g-C3N4,185 and doped metal oxides186 are irradiated with UV or visible light to generate electron–hole pairs. The vallance band (VB) electrons migrate to the conduction band (CB) (if the energy of irradiated light is greater than band gap energy) while holes remain in the valence band. The conduction electrons react with oxygen molecules to form O2˙– and holes with water molecules to form ˙OH187 as shown in Fig. 11. The O2˙– radicals react with water molecules to produce HOO˙ which produce H2O2 after combining the two HOO˙ radicals. These H2O2 produce OH radicals after decomposition. These radicals then attack MR molecules which break down the aromatic structure into CO2, H2O, and other non-toxic inorganic products188 as given in eqn (4)–(10).

Semiconductor + hv → eCB− + hVB+ 4

Fig. 11. Photocatalytic degradation mechanism of methyl red with semiconductors.

Fig. 11

Reaction at CB:

eCB− + O2 → O2˙− 5
O2˙− + H2O → HOO˙ + OH− 6
HOO˙ + HOO˙ → H2O2 + O2 7
H2O2 → 2OH˙ 8

Reaction at VB:

H2O/OH− + hVB+ → OH˙ + H+/OH˙ 9

Overall reaction:

MR + OH˙/O2˙− → intermediate → CO2 + H2O + NH3 10

Photocatalysis has several advantages over chemical reduction like complete mineralization of MR and avoidance of secondary pollution. However, the process is strongly dependent on catalyst design. For instance, bare CdS is limited by its wide band gap which requires UV light, and by the rapid recombination of electron–hole pairs, which reduces efficiency.189 To address these issues, researchers have explored doping with metals or nonmetals, coupling with other semiconductors, and loading with noble metal nanoparticles to extend light absorption into the visible region and suppress recombination. For example, Ag–ZnO nanocomposites have demonstrated significantly higher MR degradation efficiency due to plasmonic effects of Ag, which enhance light harvesting and electron transfer.190

In conclusion, catalytic treatment of MR through reduction and photocatalysis provides a highly effective route for its removal from wastewater. While chemical reduction ensures rapid decolorization through azo bond cleavage, photocatalysis enables further breakdown of toxic intermediates into benign products. The integration of these two processes, combined with advancements in nanoparticle design and support engineering which holds strong potential for developing sustainable and scalable dye remediation technologies.

6.3. Oxidative degradation

In addition to chemical reduction and photocatalysis, oxidative degradation has been widely studied as an alternative pathway for the treatment of MR.55 Oxidative degradation relies on the generation of highly reactive oxygen species (ROS), particularly hydroxyl radicals (˙OH), which are among the strongest oxidants known in aqueous systems.191 These radicals are capable of non-selectively attacking the aromatic rings and azo linkages of MR, ultimately leading to complete mineralization into CO2, H2O, and inorganic ions.192 The most common approaches for ROS generation include advanced oxidation processes (AOPs) like Fenton and photo-Fenton reactions, ozonation, persulfate activation, and photocatalytic oxidation.

The Fenton process (ferrous ions (Fe2+) and hydrogen peroxide (H2O2)) is one of the most studied techniques for MR degradation. In this system, Fe2+ catalyzes the decomposition of H2O2 to produce hydroxyl radicals, which then oxidize MR molecules.193 Although effective, the Fenton reaction is restricted to acidic pH conditions and suffers from the generation of iron-containing sludge, which complicates post-treatment handling.194 To overcome these limitations, the photo-Fenton process has been explored, where UV or visible light is used to accelerate the Fe2+/H2O2 reaction which enhances radical production and improves the dye degradation efficiency.195 During degradation process, the mechanism follows the eqn (11)–(15).

Fe2+ + H2O2 → Fe3+ + OH˙ + OH− 11
Fe3+ + OH− → Fe2+ + OH˙ 12
Fe2+ + OH˙ → Fe3+ + OH− 13
OH˙ + H2O2 → H2O + HOO˙ 14
HOO˙ + HOO˙ → H2O2 + O2 15

Fe2+ ion donates an electron to hydrogen peroxide to produce Fe3+ ions, hydroxide, and hydroxyl radical as given in eqn (11). The Fe3+ ion can gain an electron from hydroxide to form Fe2+ ions and hydroxyl radical and vice versa as in eqn (12) and (13). The hydroxyl radical reacts with hydrogen peroxide to form water and hydrogen peroxide radical as given in eqn (14). The hydrogen peroxide radical produces hydrogen peroxide and oxygen molecules in the last eqn (15).

Ozonation is another oxidative approach, where ozone molecules decompose in water to produce hydroxyl radicals.184 While ozonation can rapidly decolorize MR, its efficiency depends heavily on pH and ozone dosage, and incomplete mineralization often leaves behind toxic intermediates.196 Similarly, persulfate (S2O82−) activation has gained attention as it generates sulfate radicals (SO4˙−), which are strong oxidants with higher redox potential than hydroxyl radicals under certain conditions.189 Persulfate can be activated thermally, photochemically, or catalytically using transition metal nanoparticles which results in efficient oxidative cleavage of MR.

Nanoparticle-assisted oxidative degradation has also been extensively investigated to overcome the drawbacks of conventional AOPs.192 For example, transition metal oxides can act as heterogeneous catalysts for persulfate or H2O2 activation which provide controlled and reusable systems. Noble metal nanoparticles, when coupled with semiconductor oxides, have been shown to enhance ROS generation owing to their ability to facilitate electron transfer and reduce recombination of photogenerated charges.

A critical issue in oxidative degradation is the formation of intermediate by-products during partial breakdown of MR. While oxidative methods are capable of attacking the azo bond and aromatic rings, incomplete mineralization often leads to the accumulation of aromatic amines or low-molecular-weight carboxylic acids, which can still pose environmental risks. Therefore, combining oxidative degradation with other catalytic pathways like photocatalysis or reduction has been suggested to ensure both rapid decolorization and complete detoxification.

Oxidative degradation represents a powerful pathway for MR treatment owing to its ability to achieve mineralization rather than simple transformation. However, the need for external oxidants, control of operational conditions (pH, oxidant dosage, catalyst stability), and handling of potential by-products remain challenges. The integration of oxidative degradation with nanoparticle-based catalysts and hybrid processes appears to be a suitable route for achieving high-efficiency, eco-friendly, and scalable treatment of MR-contaminated wastewater.

7. Thermodynamic aspects

The catalytic reduction of MR at different temperatures are mostly studied with metal nanoparticles (with or without capping agents) and reductants like NaBH4. This catalytic reduction of MR is governed not only by reaction kinetics but also by important thermodynamic parameters that determine the feasibility, spontaneity, and energy requirements of the process. Thermodynamic studies provide valuable insight into the interaction between dye molecules and catalyst surfaces, the stability of reaction intermediates, and the overall driving force of the reduction reaction.

The activated Gibbs free energy change (ΔG*) (kJ mol−1) is one of the most important thermodynamic parameters for evaluating the spontaneity of catalytic reduction of MR. The value of ΔG depends upon the value of activated enthalpy change (ΔH*) (kJ mol−1) and activated entropy change (ΔS*) (J mol−1 K−1) as shown in eqn (16). The value of ΔG* must be negative for a spontaneous reduction process.197 During catalytic reduction, electrons are transferred from BH4− ions to the azo bond (–N Created by potrace 1.16, written by Peter Selinger 2001-2019 N–) of MR through the nanoparticle surface as discussed in mechanism. The overall decrease in free energy indicates that the products formed after azo bond cleavage are thermodynamically more stable than the parent dye molecule. In most reported studies, negative ΔG* values confirm that the catalytic reduction of MR is a spontaneous process under the investigated conditions. Additionally, more negative ΔG* value indicates stronger interactions between MR molecules and catalytic active sites which leads to enhanced catalytic reduction efficiency.198

ΔG* = ΔH* − TΔS* 16

The ΔH* describes the heat absorbed or released during the catalytic reduction process and it is calculated with the help of eqn (17). To find this value, a graph has been drawn in which ln(kapp/T) is taken along Y-axis and 1/T along X-axis. The slop of this graph is used to find ΔH*. The reduction of MR can be either exothermic or endothermic depending on the catalyst composition, reaction medium, and adsorption behavior. In many nanoparticle-catalyzed systems, negative ΔH* values are observed which indicate that the reduction process is exothermic. This suggests that the formation of reduced products and adsorption of reactants on catalyst surfaces release energy. Exothermic reactions are favorable because they require less external energy input.199 Nonetheless, excessively strong adsorption resulting from highly exothermic interactions can hinder desorption of products and reduce catalyst turnover efficiency.

The ΔS* shows the degree of disorder or randomness within the reaction system. Its value can be calculated by the intercept value which is obtained from ln(kapp/T) vs. 1/T graph using eqn (17). During MR reduction, changes in entropy are associated with adsorption of MR molecules onto catalyst surfaces, electron transfer processes, and formation of reaction products. Positive ΔS* value indicates increased randomness at the solid–liquid interface, which can result from structural rearrangements and the generation of smaller degradation products.200 On the other hand, negative ΔS* value suggests a more ordered system owing to strong adsorption of MR molecules on catalytic surfaces. The magnitude and sign of ΔS* provide information regarding the adsorption mechanism and molecular organization during reduction.

7. 17

Activation energy (Ea) is a primarily kinetic parameter, and it has significant thermodynamic implications. Eqn (18) (Arrhenius equation) is used to calculate the Ea values. A graph is drawn in which ln kapp is taken along Y-axis and 1/T along X-axis. The slope value of this graph is used to calculate Ea values. The reduction of MR by NaBH4 alone is thermodynamically favorable but kinetically slow because of a high activation energy barrier. Nanoparticles act as catalysts by lowering this Ea through the introduction of alternative reaction pathways. A lower Ea facilitates faster electron transfer from BH4− to MR and accelerates azo bond cleavage. Catalysts with lower activation energies exhibit superior catalytic performance and higher kapp values.201

7. 18

MR molecules must adsorb onto the nanoparticle surface before the electron transferring. The adsorption process itself follows thermodynamic principles and significantly influences reduction efficiency. The adsorption equilibrium constant (Keq) can be used to calculate thermodynamic parameters through the van't Hoff equation. Strong adsorption increases the local concentration of MR near active sites which facilitate electron transfer and hydrogenation. But excessively strong adsorption can block active sites and reduce catalyst regeneration. Hence, optimal adsorption strength is required to balance reactant adsorption and product desorption.

Temperature significantly affects the thermodynamic behavior of MR reduction. According to thermodynamic principles, increasing temperature can alter ΔG*, ΔH*, and ΔS* values. In endothermic systems, higher temperatures enhance reduction efficiency by providing additional energy for electron transfer and bond cleavage.64 While highly exothermic systems can exhibit reduced adsorption capacity at elevated temperatures owing to increased molecular mobility. So, determining the optimum reaction temperature is essential for maximizing catalytic performance while maintaining catalyst stability.

