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Nanoscale Advances logoLink to Nanoscale Advances
. 2026 Sep 9. Online ahead of print. doi: 10.1039/d6na00434b

In situ growth of SnS2 nanoplates on g-C3N4 nanosheets: an efficient nanoheterostructure for hydrogen generation

Amol G Kadlag a,b, Niteen S Jawale b, Shrinivas C Motekar b,c, Govind G Umarji b, Krishna D Daware d, Jalindar D Ambekar b, Sudhir S Arbuj b,✉
PMCID: PMC13625683  PMID: 42820003

Abstract

The development of reliable, efficient photocatalysts for water splitting is essential to the production of clean hydrogen energy. Fast charge recombination limits the efficiencies of graphitic carbon nitride (g-C3N4) and tin disulfide (SnS2), notwithstanding their potential as materials. In this work, pristine SnS2, pristine g-C3N4, and various SnS2/g-C3N4 nanocomposites (containing 2.5, 5, 10, 20, and 30 wt% of SnS2) were effectively synthesized using a one-step in situ hydrothermal method. The structural, optical, morphological, and electrical properties of the materials were carefully investigated using XRD, IR, UV-vis, PL, XPS, FESEM, FETEM, and photoconductivity tests. The generated materials were evaluated for photocatalytic hydrogen generation via water splitting under a 400 W mercury vapor lamp. Of all the generated samples, the 10% SnS2/g-C3N4 nanocomposite exhibited the highest photocatalytic activity. It generated a peak hydrogen generation yield of around 1094.7 µmol 0.1 g−1 of catalyst over a 4-hour reaction time. PL and photoconductivity measurements indicate that this enhanced activity is due to reduced recombination of photogenerated electron–hole pairs and fast interfacial charge transfer. Furthermore, after three consecutive cycles of reuse, the 10% nanocomposite demonstrated exceptional stability and continued to function well. Creating an ideal 10% SnS2/g-C3N4 heterojunction significantly improves charge separation and catalytic efficiency. This illustrates its potential as a dependable, reusable catalyst for solar-powered hydrogen production.


The development of reliable, efficient photocatalysts for water splitting is essential to the production of clean hydrogen energy.graphic file with name d6na00434b-ga.webp

1. Introduction

The ever-growing global population is driving an unprecedented surge in energy demand.1,2 At present, approximately 80% of the world's energy needs are fulfilled by non-renewable energy sources, including carbon-based fossil fuels such as coal and petroleum.3,4 The formation of fossil fuels is a complex process that unfolds over millions, and in some instances, even billions of years. Unfortunately, the combustion of these fuels results in the emission of over 7.8 billion metric tons of carbon dioxide into the atmosphere, along with other harmful and toxic gases such as NO, CH4, SO2, CO, and so on.5 These gases have a detrimental effect on biodiversity and other forms of life as a result of global warming and climate change. It is becoming more and more apparent that fossil fuels are non-renewable and finite.6,7 Therefore, it is essential to focus on energy conservation and explore innovative renewable energy sources.5,8 At this pivotal juncture, the world has the potential to shift towards renewable energy sources that prioritize environmental safety and human health.9,10 Renewable energy stands out as the most effective alternative to fossil fuels, primarily because of its superior sustainability.11–13 Hydrothermal, geothermal, wind, and solar power are well-known renewable energy sources that are abundant, safe, and dependable in their efforts to reduce pollution and climate change.14

In this context, hydrogen (H2) is viewed as a clean, environmentally friendly substitute for fossil fuels, suitable for direct use in automobiles or in fuel cells for power generation.15,16 Researchers from all over the world think that H2 is one of the best possible alternatives to the fossil fuels for the 21st century.17 Due to its higher energy density, absence of carbon emissions, and eco-friendliness.18 Hydrogen production can be achieved through several methods, including partial oxidation of methane, methane reforming, autothermal reforming, plasmolysis of hydrocarbons, and water splitting.19 Hydrogen production via water splitting stands out as a compelling and eco-friendly approach, leveraging renewable resources such as water and effectively mitigating environmental issues.8

Among all renewable energy sources, sunlight is a sustainable, clean, and abundant resource that offers a large quantity of energy compared to other available renewable sources on Earth.8,20 Consequently, solar energy possesses significant potential for addressing future energy requirements in accordance with sustainability standards. The advancement of photocatalysts that operate in sunlight is a possible solution to address increasing energy demand.21 To effectively dissociate water into H2 and O2, scientists developed artificial photocatalysts, drawing inspiration from the natural photosynthesis process. In this scenario, the photocatalyst produces potent reducing (electrons) and oxidizing (holes) species to facilitate the reduction and oxidation of H2O, resulting in the generation of H2 and O2.22,23 Photocatalytic water splitting has garnered significant interest due to its potential to harness substantial solar energy for hydrogen production from water.24 This approach is efficient, cost-effective and sustainable. This photocatalytic phenomenon is being widely investigated after the first report published by Fujishima and Honda in 1972. It described revolutionary research on decomposition of water into hydrogen and oxygen over semiconductor nanostructures as heterogeneous photocatalysts. Their approach used a photoelectrochemical cell consisting of TiO2 as the photoanode and platinum as the counter electrode. The cell worked under UV irradiation, with an external bias.25 The photocatalytic hydrogen production technique is a pioneering method that might completely change how we deal with pressing global problems. This is especially important in a time when environmental problems are getting worse and we can focus to embark on some eye-catching progress to make things more sustainable.26–28