The reduction of MR involves cleavage of the azo bond (–N Created by potrace 1.16, written by Peter Selinger 2001-2019 N–), which is responsible for the color of dye and stability. Thermodynamically, the reduction process becomes favorable because the resulting aromatic amine products possess lower free energy than the azo-containing parent molecule. The adsorption of BH4− and MR on the nanoparticle surface lowers the energy barrier for electron transfer which makes bond dissociation energetically favorable. As a result, the catalyst generates a low-energy pathway that promotes spontaneous reduction and rapid decolorization.

Thermodynamic analysis of MR reduction faces several challenges. Most studies focus primarily on kinetic parameters, while detailed thermodynamic investigations are neglected. Additionally, the coexistence of adsorption, hydrogenation, electron transfer, and desorption processes makes it difficult to isolate individual thermodynamic contributions. Variations in nanoparticle size, pH, catalyst composition, and reaction medium further complicate direct comparison between studies. Advanced computational techniques like Density Functional Theory (DFT) and molecular simulations are increasingly being employed to better understand adsorption energies, reaction pathways, and electron transfer mechanisms at the atomic level.202

Future research should focus on integrating experimental thermodynamic studies with theoretical modeling to establish clear relationships between catalyst structure and reduction efficiency. The knowledge of surface free energy, adsorption energies, and electron-transfer thermodynamics will facilitate the rational design of highly efficient catalysts. Likewise, combining thermodynamic analysis with kinetic modeling can provide a comprehensive understanding of MR reduction mechanisms which enable the development of sustainable and scalable catalytic systems for wastewater treatment.

8. Recycling

The recycling and reusability of catalysts are critical parameters for evaluating the practical applicability, economic feasibility, and environmental sustainability of MR treatment technologies. Although many catalysts exhibit excellent degradation or reduction efficiencies during their first cycle, their long-term performance depends on their ability to maintain catalytic activity over multiple reaction cycles without significant structural deterioration, leaching, or deactivation. Thus, catalyst recycling studies have become an essential component of both photocatalytic degradation and catalytic reduction research. The equation which is used to calculate the efficiency of a catalyst during recycling is provided in eqn (19).

8. 19

In photocatalytic systems, catalyst recovery is performed after each degradation cycle through centrifugation, filtration, sedimentation, or magnetic separation. After the photocatalytic degradation of MR, the catalyst is separated from the treated solution, washed several times with distilled water and ethanol to remove adsorbed dye molecules and degradation intermediates, dried at moderate temperatures (60–100 °C), and then reused in subsequent photocatalytic experiments.64

The recycling mechanism involves several steps. During photocatalysis, MR molecules adsorb onto the catalyst surface and undergo oxidation by ˙OH, O2˙–, and photogenerated holes (h+). After complete degradation, residual intermediates can remain adsorbed on active sites which block light absorption and hence reduce the photocatalytic activity. Washing and regeneration help restore surface activity by removing these deposits.203 In some cases, mild thermal treatment is employed to completely eliminate organic residues and recover photocatalytic efficiency.

Photocatalysts show gradual activity loss after repeated cycles. Several factors contribute to this decline like metal ion leaching, loss of crystallinity, surface fouling, particle agglomeration, and photo-corrosion. For example, ZnO can undergo photo-corrosion under prolonged irradiation, while TiO2 can suffer from accumulation of degradation by-products on its surface. To resolve these issues, researchers have developed doped semiconductors, heterojunction photocatalysts, and supported photocatalysts that exhibit improved structural stability and recyclability.204,205

Magnetic photocatalysts (Fe3O4-based composites) show a significant advantage because they can be rapidly recovered using an external magnetic field without filtration or centrifugation. This approach minimizes catalyst loss and enhances operational efficiency. In many studies, magnetic photocatalysts retain more than 85–95% of their initial degradation efficiency after five to ten recycling cycles.206 These results demonstrate their potential for practical wastewater treatment applications.

The recycling of catalysts in catalytic reduction systems follows a similar strategy but involves different deactivation mechanisms. In a typical catalytic reduction process, nanoparticles facilitate electron transfer from NaBH4 to MR molecules which results in cleavage of the azo bond and formation of aromatic amines. After completion of catalytic reduction reaction, the catalyst is separated by centrifugation, filtration, or magnetic recovery, thoroughly washed to remove reaction products and residual borohydride, dried, and reused in subsequent reduction cycles.207

A major challenge during catalyst recycling is the adsorption of reduction products and intermediates onto active catalytic sites. These adsorbed species can block electron transfer pathways and reduce the accessibility of reactants to the catalyst surface. Moreover, repeated exposure to aqueous environments can induce nanoparticle aggregation, oxidation, or metal leaching which leads to a decrease in catalytic efficiency. Supported catalysts exhibit superior recyclability compared to unsupported nanoparticles.208 Carbon-based supports like carbon nanotubes, graphene oxide, and activated carbon prevent nanoparticle agglomeration and maintain high surface area during repeated use. Likewise, polymeric supporting materials like microgels, hydrogels, and chitosan stabilize nanoparticles through strong metal–support interactions which reduce catalyst loss and improve their durability. MOFs and mesoporous silica supporting materials also enhance catalyst stability by confining nanoparticles within porous structures.

Magnetically recoverable catalysts are advantageous in reduction systems as photocatalytic recycling. Fe3O4-supported metal nanoparticles can be rapidly separated from treated solutions using a magnetic field. It minimizes the catalyst loss and reduces the operational costs. Such systems maintain their initial reduction efficiency after multiple cycles which make them attractive for large-scale wastewater treatment.209

One of the primary challenges is nanoparticle leaching, where active metal species dissolve into the solution during repeated cycles. This not only reduces catalytic performance but also introduces potential secondary contamination. Strong metal-supporter interactions, core–shell structures, and surface coatings have been developed to minimize leaching. Another challenge is surface fouling, caused by accumulation of reaction intermediates and degradation products. Periodic regeneration through thermal treatment, chemical washing, or UV-assisted cleaning can restore catalyst activity. Particle aggregation also reduces active surface area and catalytic efficiency. Immobilization on supporting materials, incorporation into hydrogels, and fabrication of magnetic nanocomposites help prevent aggregation and improve long-term stability.

From a practical standpoint, catalyst recyclability is as important as catalytic efficiency itself. A catalyst that achieves greater MR removal in a single cycle but rapidly loses activity upon reuse can be less valuable than a slightly less active catalyst with excellent long-term stability. Future research should focus on developing multifunctional catalysts that combine high activity, resistance to fouling, easy recovery, and long-term structural stability. Magnetic nanocomposites, supported multi-metallic nanoparticles, and stimuli-responsive polymer-based catalysts represent promising directions for achieving sustainable and economically viable MR remediation technologies.

9. Factors influencing and enhancing the catalytic degradation/reduction of methyl red

The efficiency of MR degradation or reduction is not governed solely by the choice of catalyst but also by a variety of operational and physicochemical factors that directly affect reaction kinetics and mechanism. These parameters include catalyst characteristics (size, morphology, surface chemistry), reaction conditions (pH, temperature, concentration of dye and reducing agent), and external inputs like light intensity in photocatalytic systems as given in Table 2. A critical understanding of these factors is essential to optimize performance and design scalable systems for wastewater treatment.

Table 2. Catalytic reduction/degradation of MR by different catalysts under different conditions.

Catalysts Studied parameters Optimum rate of reaction (min−1) Optimum removal efficiency (%) Reduction/degradation References
Bi–ZnO Temperature, dose of catalyst, dye concentration, contact time, scavengers 3.46 × 10−3 95 Photocatalytic degradation 64
LaMnCeO3–TiO2 Temperature, pH, dye concentration, and contact time — 96 Photocatalytic degradation 221
Fe2+/H2O2 system (Fenton oxidation) pH, current density, dye concentration — 96 Oxidative degradation 222
Ti–Ru0.3Ti0.7O2 pH, concentration of NaCl, NaSO4, NaNO3, and current density — 90 Electrochemical oxidation degradation 223
Fe3O4@phosphine–imidazolium-AuCu pH 27 Catalytic reduction 207
Ag–P(CS-NVC-MAA) — 0.562 min−1 — Catalytic reduction 28
Ag–Mn–Ni–Zn pH — 98 Catalytic reduction 224

Catalyst size and morphology play one of the most decisive roles in MR degradation. Smaller nanoparticles expose a larger surface-to-volume ratio which offer more active sites for adsorption of MR molecules and reducing agents. Furthermore, anisotropic morphologies like nanorods, nanosheets, and nanostars expose high-energy crystallographic facets that accelerate electron transfer. For example, silver nanoplates210 or gold nanorods211 often outperform spherical nanoparticles owing to their enhanced surface reactivity and localized surface plasmon resonance (LSPR) effects, which increase local electron density and catalytic efficiency. However, extremely small particles can agglomerate which lead to reduced catalytic activity. Therefore, immobilization of supporting materials is necessary.

Surface functionalization and support significantly enhance catalytic efficiency by preventing aggregation, improving electron transport, and increasing adsorption capacity. Carbon-based supports like graphene oxide104 or activated carbon212 not only stabilize nanoparticles but also pre-concentrate MR molecules through π–π interactions and thus improve contact between the dye and catalytic sites. Similarly, polymeric supports like chitosan212 and hydrogels39 provide functional groups that attract negatively charged MR molecules, while also acting as reservoirs for reducing agents. Surface modification with functional groups (–NH2, –COOH, –OH) can also increase interaction strength with MR which enhance reaction kinetics.

pH of the reaction medium is another critical parameter influencing MR reduction. The charge state of MR molecules, as well as the surface charge of the catalyst, is highly pH-dependent. In acidic conditions, MR is predominantly in its protonated form, which improves electrostatic interactions with negatively charged catalyst surfaces.213 Conversely, in alkaline media, hydroxyl radicals are more efficiently generated in photocatalytic systems which accelerate oxidative degradation.188 Therefore, the optimal pH depends on the catalytic pathway: reduction tends to be faster in slightly acidic conditions, while photocatalytic oxidation benefits from alkaline conditions.39

Concentration of MR and reducing agent also affects the efficiency of degradation. At very high MR concentrations, active catalytic sites can become saturated after a certain level of concentration which leads to slower reaction rates owing to limited availability of electrons or reactive radicals.30,39,191 Conversely, at excessively high NaBH4 concentrations, side reactions like hydrogen gas evolution can reduce efficiency by diverting electrons away from MR reduction.29,214,215 An optimized ratio between dye molecules and reducing agent is therefore crucial for achieving maximum efficiency.

Light intensity and wavelength are key factors in photocatalytic degradation of MR. Semiconductors such as TiO2, ZnO, and g-C3N4 require sufficient photon energy to excite electrons across the band gap.216 Higher light intensity enhances electron–hole pair generation, but excessive intensity can also accelerate charge recombination or cause thermal effects that reduce efficiency.182 Band-gap engineering through doping or coupling with plasmonic metals allows catalysts to utilize visible light more effectively which enhances MR degradation under solar irradiation. It is critical for practical applications.

Temperature has a dual effect on MR reduction. On one hand, higher temperatures increase the reaction rate by providing more thermal energy to overcome activation barriers.30,39 On the other hand, excessive heating can destabilize catalysts, promote nanoparticle sintering, or cause desorption of dye molecules from the catalyst surface and hence reduce overall efficiency.128 Thus, maintaining an optimal temperature range is essential for balancing kinetic acceleration with catalyst stability.

Catalyst dosage and dispersion also influence degradation efficiency.217 Higher catalyst loading increases the number of active sites available for reaction, but beyond a certain threshold, particle aggregation and light scattering (in photocatalysis) reduce efficiency.218 Similarly, poor dispersion of nanoparticles in solutions leads to uneven reaction zones and incomplete degradation. The use of supports, surfactants, or stabilizing polymers can improve dispersion and optimize catalyst utilization.

Dissolved oxygen concentration plays a crucial role in oxidative and photocatalytic pathways. Oxygen molecules act as electron acceptors, forming reactive oxygen species (ROS) such as superoxide radicals (O2˙−), which drive MR mineralization.219,220 Low oxygen availability limits ROS production, while high oxygen levels enhance degradation but can also compete with dye molecules for electrons. Controlling aeration or oxygen supply is therefore important for balancing reduction and oxidation pathways.

The degradation and reduction of MR are highly sensitive to multiple interacting factors. Optimizing catalyst design (size, shape, support, surface chemistry) alongside reaction conditions (pH, light intensity, reactant concentration, and temperature) is essential for achieving efficient, sustainable, and scalable dye removal. A critical future direction lies in developing adaptive catalytic systems that can self-adjust to fluctuating conditions in real wastewater which control robust performance across diverse environments.

10. Challenges and future perspectives

The application of inorganic nanoparticles for the reduction and degradation of MR has attracted significant attention owing to their high catalytic efficiency, rapid reaction kinetics, and ability to remove dye pollutants under mild operating conditions. Several scientific and technological challenges continue to limit their practical implementation in large-scale wastewater treatment systems. One of the most critical issues is nanoparticle aggregation, which occurs because of the high surface energy of nanoscale materials. Aggregation reduces the available active surface area, decreases the number of accessible catalytic sites, and ultimately lowers catalytic efficiency. Although the incorporation of nanoparticles into supporting materials like polymers, silica, activated carbon, graphene oxide, and MOFs has improved dispersion and stability which maintain long-term structural integrity under realistic treatment conditions remains a major challenge.

Another important concern is catalyst stability and metal leaching during repeated catalytic cycles. Many metallic nanoparticles are susceptible to oxidation, corrosion, or dissolution in aqueous environments under acidic or alkaline conditions. The release of metal ions not only decreases catalytic activity but can also generate secondary contamination which generates additional environmental concerns. Additionally, the long-term environmental fate and toxicity of nanoparticles remain insufficiently understood. While numerous studies have focused on catalytic performance, comparatively few have investigated the ecological impacts of nanoparticle release into natural ecosystems. So, comprehensive assessments of bioaccumulation, nanoparticle toxicity, and environmental persistence are necessary before large-scale deployment can be considered environmentally safe.

A further limitation is associated with the incomplete degradation of MR. In catalytic reduction systems, the azo bond is cleaved efficiently which results in rapid decolorization. However, the generated aromatic amine intermediates can still possess toxicity and environmental persistence. Consequently, color removal alone should not be considered evidence of complete detoxification. Future treatment strategies should emphasize complete mineralization through the integration of reduction, biological degradation, advanced oxidation, photocatalysis, or electrochemical processes. Such combined approaches can ensure the conversion of toxic intermediates into harmless end products and hence enhance the environmental sustainability of treatment technologies.

The complexity of real industrial wastewater also presents significant challenges. Most experimental investigations are conducted using synthetic dye solutions under controlled laboratory conditions. In contrast, actual wastewater contains a wide range of interfering substances like suspended solids, heavy metals, surfactants, salts, and various organic pollutants. These components can compete for active sites, alter catalyst surface properties, inhibit electron transfer, and reduce the overall degradation efficiency. So, catalytic systems that perform exceptionally well in laboratory studies can exhibit significantly lower efficiencies when applied to real wastewater streams. Therefore, greater emphasis should be placed on evaluating catalyst performance under realistic environmental conditions.

Catalyst recovery and recyclability represent additional obstacles to practical implementation. Although many catalysts demonstrate excellent activity during initial cycles, their performance declines after repeated use because of fouling, structural degradation, agglomeration, and active-site blockage. The development of magnetic nanocomposites, immobilized catalysts, and supported nanoparticle systems has improved recovery efficiency and catalyst longevity. However, further advances are needed to ensure stable long-term operation in continuous treatment systems. Economic considerations also remain a major barrier to commercialization. Many advanced catalysts require costly precursors, noble metals, sophisticated synthesis procedures, and energy-intensive processing conditions. Therefore, the development of low-cost, scalable, and environmentally benign synthesis methods remains a priority for future research.

The future outlook for inorganic nanoparticle-based MR remediation remains highly promising. Advances in nanotechnology and materials engineering are enabling the development of increasingly sophisticated catalysts with enhanced activity, stability, selectivity, and recyclability. Future research is expected to focus on multifunctional nanomaterials capable of simultaneously performing reduction, photocatalysis, adsorption, and oxidation within a single platform. Multi-metallic nanoparticles and hybrid nanocomposites are attractive because synergistic interactions among different components can improve charge separation, optimize adsorption properties, and enhance catalytic efficiency. In addition, green synthesis approaches utilizing plant extracts, microorganisms, and biodegradable polymers are expected to play an increasingly important role in reducing the environmental footprint of catalyst production.

The integration of artificial intelligence, computational modeling, and machine learning into catalyst design can further accelerate the discovery of highly efficient materials by predicting optimal compositions and structures prior to experimental synthesis. Simultaneously, greater attention is likely to be devoted to solar-driven catalytic systems that maximize visible-light utilization and minimize external energy requirements. Future investigations should also prioritize pilot-scale studies, long-term durability assessments, continuous-flow reactor systems, and techno-economic analyses to bridge the gap between laboratory research and industrial implementation. Through the combined advancement of catalyst design, sustainable synthesis strategies, and process engineering, inorganic nanoparticles are expected to play a central role in the development of next-generation technologies for the efficient and environmentally responsible remediation of MR-contaminated wastewater.

11. Conclusions

MR is one of the most widely used azo dyes in different industries, and its continuous discharge into aquatic environments poses serious environmental and health concerns due to its persistence, toxicity, and resistance to natural degradation processes. Conventional treatment methods face different limitations like incomplete dye removal, high operational costs, secondary pollution, and poor efficiency in treating complex wastewater streams. Therefore, nanoparticle-based catalytic technologies have emerged as highly promising alternatives for the effective remediation of MR-contaminated water.

This review critically highlights the significant progress achieved in both catalytic reduction and photocatalytic degradation of MR using inorganic nanoparticles. In catalytic reduction systems, nanoparticles act as efficient electron mediators that facilitate electron transfer from reductants like NaBH4 to the azo bond of MR which result in rapid decolorization and cleavage of the dye molecule. Mono-metallic, bi-metallic, tri-metallic, and tetra-metallic nanoparticles have demonstrated remarkable catalytic activities, with multi-metallic systems exhibiting superior performance due to synergistic electronic and structural effects. Additionally, the incorporation of nanoparticles into inorganic, carbon-based, polymeric, and MOF supporting materials has significantly improved catalyst stability, dispersion, and recyclability while minimizing aggregation and metal leaching.

Photocatalytic degradation provides an additional advantage by enabling the generation of ROS which can oxidize MR and its intermediate products into less harmful compounds or achieve complete mineralization under appropriate conditions. The development of advanced photocatalysts through dopant, heterojunction construction, plasmonic modification, and band-gap engineering has enhanced visible-light utilization, charge separation efficiency, and photocatalytic activity. These advances have expanded the potential of photocatalytic systems for sustainable and solar-driven wastewater treatment applications.

The review also demonstrates that the efficiency of both catalytic reduction and photocatalytic degradation is strongly influenced by factors such as dissolved oxygen, catalyst dosage, pH, supporter materials, surface chemistry, morphology, particle size, catalyst composition, temperature, reactant concentration, and light intensity. Careful optimization of these parameters is essential for maximizing degradation efficiency and ensuring long-term catalyst stability. Furthermore, catalyst recyclability remains a crucial consideration for practical applications and supported as well as magnetically recoverable catalysts have shown considerable promise in maintaining high catalytic performance over multiple operational cycles.

Several challenges are present like catalyst aggregation, incomplete mineralization, photo-corrosion, nanoparticle leaching, limited visible-light utilization, toxicity of intermediate products, and the discrepancy between laboratory-scale performance and real wastewater treatment conditions. Addressing these challenges will require the development of multifunctional catalysts capable of integrating adsorption, oxidation, reduction, and photocatalytic processes within a single platform. Future research should also focus on green synthesis approaches, environmentally benign catalyst design, real wastewater applications, pilot-scale studies, and comprehensive environmental risk assessments.

Inorganic nanoparticles have demonstrated exceptional potential as catalysts for both the reduction and photocatalytic degradation of MR. The combination of advanced nanomaterial engineering, enhanced catalyst recovery systems, sustainable synthesis strategies, and integrated treatment technologies is expected to significantly improve the efficiency and practicality of MR remediation. Continued advancements in this field will contribute substantially to the development of cost-effective, environmentally friendly, and scalable wastewater treatment technologies capable of addressing the growing global challenge of dye pollution.

Conflicts of interest

There are no conflicts to declare.

Abbreviations

MR

Methyl red

IMNPs

Inorganic metal nanoparticles (IMNPs)

NPs

Nanoparticles

ROS

Reactive oxygen species (ROS)

CB

Conduction band

VB

Valence band

MOF

Metal–organic framework

AOPs

Advanced oxidation processes

PDA

Polydopamine

E g

Energy band gap

AN

Alginate

PVA

Polyvinyl alcohol

QDs

Quantum dots

ETB

Erythrosine B

AOPs

Advanced oxidation processes

APTMS

3-Aminopropyltrimethoxysilane

SBA-15

Santa barbara amorphous-15

MPS

Mesoporous silica

MOFs

Metal–organic frameworks

CNT

Carbon nanotube

CECS

Carboxyethyl chitosan

CS

Chitosan

AC

Activated carbon

IPA

Isopropylalcohol

PZC

Point of zero charge

SPR

Surface plasmon resonance

TCN

Tubular carbon nitride

MCC

Modified coconut coir

RGO

Reduced graphene oxide

GO

Graphene oxide

Biography

Muhammad Arif.

Muhammad Arif

Dr Muhammad Arif has been a Professor (Assistant) in Chemistry at the Department of Chemistry, University of Management and Technology, Lahore since 2022. He worked as a lecturer in Chemistry at the Department of Chemistry, School of Science, University of Management and Technology, Lahore from 2017 to 2022. He has done a PhD in Chemistry at University of The Punjab, Lahore, Pakistan. He obtained his M.Phil and M.Sc degrees in Organic Chemistry from Quaid-i-Azam University Islamabad, Islamabad and Institute of Chemistry, University of the Punjab, Lahore, Pakistan respectively. His research areas are synthesis, characterization and applications of metal nanoparticles fabricated in microgels, ligands, and semiconductors in different fields.

Data availability

No primary research results, software or code have been included and no new data were generated or analysed as part of this review.

References

  1. Tang Z. Xu C. Shen C. Meng X. Xu H. Li F. J. Hazard. Mater. 2025;488:137465. doi: 10.1016/j.jhazmat.2025.137465. [DOI] [PubMed] [Google Scholar]
  2. Periyasamy A. P. Water, Air, Soil Pollut. 2025;236(9):1–39. doi: 10.1007/s11270-025-08204-7. [DOI] [Google Scholar]
  3. Sudhakaran G. Karthikeyan R. Madesh S. Dhaareshwar V. N. Pachaiappan R. Rajagopal R. Soundharrajan I. Karthick Raja Namasivayam S. Arockiaraj J. Toxicology. 2025;511:154065. doi: 10.1016/j.tox.2025.154065. [DOI] [PubMed] [Google Scholar]
  4. Chennoufi I. H. Zanane C. Ameslek M. El Louali M. Zahir H. Latrache H. Fibers Polym. 2025;26:1237–1249. doi: 10.1007/s12221-025-00878-4. [DOI] [Google Scholar]
  5. Yang J. Zhao J. Xie R. Wu C. Huang F. Cellulose. 2025;32:1917–1936. doi: 10.1007/s10570-024-06359-w. [DOI] [Google Scholar]
  6. Rafique Khattak S. Badshah A. Asghar B. Sun W. Ullah R. Iqbal Z. Nishan U. Khan M. Soylak M. Anal. Lett. 2025;58:1506–1518. doi: 10.1080/00032719.2024.2377370. [DOI] [Google Scholar]
  7. Ho D. Masura J. Colorants. 2025;4:20. doi: 10.3390/colorants4020020. [DOI] [Google Scholar]
  8. Muruganandham M. Tamilselvi Y. Sivasubramanian K. Velmurugan P. Oleyan Al-Otibi F. Sivakumar S. Front. Chem. 2025;13:1474160. doi: 10.3389/fchem.2025.1474160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Al Fahad M. A. Ahamed R. Ahmed T. Jahan N. Mia R. Toki G. F. I. Mahmud S. T. Niloy K. K. Renew. Dyes Pigm. 2024:165–175. [Google Scholar]
  10. Lee W. Sajadieh S. M. M. Choi H. K. Park J. Do Noh S. Int. J. Precis. Eng. Manuf. Green Technol. 2024;11:743–763. doi: 10.1007/s40684-024-00627-7. [DOI] [Google Scholar]
  11. Assayehegn E. Gidey A. T. Gebreslassie G. Gebremariam G. Solaiappan A. Chebude Y. Alemayehu E. Mater. Today Commun. 2023;37:107447. doi: 10.1016/j.mtcomm.2023.107447. [DOI] [Google Scholar]
  12. Assayehegn E. Solaiappan A. Gidey A. T. Gebreegziabher G. G. Gebretsadik T. T. Chebude Y. Alemayehu E. Glob. Chall. 2024;8(10):2400174. doi: 10.1002/gch2.202400174. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Omar A. Z. Mahmoud M. N. Hamed E. A. El-Sadany S. K. Alharbi H. Y. Aljohani M. S. El-Atawy M. A. J. Mol. Liq. 2025;426:127456. doi: 10.1016/j.molliq.2025.127456. [DOI] [Google Scholar]
  14. Meganathan M. K. Arunachalam R. Ramalingam S. ACS Sustainable Chem. Eng. 2025;13:10285–10291. doi: 10.1021/acssuschemeng.5c02228. [DOI] [Google Scholar]
  15. Hu H. Wang J. Sun H. Chen Y. Chen J. Color. Technol. 2025;141:344–355. [Google Scholar]
  16. Basdeki E. Vasilaki S. E. Sensi M. Flemetakis E. Biscarini F. Power D. Tsironi T. Int. J. Food Sci. 2025;2025:3576183. doi: 10.1155/ijfo/3576183. [DOI] [Google Scholar]
  17. Hartzell E. J. Gonzalez Obeso C. Hasturk O. Scheel R. A. Wan L. Moser F. Smith T. Kaplan D. Adv. Funct. Mater. 2025;35:2407882. doi: 10.1002/adfm.202407882. [DOI] [Google Scholar]
  18. Shao Z. Sun H. Wong E. H. H. Polym. Chem. 2025;16:1373–1382. doi: 10.1039/D5PY00068H. [DOI] [Google Scholar]
  19. Xiang X. Zhou J. Lin S. Zhang N. Abulipizi G. Chen G. Li Z. Sci. Total Environ. 2022;840:156681. doi: 10.1016/j.scitotenv.2022.156681. [DOI] [PubMed] [Google Scholar]
  20. Urucu O. A. Garosi B. Musah R. A. ACS Omega. 2025;10:1943–1953. doi: 10.1021/acsomega.4c07468. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Bopape D. A. Ntsendwana B. Mabasa F. D. Heliyon. 2024;10(20):e39316. doi: 10.1016/j.heliyon.2024.e39316. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Tokalı F. S. Taslimi P. Taskin-Tok T. Karakuş A. Sadeghian N. Gulçin İ. J. Biochem. Mol. Toxicol. 2024;38:e23521. doi: 10.1002/jbt.23521. [DOI] [PubMed] [Google Scholar]
  23. Urucu O. A. Garosi B. Musah R. A. ACS Omega. 2025;10:1943–1953. doi: 10.1021/acsomega.4c07468. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Ihaddaden S. Aberkane D. Boukerroui A. Robert D. J. Water Proc. Eng. 2022;49:102952. doi: 10.1016/j.jwpe.2022.102952. [DOI] [Google Scholar]
  25. Kumar P. Ramasamy P. Jagadeesan M. J. Environ. Chem. Eng. 2025;13:118150. doi: 10.1016/j.jece.2025.118150. [DOI] [Google Scholar]
  26. Behera U. S. Poddar S. Byun H. S. J. Chem. Technol. Biotechnol. 2024;99:1212–1224. doi: 10.1002/jctb.7626. [DOI] [Google Scholar]
  27. Al-Essa K. Al-Essa E. M. Qarqaz A. Al-Issa S. Alshahateet S. F. Al-Fawares O. Water. 2025;17:158. doi: 10.3390/w17020158. [DOI] [Google Scholar]
  28. Arif M. Raza H. Ben Moussa S. Alzahrani A. Y. A. Akhter T. Int. J. Biol. Macromol. 2024;282:136906. doi: 10.1016/j.ijbiomac.2024.136906. [DOI] [PubMed] [Google Scholar]
  29. Arif M. J. Environ. Chem. Eng. 2023;11:109270. doi: 10.1016/j.jece.2023.109270. [DOI] [Google Scholar]
  30. Arif M. Shahid M. Irfan A. Wang X. Noor H. Farooqi Z. H. Begum R. Inorg. Chem. Commun. 2022;144:109870. doi: 10.1016/j.inoche.2022.109870. [DOI] [Google Scholar]
  31. Şahin M. Arslan Y. Tomul F. Yıldırım B. Genç H. React. Kinet., Mech. Catal. 2022;135:3303–3315. doi: 10.1007/s11144-022-02299-3. [DOI] [Google Scholar]
  32. Meydan I. Aygun A. Tiri R. N. E. Gur T. Kocak Y. Seckin H. Sen F. Environ. Sci. Adv. 2024;3:28–35. [Google Scholar]
  33. Selvarani J. F. L. Pushpavalli K. S. Kala S. M. J. Prakash K. S. J. Organomet. Chem. 2025;1036:123706. doi: 10.1016/j.jorganchem.2025.123706. [DOI] [Google Scholar]
  34. Sood A. Srishti Kaur N. Sharma B. Kumar R. Bhasin K. K. Dhau J. S. Chaudhary G. R. J. Cleaner Prod. 2025;508:145495. doi: 10.1016/j.jclepro.2025.145495. [DOI] [Google Scholar]
  35. Bibi I. Majid F. Raza Q. Kamal S. Jilani K. Nouren S. Fayyaz S. Alwadai N. Ayyar M. Patil R. Iqbal M. Semiconductors. 2025;59:391–403. doi: 10.1134/S1063782624602905. [DOI] [Google Scholar]
  36. Shivani Bhat R. S. Sajankila S. P. Bindu A. G. Appl. Phys. A: Mater. Sci. Process. 2025;131:649. doi: 10.1007/s00339-025-08775-6. [DOI] [Google Scholar]
  37. Inam H. Durrani A. I. Huma R. Hussain F. Chem. Pap. 2025;79:5921–5940. doi: 10.1007/s11696-025-04163-9. [DOI] [Google Scholar]
  38. Dev S. S. Santhosh C. James G. Indian J. Agric. Res. 2025;59:993. [Google Scholar]
  39. Arif M. RSC Adv. 2023;13:3008–3019. doi: 10.1039/D2RA07932A. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Ullah I. Tariq M. Abdullah A. Z. Muhammad M. Khan J. Rahim A. Int. J. Environ. Res. 2024;18:1–16. doi: 10.1007/s41742-024-00653-y. [DOI] [Google Scholar]
  41. Yang J. M. Liu B. W. Zhang W. Langmuir. 2024;40:6962–6970. doi: 10.1021/acs.langmuir.3c04012. [DOI] [PubMed] [Google Scholar]
  42. Birdeanu M. Fratilescu I. Epuran C. Mocanu L. Ianasi C. Lascu A. Fagadar-Cosma E. Int. J. Mol. Sci. 2023;24:8920. doi: 10.3390/ijms24108920. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Ahmed E. M. Feteha A. Kamal R. S. Behalo M. S. Abdel-Raouf M. E. Environ. Sci. Pollut. Res. 2024;31:49626–49645. doi: 10.1007/s11356-024-34347-x. [DOI] [PubMed] [Google Scholar]
  44. Nguyen N. P. T. Nguyen N. T. T. Nguyen T. T. T. Nguyen D. T. C. Arabian J. Sci. Eng. 2025;50:20649–20663. doi: 10.1007/s13369-025-10283-x. [DOI] [Google Scholar]
  45. Arif M. J. Environ. Manage. 2025;395:127697. doi: 10.1016/j.jenvman.2025.127697. [DOI] [PubMed] [Google Scholar]
  46. Arif M. J. Alloys Compd. 2025;1046:184820. doi: 10.1016/j.jallcom.2025.184820. [DOI] [Google Scholar]
  47. Naz M. Rafiq A. Ikram M. Haider A. Ahmad S. O. A. Haider J. Naz S. J. Mater. Sci. 2021;56(28):15572–15608. doi: 10.1007/s10853-021-06279-1. [DOI] [Google Scholar]
  48. Bal G. Thakur A. Mater. Today: Proc. 2022;50:1575–1579. [Google Scholar]
  49. Arif M. J. Mol. Liq. 2024;403:124869. doi: 10.1016/j.molliq.2024.124869. [DOI] [Google Scholar]
  50. Arif M. J. Mol. Liq. 2023;375:121346. doi: 10.1016/j.molliq.2023.121346. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Naseem K. Abrar E. Khalid A. Ismail M. A. Inorg. Chem. Commun. 2024;163:112367. doi: 10.1016/j.inoche.2024.112367. [DOI] [Google Scholar]
  52. Kumar A. Kapoor A. Pal D. B. Asia-Pac. J. Chem. Eng. 2025;21:e70175. doi: 10.1002/apj.70175. [DOI] [Google Scholar]
  53. Arif M. RSC Adv. 2025;15:27668–27684. doi: 10.1039/D5RA04059K. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Al-Asadi S. T. Mussa Z. H. Al-Qaim F. F. Kamyab H. Al-Saedi H. F. S. Deyab I. F. Kadhim N. J. Carbon Trends. 2025;20:100507. doi: 10.1016/j.cartre.2025.100507. [DOI] [Google Scholar]
  55. Khan A. Nayarisseri A. Singh S. K. Sci. Rep. 2025;15:1–23. doi: 10.1038/s41598-025-95359-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Fatehi F. Khalili Sadrabad E. Feilizadeh M. Derakhshan Z. Heidari Kochaki S. Hekmatimoghaddam S. Jebali A. Mohajeri F. A. Int. J. Environ. Health Res. 2025;35:1204–1212. doi: 10.1080/09603123.2024.2383427. [DOI] [PubMed] [Google Scholar]
  57. Arif M. Chem. Data Collect. 2023;48:101104. doi: 10.1016/j.cdc.2023.101104. [DOI] [Google Scholar]
  58. Arif M. J. Indian Chem. Soc. 2023;100:100931. doi: 10.1016/j.jics.2023.100931. [DOI] [Google Scholar]
  59. Nowak D. Balcerak-Woźniak A. Kabatc-Borcz J. J. Mol. Liq. 2025;422:126876. doi: 10.1016/j.molliq.2025.126876. [DOI] [Google Scholar]
  60. Sumathi H. P. Prameela H. C. Bindushree T. N. Rajendraprasad N. Chem. Afr. 2025;8:3097–3107. doi: 10.1007/s42250-025-01315-y. [DOI] [Google Scholar]
  61. Yetgin S. Ağırsaygın M. Yazgan İ. Processes. 2025;13:1105. doi: 10.3390/pr13041105. [DOI] [Google Scholar]
  62. Singh G. Diskit T. Singh A. Dege N. Ozturk S. Rana S. Singh J. Dalal A. Devi S. Spectrochim. Acta, Part A. 2025;330:125737. doi: 10.1016/j.saa.2025.125737. [DOI] [PubMed] [Google Scholar]
  63. Sma-Air S. Ritchie R. J. Int. Biodeterior. Biodegrad. 2025;196:105915. doi: 10.1016/j.ibiod.2024.105915. [DOI] [Google Scholar]
  64. Alamzeb M. Zulfiqar N. U. A. Akhtar M. F. Riaz I. Ameen F. Asghar A. Setzer W. N. J. Fluoresc. 2025;36(1):61–83. doi: 10.1007/s10895-025-04533-2. [DOI] [PubMed] [Google Scholar]
  65. Heydari S. Mohadesi M. Environ. Prog. Sustainable Energy. 2025;45:e70213. doi: 10.1002/ep.70213. [DOI] [Google Scholar]
  66. Goswami Y. C. Kaundal J. B. Begzaad S. Tiwari R. K. J. Iran. Chem. Soc. 2023;20(7):1681–1697. doi: 10.1007/s13738-023-02789-8. [DOI] [Google Scholar]
  67. Shafiq F. Yu S. Pan Y. Qiao W. Coatings. 2024;14:921. doi: 10.3390/coatings14080921. [DOI] [Google Scholar]
  68. sh El-sonbaty S. Rashad M. Abu El-Fadl A. A. Abu-Sehly A. A. Mohammed M. M. J. Mol. Liq. 2025;422:126900. doi: 10.1016/j.molliq.2025.126900. [DOI] [Google Scholar]
  69. Mbuyazi T. B. Ajibade P. A. Int. J. Mol. Sci. 2024;25:7876. doi: 10.3390/ijms25147876. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Hussain S. Bibi I. Iqbal M. Majid F. Kamal S. Taj B. Fatima G. Kokab M. Nazir A. Alwadai N. Polyhedron. 2025;281:117733. doi: 10.1016/j.poly.2025.117733. [DOI] [Google Scholar]
  71. Gul T. Khan I. Ahmad B. Ahmad S. Alsaiari A. A. Almehmadi M. Abdulaziz O. Alsharif A. Khan I. Saeed K. Heliyon. 2023;9(6):e16738. doi: 10.1016/j.heliyon.2023.e16738. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Padmavathy N. Vinuth M. Naik M. M. Yashwanth H. J. Hemakumar K. H. Chem. Pap. 2026;2026:1–14. [Google Scholar]
  73. Shivanna S. Purushotham D. Kodandaram A. Nagabhushana C. M. Mavinakere Ramesh A. Chem. Phys. Impact. 2023;6:100241. doi: 10.1016/j.chphi.2023.100241. [DOI] [Google Scholar]
  74. Alharbi A. A. Aldaghri O. A El-Badry B. Ibnaouf K. H. Alfadhl F. Albadri A. Ahmed A. H. Modwi A. Opt. Mater. 2024;152:115443. doi: 10.1016/j.optmat.2024.115443. [DOI] [Google Scholar]
  75. Anjum F. Shaban M. Ismail M. Gul S. Bakhsh E. M. Khan M. A. Sharafat U. Khan S. B. Khan M. I. ACS Omega. 2023;8:17667–17681. doi: 10.1021/acsomega.3c00129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Afaq M. Sajid A. Manzoor Q. Imtiaz F. Sajid A. Javed R. Ahmad A. Alwadai N. Mnif W. Iqbal M. Mater. Sci. Eng., B. 2025;312:117847. doi: 10.1016/j.mseb.2024.117847. [DOI] [Google Scholar]
  77. Jahnavi H. K. Rajendra Prasad S. J. Alloys Compd. Commun. 2026;10:100174. [Google Scholar]
  78. Robles R. V. Q. Nestor A. R. V. Leal M. A. C. Estrella F. J. O. Castillo A. C. Morales P. A. L. Inorg. Chem. Commun. 2026;188:116572. doi: 10.1016/j.inoche.2026.116572. [DOI] [Google Scholar]
  79. Boulika H. Nabih M. H. Chiki Z. Boutouil M. Kandri N. I. Zerouale A. Results Chem. 2025;18:102852. doi: 10.1016/j.rechem.2025.102852. [DOI] [Google Scholar]
  80. Gholinejad M. Mohammadi S. Nayeri S. Sansano J. M. Inorg. Chem. Commun. 2025;177:114376. doi: 10.1016/j.inoche.2025.114376. [DOI] [Google Scholar]
  81. Gholinejad M. Bashirimousavi S. Sansano J. M. Sci. Rep. 2024;14:1–16. doi: 10.1038/s41598-024-56559-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Trieu Q. A. Ai Ung Q. N. Thai P. N. Mai T. M. Van Nguyen D. RSC Adv. 2025;15:13353–13363. doi: 10.1039/D5RA02503F. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Lee S. Ahn E. Y. Wang T. I. Park Y. Artif. Cells, Nanomed., Biotechnol. 2025;53:399–419. doi: 10.1080/21691401.2025.2542847. [DOI] [PubMed] [Google Scholar]
  84. Baran T. Karaoğlu K. Nasrollahzadeh M. Environ. Res. 2023;220:115153. doi: 10.1016/j.envres.2022.115153. [DOI] [PubMed] [Google Scholar]
  85. Nejo A. O. Adetona A. J. Lawal A. Lafia J. Sci. Ind. Res. 2024:54–60. [Google Scholar]
  86. Kaboudin B. Burunli B. Nazerian M. Zhang T. Gu Y. J. Organomet. Chem. 2025;1025:123477. doi: 10.1016/j.jorganchem.2024.123477. [DOI] [Google Scholar]
  87. Paz Y. Antoniou M. G. Druciarek J. Kutyła D. Pach A. Kula A. Luty-Błocho M. Catalysts. 2025;15:133. doi: 10.3390/catal15020133. [DOI] [Google Scholar]
  88. Zahran M. Gamal S. Zahran M. A. H. Azzem M. A. Microchem. J. 2025;213:113627. doi: 10.1016/j.microc.2025.113627. [DOI] [Google Scholar]
  89. Sandhya K. Reddy G. B. Ayodhya D. Noorjahan M. Mangatayaru K. G. Results Chem. 2023;5:100969. doi: 10.1016/j.rechem.2023.100969. [DOI] [Google Scholar]
  90. Lin C. C. Huang R. C. Wu K. Y. Powder Technol. 2025;465:121301. doi: 10.1016/j.powtec.2025.121301. [DOI] [Google Scholar]
  91. Ike J. I. Babayemi A. K. Egbosiuba T. C. Jin C. G. Mustapha S. Yusuff A. S. Yadav V. K. Igwegbe C. A. ACS Appl. Eng. Mater. 2024;2:1031–1046. doi: 10.1021/acsaenm.4c00065. [DOI] [Google Scholar]
  92. Alraae A. Moussadik A. Benzaouak A. El Hazzat M. Kacimi M. Dahhou M. Sifou A. El Hamidi A. Colloids Surf., A. 2025;718:136885. doi: 10.1016/j.colsurfa.2025.136885. [DOI] [Google Scholar]
  93. Ecer Ü. Zengin A. Şahan T. J. Energy Inst. 2025;119:101974. doi: 10.1016/j.joei.2025.101974. [DOI] [Google Scholar]
  94. Rajapantulu A. Bandyopadhyaya R. Langmuir. 2025;41:8049–8059. doi: 10.1021/acs.langmuir.4c04174. [DOI] [PubMed] [Google Scholar]
  95. Khan A. Raza Z. A. Bhatti H. N. Sarwar T. Int. J. Biol. Macromol. 2024;261:129881. doi: 10.1016/j.ijbiomac.2024.129881. [DOI] [PubMed] [Google Scholar]
  96. Fukui Y. Baba E. Fujimoto K. RSC Adv. 2025;15:1115–1124. doi: 10.1039/D4RA07142E. [DOI] [PMC free article] [PubMed] [Google Scholar]
  97. Arif M. Tahir F. Hussain T. Alrokayan S. Akhter T. RSC Adv. 2025;15:8580–8593. doi: 10.1039/D5RA00713E. [DOI] [PMC free article] [PubMed] [Google Scholar]
  98. Susan Punnoose M. Korah B. K. Mathew B. J. Water Chem. Technol. 2025;47:144–158. doi: 10.3103/S1063455X25020080. [DOI] [Google Scholar]
  99. Banu R. Gangapuram B. Ayodhya D. Dadigala R. Veerabhadram G. Kotu G. M. J. Fluoresc. 2023;33:209–221. doi: 10.1007/s10895-022-03073-3. [DOI] [PubMed] [Google Scholar]
  100. Pegu B. Konwer S. Graphene 2D Mater. 2023;8:121–133. doi: 10.1007/s41127-023-00063-5. [DOI] [Google Scholar]
  101. Abdussalam-Mohammed W. Edbey K. Farhat H. E. Shah P. Shamsi S. S. Bhattarai A. Inorg. Chem. Commun. 2025;173:113893. doi: 10.1016/j.inoche.2025.113893. [DOI] [Google Scholar]
  102. Saba M. Farooq S. Alessa A. H. Bektas K. I. Belduz A. O. Khan A. Z. Shah A. A. Badshah M. Khan S. BMC Biotechnol. 2025;25:1–15. doi: 10.1186/s12896-025-00959-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. Shafiq F. Yu S. Pan Y. Qiao W. Coatings. 2024;14:921. doi: 10.3390/coatings14080921. [DOI] [Google Scholar]
  104. Al-ogeily H. J. A. Shabanian S. R. Dashtpeyma G. Water, Air, Soil Pollut. 2025;236:1–20. doi: 10.1007/s11270-025-07836-z. [DOI] [Google Scholar]
  105. Bagherzadeh M. Dastjerdi M. H. C. Mokhtari J. Abadian-Naeini F. Mohsennia M. Cleaner Chem. Eng. 2025;11:100152. doi: 10.1016/j.clce.2025.100152. [DOI] [Google Scholar]
  106. Zhang Y. Zhang X. Chen C. Wang J. Wei F. Liu H. Du F. Jiang L. Zhu W. Tan X. Su R. Yan J. Anal. Chem. 2025;97(30):16491–16505. doi: 10.1021/acs.analchem.5c02529. [DOI] [PubMed] [Google Scholar]
  107. Idris D. S. Roy A. Malik A. Khan A. A. Sharma K. Roy A. J. Inorg. Organomet. Polym. Mater. 2024;35:594–606. doi: 10.1007/s10904-024-03316-9. [DOI] [Google Scholar]
  108. Saif A. Ali S. Jamil S. Kamal T. Latif M. J. Khan S. R. Arshad H. Mariam U. Liaqat S. J. Inorg. Organomet. Polym. Mater. 2025;35:3344–3365. doi: 10.1007/s10904-024-03460-2. [DOI] [Google Scholar]
  109. Michael A. Singh A. Roy A. Kaur K. Kumar A. Rustagi S. Verma D. Raj S. Lett. Appl. NanoBioScience. 2025;14:87. [Google Scholar]
  110. Gholinejad M. Saidiansar M. A. Eskandari M. Sansano J. M. Polyhedron. 2024;259:117059. doi: 10.1016/j.poly.2024.117059. [DOI] [Google Scholar]
  111. Singh D. Gupta D. Tiwari A. Naik J. Quraishi F. Singh R. P. Singh S. K. Singh A. K. Discover Appl. Sci. 2025;7:1–16. [Google Scholar]
  112. Güney B. C. Dikyar A. Şahin M. Arslan Y. React. Kinet., Mech. Catal. 2025:1–21. [Google Scholar]
  113. Lin T. K. Leu J. Y. Kuo J. T. Lai Y. L. Chung Y. C. Liu H. W. Appl. Sci. 2025;15:4345. doi: 10.3390/app15084345. [DOI] [Google Scholar]
  114. Sampath S. Ranjini S. S. Lavanya V. Samiappan S. C. J. Water Proc. Eng. 2025;76:108228. doi: 10.1016/j.jwpe.2025.108228. [DOI] [Google Scholar]
  115. Pooja A. G. Lasyal R. Kinet. Catal. 2024;65:122–132. doi: 10.1134/S0023158423600657. [DOI] [Google Scholar]
  116. Lin T. K. Leu J. Y. Kuo J. T. Lai Y. L. Chung Y. C. Liu H. W. Appl. Sci. 2025;15:4345. doi: 10.3390/app15084345. [DOI] [Google Scholar]
  117. Umar A. Alam S. Zaman H. Zahoor M. Ullah R. Ali E. A. Umar M. N. Appl. Organomet. Chem. 2025;39:e70189. doi: 10.1002/aoc.70189. [DOI] [Google Scholar]
  118. Agarwal S. Kim D. S. Nagappagari L. R. Yu Y. T. Inorg. Chem. Commun. 2025;180:114959. doi: 10.1016/j.inoche.2025.114959. [DOI] [Google Scholar]
  119. Umar A. Alam S. Zaman H. Zahoor M. Ullah R. Ali E. A. Umar M. N. Appl. Organomet. Chem. 2025;39:e70189. doi: 10.1002/aoc.70189. [DOI] [Google Scholar]
  120. Kunwar S. Roy A. Bhusal U. Gacem A. Abdullah M. M. S. Sharma P. Yadav K. K. Rustagi S. Chatterjee N. Deshwal V. K. Park H. K. Jeon B. H. Catalysts. 2023;13:891. doi: 10.3390/catal13050891. [DOI] [Google Scholar]
  121. He Q. Yu D. Ma T. Bao J. Wang J. Zhang J. Cheng J. Fan W. Li J. Mater. Chem. Phys. 2025;332:130296. doi: 10.1016/j.matchemphys.2024.130296. [DOI] [Google Scholar]
  122. Gupta A. Haque B. Roy A. Malik A. Ali Khan A. Kaur K. Roy A. Inorg. Chem. Commun. 2024;166:112599. doi: 10.1016/j.inoche.2024.112599. [DOI] [Google Scholar]
  123. Patel D. Ameta R. K. J. Mol. Struct. 2025;1340:142464. doi: 10.1016/j.molstruc.2025.142464. [DOI] [Google Scholar]
  124. Rius-Ayra O. Biserova-Tahchieva A. López-Jiménez I. Llorca-Isern N. Surf. Interfaces. 2025;72:106959. doi: 10.1016/j.surfin.2025.106959. [DOI] [Google Scholar]
  125. Haque B. Gupta A. Roy A. Malik A. Khan A. A. Clean Technol. Environ. Policy. 2025;27:993–1020. doi: 10.1007/s10098-024-02906-y. [DOI] [Google Scholar]
  126. Sun S. Fu X. Yang X. Zhao S. Zhi H. Shang R. Wang X. Yang Y. Yan Z. Hu L. Int. J. Biol. Macromol. 2025;308:142546. doi: 10.1016/j.ijbiomac.2025.142546. [DOI] [PubMed] [Google Scholar]
  127. Naseem K. Haider S. Alam K. Shabbir S. JOM. 2025;77:2624–2636. doi: 10.1007/s11837-025-07195-4. [DOI] [Google Scholar]
  128. Mishra S. R. Gadore V. Ahmaruzzaman M. Int. J. Environ. Anal. Chem. 2025;105:1738–1763. doi: 10.1080/03067319.2023.2298367. [DOI] [Google Scholar]
  129. Sharma K. Singh R. Sharma S. Tripathi C. S. P. Guin D. Colloids Surf., A. 2024;686:133332. doi: 10.1016/j.colsurfa.2024.133332. [DOI] [Google Scholar]
  130. Alotaibi B. M. Chen X. Alharbi T. M. D. Heydari A. Raston C. L. Chem. – Eur. J. 2025;31:e202403207. doi: 10.1002/chem.202403207. [DOI] [PubMed] [Google Scholar]
  131. Sharma N. Kaur M. Sharma V. Sharma S. Paul S. Inorg. Chem. Commun. 2024;161:112003. doi: 10.1016/j.inoche.2023.112003. [DOI] [Google Scholar]
  132. Li Y. Zhang X. Sun Y. Yang Z. Liu J. Int. J. Electrochem. Sci. 2023;18:100097. doi: 10.1016/j.ijoes.2023.100097. [DOI] [Google Scholar]
  133. Noreen I. Hashmi A. Iqbal Y. Malik F. P. Iqbal M. Amin F. Mater. Chem. Phys. 2023;308:128299. doi: 10.1016/j.matchemphys.2023.128299. [DOI] [Google Scholar]
  134. Boukoussa B. Cherdouane K. R. Zegai R. Mokhtar A. Hachemaoui M. Issam I. Iqbal J. Patole S. P. Zeggai F. Z. Hamacha R. Abboud M. Surf. Interfaces. 2024;44:103622. doi: 10.1016/j.surfin.2023.103622. [DOI] [Google Scholar]
  135. Al-Shawi N. H. A. A. Ebrahiminejad Z. Asgary S. Int. J. Mater. Res. 2024;115:586–595. doi: 10.1515/ijmr-2023-0263. [DOI] [Google Scholar]
  136. Swathy T. S. Antony M. J. Jose M. A. Mater. Chem. Phys. 2025;340:130788. doi: 10.1016/j.matchemphys.2025.130788. [DOI] [Google Scholar]
  137. Tu N. T. T. Thanh T. S. Quy P. T. Ha T. T. M. Thu P. T. K. Bich N. H. Sn L. V. T. Nguyen V. T. Nhiem D. N. Lieu P. K. Khieu D. Q. Adsorpt. Sci. Technol. 2023;2023:8943198. doi: 10.1155/2023/8943198. [DOI] [Google Scholar]
  138. Shanmugaraj K. Bedoya S. González-Vera D. Campos C. H. Mathivanan M. Arivazhagan M. Annamalai P. Gowri V. M. Thangavelu P. J. Water Proc. Eng. 2025;71:107234. doi: 10.1016/j.jwpe.2025.107234. [DOI] [Google Scholar]
  139. Ingrosso C. Disha A. Dell'Edera M. De Pasquale I. Bianco G. V. Milella A. Grandolfo A. Mesto E. Schingaro E. Striccoli M. Fanizza E. Comparelli R. Curri M. L. J. Photochem. Photobiol., A. 2025;460:116149. doi: 10.1016/j.jphotochem.2024.116149. [DOI] [Google Scholar]
  140. Goswami R. Goswami Y. C. Shahrestasni M. Rev. Roum. Chim. 2024:595–603. doi: 10.33224/rrch.2024.69.10-12.09. [DOI] [Google Scholar]
  141. Ghosh S. Mallik T. Roy M. N. Ekka D. ChemistrySelect. 2025;10:e202405880. doi: 10.1002/slct.202405880. [DOI] [Google Scholar]
  142. Qayyum M. Faizan M. Javed M. Fiaz M. Fatima M. Ali A. Ali S. K. Bahadur A. Iqbal S. Mahmood S. Jafri I. Farouk A. E. J. Inorg. Organomet. Polym. Mater. 2025:1–25. [Google Scholar]
  143. Mensah K. Shokry H. Elkady M. Hawash H. B. Samy M. Water Sci. Eng. 2024;17:226–235. doi: 10.1016/j.wse.2024.01.005. [DOI] [Google Scholar]
  144. Natrayan L. Surakasi R. Kaliappan S. Patil P. P. Saravanan A. Siranjeevi R. Surf. Interfaces. 2023;41:103151. doi: 10.1016/j.surfin.2023.103151. [DOI] [Google Scholar]
  145. Ravichandran R. Annamalai K. Annamalai A. Elumalai S. Colloids Surf., A. 2023;664:131117. doi: 10.1016/j.colsurfa.2023.131117. [DOI] [Google Scholar]
  146. sh El-sonbaty S. Rashad M. Abu El-Fadl A. A. Abu-Sehly A. A. Mohammed M. M. J. Mol. Liq. 2025;422:126900. doi: 10.1016/j.molliq.2025.126900. [DOI] [Google Scholar]
  147. Hu W. Yang Q. Wang R. Chen Q. Kong Y. Environ. Prog. Sustainable Energy. 2025;44:e14543. doi: 10.1002/ep.14543. [DOI] [Google Scholar]
  148. Yu Q. Liu Z. Wang T. Kou X. Zhao L. Sun P. Lu G. ACS Nano. 2025;19:16639–16649. doi: 10.1021/acsnano.5c00604. [DOI] [PubMed] [Google Scholar]
  149. Karami Z. Abbasi A. Ghorbani P. Zamani S. J. Solid State Chem. 2025;347:125329. doi: 10.1016/j.jssc.2025.125329. [DOI] [Google Scholar]
  150. Weir C. N. G. Blanchard R. J. Parsons A. P. Kalarikkandy G. Katz M. J. J. Mater. Chem. C. 2023;12:125–131. doi: 10.1039/D3TC03120A. [DOI] [Google Scholar]
  151. Saha S. Aalam G. Ajay Amir M. Sayeed Khan G. Ingole P. P. Wazed Ali S. ChemistrySelect. 2024;9:e202400044. doi: 10.1002/slct.202400044. [DOI] [Google Scholar]
  152. Jayasundara T. Perera I. Hettiarachchi C. Mater. Chem. Phys. 2025;332:130292. doi: 10.1016/j.matchemphys.2024.130292. [DOI] [Google Scholar]
  153. Karimi S. Gholinejad M. Khezri R. Sansano J. M. Nájera C. Yus M. RSC Adv. 2023;13:8101–8113. doi: 10.1039/D3RA00283G. [DOI] [PMC free article] [PubMed] [Google Scholar]
  154. Ahmadijokani F. Ahmadipouya S. Haris M. H. Rezakazemi M. Bokhari A. Molavi H. Ahmadipour M. Pung S. Y. Klemeš J. J. Aminabhavi T. M. Arjmand M. ACS Appl. Mater. Interfaces. 2023;15:30106–30116. doi: 10.1021/acsami.3c02171. [DOI] [PubMed] [Google Scholar]
  155. Ghasempour H. Zarekarizi F. Morsali A. CrystEngComm. 2022;24:4074–4084. doi: 10.1039/D2CE00369D. [DOI] [Google Scholar]
  156. Haleem A. Zhu X. Khan D. M. Bakhsh B. G. Huang K. Li H. Zhong H. Int. J. Biol. Macromol. 2025;316:144543. doi: 10.1016/j.ijbiomac.2025.144543. [DOI] [PubMed] [Google Scholar]
  157. Bhat M. Vijaya Sekhar E. Kalaiah B. Sagar. 2025;14:45. [Google Scholar]
  158. Aguilar-Ferrer D. Vasileiadis T. Iatsunskyi I. Ziółek M. Żebrowska K. Ivashchenko O. Błaszkiewicz P. Grześkowiak B. Pazos R. Moya S. Bechelany M. Coy E. Adv. Funct. Mater. 2023;33:2304208. doi: 10.1002/adfm.202304208. [DOI] [Google Scholar]
  159. Iqbal S. Iqbal N. Musaddiq S. Farooqi Z. H. Habila M. A. Wabaidur S. M. Iqbal A. Heliyon. 2024;10(3):e25385. doi: 10.1016/j.heliyon.2024.e25385. [DOI] [PMC free article] [PubMed] [Google Scholar]
  160. Correa P. A. P. Buenaventura S. F. O. Santos J. R. S. Lopez E. C. R. Next Mater. 2025;8:100621. doi: 10.1016/j.nxmate.2025.100621. [DOI] [Google Scholar]
  161. Wani M. Y. Shah S. A. New J. Chem. 2024;48:19044–19059. doi: 10.1039/D4NJ03947E. [DOI] [Google Scholar]
  162. Surti P. Kumar Kailasa S. Jung Park T. Kumar Mungray A. Sustain. Energy Technol. Assessments. 2024;61:103584. doi: 10.1016/j.seta.2023.103584. [DOI] [Google Scholar]
  163. Nguyen T. M. Kaushik N. Nguyen L. T. Nguyen G. T. Nguyen T. H. Pham H. S. Choi E. H. Kaushik N. K. Nguyen L. N. Appl. Sci. 2025;15:5280. doi: 10.3390/app15105280. [DOI] [Google Scholar]
  164. Raza A. Rauf Khan S. Ali S. Jamil S. Bibi S. Inorg. Chem. Commun. 2023;153:110851. doi: 10.1016/j.inoche.2023.110851. [DOI] [Google Scholar]
  165. Hussain I. Shahid M. Ali F. Irfan A. Begum R. Farooqi Z. H. Environ. Technol. 2023;44:1679–1689. doi: 10.1080/09593330.2021.2011429. [DOI] [PubMed] [Google Scholar]
  166. Arif M. Raza H. Haroon S. M. Ben Moussa S. Tahir F. Alzahrani A. Y. A. Int. J. Biol. Macromol. 2024;270:132331. doi: 10.1016/j.ijbiomac.2024.132331. [DOI] [PubMed] [Google Scholar]
  167. Al-Essa K. Al-Essa E. M. Qarqaz A. Al-Issa S. Alshahateet S. F. Al-Fawares O. Water. 2025;17:158. doi: 10.3390/w17020158. [DOI] [Google Scholar]
  168. Hernández-García Á. I. Bustos-Bustos E. Campos-Delgado J. Kolosovas-Machuca E. S. Navarro-Amador R. Cerro-Lopez M. J. Mater. Chem. A. 2026;14:3985–3994. doi: 10.1039/D5TA05796E. [DOI] [Google Scholar]
  169. Saif A. Ali S. Jamil S. Kamal T. Latif M. J. Khan S. R. Arshad H. Mariam U. Liaqat S. J. Inorg. Organomet. Polym. Mater. 2024;35(5):3344–3365. doi: 10.1007/s10904-024-03460-2. [DOI] [Google Scholar]
  170. Saha A. Hossain S. Sultana M. J. Ahmed F. R. S. Sohag M. S. U. Islam M. E. Next Mater. 2026;11:101899. doi: 10.1016/j.nxmate.2026.101899. [DOI] [Google Scholar]
  171. Zahran M. Gamal S. Zahran M. A. H. Azzem M. A. Microchem. J. 2025;213:113627. doi: 10.1016/j.microc.2025.113627. [DOI] [Google Scholar]
  172. Gholinejad M. Mohammadi S. Nayeri S. Sansano J. M. Inorg. Chem. Commun. 2025;177:114376. doi: 10.1016/j.inoche.2025.114376. [DOI] [Google Scholar]
  173. Saddiqua A. Ali S. Jamil S. Noreen S. Khan S. R. Latif M. J. Nazir L. Saif A. Fatima K. J. Inorg. Organomet. Polym. Mater. 2025;35(9):7422–7441. doi: 10.1007/s10904-025-03758-9. [DOI] [Google Scholar]
  174. Khan S. Roy A. Chem. Pap. 2026;80(5):5195–5206. doi: 10.1007/s11696-025-04618-z. [DOI] [Google Scholar]
  175. Saba M. Farooq S. Alessa A. H. Bektas K. I. Belduz A. O. Khan A. Z. Shah A. A. Badshah M. Khan S. BMC Biotechnol. 2025;25(1):27. doi: 10.1186/s12896-025-00959-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  176. Belachew K. Tegegne N. A. Kebede M. A. Andoshe D. M. Zhang Q. Hone F. G. Mater. Adv. 2026;7:4725–4743. doi: 10.1039/D6MA00160B. [DOI] [Google Scholar]
  177. Shivani Bhat R. S. Sajankila S. P. Bindu A. G. Appl. Phys. A. 2025;131(8):649. doi: 10.1007/s00339-025-08775-6. [DOI] [Google Scholar]
  178. Amiri F. Iranmanesh P. Khorasanipour N. Saeednia S. Int. J. Environ. Sci. Technol. 2025;23(1):48. doi: 10.1007/s13762-025-06818-2. [DOI] [Google Scholar]
  179. Naas A. Gueddim A. Khader B. Meglali O. Bouraiou A. Phys. B. 2025;711:417230. doi: 10.1016/j.physb.2025.417230. [DOI] [Google Scholar]
  180. Arif M. Rauf A. Hussain T. Alrokayan S. J. Mol. Liq. 2025;437:128405. doi: 10.1016/j.molliq.2025.128405. [DOI] [Google Scholar]
  181. Kabiri B. Heidari H. Sci. Rep. 2025;15:1–20. doi: 10.1038/s41598-025-98540-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  182. Ullah I. Tariq M. Muhammad M. Khan J. Rahim A. Abdullah A. Z. Colloids Surf., A. 2023;679:132614. doi: 10.1016/j.colsurfa.2023.132614. [DOI] [Google Scholar]
  183. Afaq M. Sajid A. Manzoor Q. Imtiaz F. Sajid A. Javed R. Ahmad A. Alwadai N. Mnif W. Iqbal M. Mater. Sci. Eng., B. 2025;312:117847. doi: 10.1016/j.mseb.2024.117847. [DOI] [Google Scholar]
  184. Goswami Y. C. Kaundal J. B. Begzaad S. Tiwari R. K. J. Iran. Chem. Soc. 2023;20:1681–1697. doi: 10.1007/s13738-023-02789-8. [DOI] [Google Scholar]
  185. Alharbi A. A. Aldaghri O. A El-Badry B. Ibnaouf K. H. Alfadhl F. Albadri A. Ahmed A. H. Modwi A. Opt. Mater. 2024;152:115443. doi: 10.1016/j.optmat.2024.115443. [DOI] [Google Scholar]
  186. Guedri A. Zaabat M. Boudine B. Guedri O. Hafdallah A. J. Inorg. Organomet. Polym. Mater. 2024;34:5193–5202. doi: 10.1007/s10904-024-03118-z. [DOI] [Google Scholar]
  187. Lee K. C. Tiong T. J. Pan G. T. Yang T. C. K. Uma K. Tseng Z. L. Nikoloski A. N. Huang C. M. J. Compos. Sci. 2024;8:164. doi: 10.3390/jcs8050164. [DOI] [Google Scholar]
  188. Rahul S. George A. Vinoth Kumar J. Shankar R. Raj A. D. Senthil Kumar M. Sundaram S. J. Babu R. S. Alam M. W. J. Mater. Sci.: Mater. Electron. 2025;36:1–21. [Google Scholar]
  189. Lianmawii L. Singh N. M. Russ. J. Phys. Chem. B. 2024;18:325–342. doi: 10.1134/S1990793124010329. [DOI] [Google Scholar]
  190. Gudadur K. S. Balakrishnan R. M. Kadam V. V. Int. J. Environ. Res. 2025;19:1–24. [Google Scholar]
  191. Idris D. S. Roy A. Nano-Struct. Nano-Objects. 2024;38:101142. doi: 10.1016/j.nanoso.2024.101142. [DOI] [Google Scholar]
  192. Sharma P. Ganguly M. Sahu M. RSC Adv. 2024;14:14606–14615. doi: 10.1039/D4RA01354A. [DOI] [PMC free article] [PubMed] [Google Scholar]
  193. Magdaleno A. L. Brillas E. Garcia-Segura S. dos Santos A. J. Sep. Purif. Technol. 2024;345:127295. doi: 10.1016/j.seppur.2024.127295. [DOI] [Google Scholar]
  194. Safo K. Noby H. Mitsuhara M. Naragino H. El-Shazly A. H. Environ. Nanotechnol. Monit. Manag. 2023;20:100836. [Google Scholar]
  195. Ghezali B. Ghazi A. Messaoud S. A. E. K. A. Benouis K. Megherbi A. Said M. E. A. Ghezali S. Ghezali S. Stud. Sci. Sci. 2025;43:11–24. [Google Scholar]
  196. Hussain S. Muhammad S. Gul S. Khan A. Ahmad S. Int. J. Environ. Sci. Technol. 2024;21:10115–10126. doi: 10.1007/s13762-024-05627-3. [DOI] [Google Scholar]
  197. Kadhim H. A. Hassan S. A. AIP Conf. Proc. 2023;2414(1):050031. doi: 10.1063/5.0114713. [DOI] [Google Scholar]
  198. Maseeh I. Anwar F. Aroob S. Javed T. Bibi I. Almasoudi A. Raheel A. Javid M. A. Carabineiro S. A. C. Taj M. B. Mater. Adv. 2024;5:5080–5095. doi: 10.1039/D4MA00038B. [DOI] [Google Scholar]
  199. Pooja A. G. Lasyal R. Kinet. Catal. 2024;65(2):122–132. doi: 10.1134/S0023158423600657. [DOI] [Google Scholar]
  200. Hussain M. Hussaini S. S. Shariq M. Alshehri E. M. AlRisi S. AlNoufali M. AlSaidi H. AlYahmadi I. Z. Khatab A. Diamond Relat. Mater. 2026;161:113131. doi: 10.1016/j.diamond.2025.113131. [DOI] [Google Scholar]
  201. Rius-Ayra O. Biserova-Tahchieva A. López-Jiménez I. Llorca-Isern N. Surf. Interfaces. 2025;72:106959. doi: 10.1016/j.surfin.2025.106959. [DOI] [Google Scholar]
  202. Bensalah J. Idrissi A. El Faydy M. Doumane G. Staoui A. Hsissou R. Lebkiri A. Habsaoui A. Abdelkader Z. Rifi E. H. J. Mol. Struct. 2023;1278:134849. doi: 10.1016/j.molstruc.2022.134849. [DOI] [Google Scholar]
  203. Jamshaid H. Aslam N. Saleem A. Younas U. Alzahrani F. M. Sajid A. Mnif W. Ali Z. Iqbal M. Pervaiz M. J. Sol-Gel Sci. Technol. 2025;116(3):2809–2821. doi: 10.1007/s10971-025-06999-9. [DOI] [Google Scholar]
  204. Inam H. Durrani A. I. Huma R. Hussain F. Chem. Pap. 2025;79(9):5921–5940. doi: 10.1007/s11696-025-04163-9. [DOI] [Google Scholar]
  205. Ullah I. Tariq M. Abdullah A. Z. Muhammad M. Khan J. Rahim A. Int. J. Environ. Res. 2024;18(6):96. doi: 10.1007/s41742-024-00653-y. [DOI] [Google Scholar]
  206. Nguyen N. P. T. Nguyen N. T. T. Nguyen T. T. T. Nguyen D. T. C. Arabian J. Sci. Eng. 2025;50(24):20649–20663. doi: 10.1007/s13369-025-10283-x. [DOI] [Google Scholar]
  207. Gholinejad M. Bashirimousavi S. Sansano J. M. Sci. Rep. 2024;14(1):5852. doi: 10.1038/s41598-024-56559-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  208. Memon K. Memon R. Khalid A. Al-Anzi B. S. Uddin S. Sherazi S. T. H. Chandio A. Talpur F. N. Latif A. A. Liaqat I. RSC Adv. 2023;13:29270–29282. doi: 10.1039/D3RA03663D. [DOI] [PMC free article] [PubMed] [Google Scholar]
  209. Alula M. T. Spende H. Aragaw T. A. Alene A. N. Aragaw B. A. Madiba M. J. Cluster Sci. 2022;34(4):2205–2214. doi: 10.1007/s10876-022-02386-4. [DOI] [Google Scholar]
  210. Mota D. R. Martini W. da S. Pellosi D. S. Environ. Sci. Pollut. Res. 2023;30:57667–57682. doi: 10.1007/s11356-023-26580-7. [DOI] [PubMed] [Google Scholar]
  211. Ahmad I. Rehman Z. U. Mahmood S. Raza A. Qureshi U. U. R. Qayyum H. Ali T. Rasheed M. A. Hassan S. M. U. Phys. Scr. 2025;100:065962. doi: 10.1088/1402-4896/add79f. [DOI] [Google Scholar]
  212. Do N. H. Nguyen O. H. Nguyen H. T. Le K. A. Le P. K. Materials and Emerging Technologies for Sustainability. 2026;2(2):2650005. doi: 10.1142/S3060932126500056. [DOI] [Google Scholar]
  213. Ranjbari A. Anbari A. P. Kashif M. Adhikary K. K. Kim K. H. Heynderickx P. M. Chem. Eng. J. 2025;505:159526. doi: 10.1016/j.cej.2025.159526. [DOI] [PubMed] [Google Scholar]
  214. Ali Z. H. Abdulazeem L. Kadhim W. A. Kzar M. H. Al-sareji O. J. Sci. Rep. 2024;14:1–12. doi: 10.1038/s41598-024-76090-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  215. Altun T. Acar M. K. Gubbuk I. H. ACS Omega. 2025;10:134–146. doi: 10.1021/acsomega.4c02497. [DOI] [PMC free article] [PubMed] [Google Scholar]
  216. Maseeh I. Anwar F. Aroob S. Javed T. Bibi I. Almasoudi A. Raheel A. Javid M. A. Carabineiro S. A. C. Taj M. B. Mater. Adv. 2024;5:5080–5095. doi: 10.1039/D4MA00038B. [DOI] [Google Scholar]
  217. Jabeen T. Khan M. S. Javaid S. Azeem W. Ayoub R. Motola M. RSC Adv. 2024;14:12513–12527. doi: 10.1039/D4RA02430C. [DOI] [PMC free article] [PubMed] [Google Scholar]
  218. Rani A. Singh K. Patel A. S. Sharma P. Bull. Mater. Sci. 2023;46:1–9. [Google Scholar]
  219. Toprak Y. E. Çubuk S. Kahraman M. V. ChemistrySelect. 2026;11(5):e07129. doi: 10.1002/slct.202507129. [DOI] [Google Scholar]
  220. Senthilraja A. Durai M. Mohanty S. S. Kumaravel S. Medidi R. S. Periyasami G. Kaliyamoorthy S. Balu K. Ahn Y. H. Shanthi M. J. Mol. Struct. 2025;1321:139993. doi: 10.1016/j.molstruc.2024.139993. [DOI] [Google Scholar]
  221. Parsafard N. Riahi-Madvar A. Sci. Rep. 2026;16(1):12322. doi: 10.1038/s41598-026-41059-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  222. majed A. A. Abbar A. H. Chem. Eng. Res. Des. 2025;223:813–825. doi: 10.1016/j.cherd.2025.10.037. [DOI] [Google Scholar]
  223. Hussain S. Muhammad S. Gul S. Khan A. Ahmad S. Int. J. Environ. Sci. Technol. 2024;21(16):10115–10126. doi: 10.1007/s13762-024-05627-3. [DOI] [Google Scholar]
  224. Haque B. Gupta A. Roy A. Malik A. Khan A. A. Clean Technol. Environ. Policy. 2024;27(3):993–1020. doi: 10.1007/s10098-024-02906-y. [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

No primary research results, software or code have been included and no new data were generated or analysed as part of this review.


Articles from RSC Advances are provided here courtesy of Royal Society of Chemistry

RESOURCES