Semiconductors are acknowledged for their outstanding efficacy in photocatalysis, photovoltaic devices, and other photo-conductive materials.29,30 In semiconductors, photons can excite electrons, resulting in efficient photogenerated electron–hole pairs that participate in redox processes.31 As a result, semiconductors are extensively employed in photocatalytic hydrogen generation. Prevalent categories of photocatalytic hydrogen generation catalysts encompass metal oxides,32,33 including TiO2, NiO, ZnO, NaTaO3, WO3, Ta2O5, SnO2, Cu2O, and CeO2;34–44 metal sulfides such as CdS, ZnS, MoS2, and SnS2;45–48 as well as other semiconductors such as BiVO4,49,50 BiOBr,51,52 ZnIn2S4,53–55 SrTiO3,56–58 MXenes,59–61 and transition metal phosphides.62–64

With the convergence of advancements in nanotechnology, materials science, and surface engineering, the researchers have gained enough insights to improve the photocatalytic efficiency of semiconductor photocatalysts. This can be achieved through modifications in synthesis methods, band gap tuning, loading of transition and noble metals, the development of porous structures, different morphologies and formation of homo- or heterojunctions. The anticipated outcomes of these initiatives are the development of highly efficient and scalable photocatalytic systems that will contribute to a sustainable energy future.33,65,66

Photocatalysts, which harness light energy to drive chemical reactions, have been at the forefront of renewable energy research, particularly in hydrogen generation via water splitting. Recently, semiconductor metal sulphides have garnered significant interest owing to their superior physical and chemical properties.67,68 Metal sulphides exhibit a narrow band gap energy and possess a negative band potential.69,70 Tin sulphide (SnS2), characterized by an indirect band gap ranging from approximately 1.91 to 2.35 eV, stands out as a particularly intriguing metal sulphide photocatalyst. Its ability to respond to visible light, combined with its affordability and non-toxic nature, enhances its appeal in the field.71–73

Nonetheless, the photocatalytic performance of single SnS2 remains suboptimal because of the rapid recombination rate of photoexcited carriers and inherent instability.74,75 Therefore, it is essential to address the aforementioned drawbacks of SnS2. The development of semiconductor nanocomposites has demonstrated significant effectiveness in improving photocatalytic activity.

For this purpose, graphitic carbon nitride (g-C3N4) has garnered considerable attention because it is a non-toxic, inexpensive, stable and facile polymeric semiconductor, which shows excellent optical performance, narrow band gap about 2.7 eV and strong visible light absorption. Moreover, it can be used to create a range of nanocomposite photocatalysts with diverse range of modification methods.76–81

Recent studies demonstrate that heterostructure engineering can significantly improve photocatalytic performance by enhancing interfacial charge transfer and suppressing photogenerated electron–hole recombination. For instance, LaFeO3/CNT heterostructures show improved charge transport,82 while Co3O4/MXenes exhibit reduced charge-transfer resistance due to efficient interfacial electron transport.83 Similarly, MnFe2O4@TiO2@MWCNTs and SrFe12O19/g-C3N4-based nanoheterostructures display enhanced photocatalytic activity through improved interfacial interactions and charge-carrier dynamics.84,85 The incorporation of conductive or plasmonic components can further promote charge migration, as demonstrated in Ag/Al@SrFe12O19/g-C3N4 systems.86 Overall, these studies highlight that photocatalytic efficiency strongly depends on the interfacial structure, charge-transfer pathways, and carrier dynamics, emphasizing the importance of understanding interfacial charge behaviour for the rational design of efficient heterojunction photocatalysts for solar-energy conversion and H2 generation.

In order to facilitate the separation of photogenerated charge carriers, g-C3N4 can be coupled with other semiconductors to provide interfacial charge channels between composites.87

In this study, we synthesized SnS2 nanosheets supported on g-C3N4 nanosheets to form a SnS2/g-C3N4 nanocomposite via an “in situ” hydrothermal approach, optimizing the SnS2 content in the SnS2/g-C3N4 nanocomposite. The resultant nanocomposites were meticulously studied and utilized for photocatalytic water splitting to produce hydrogen. A potential photocatalytic mechanism for the improved photocatalytic activity of SnS2/g-C3N4 composites was presented.

2. Experimental section

2.1. Materials

Melamine was purchased from Sigma-Aldrich, stannic(iv) chloride (SnCl4·5H2O) was purchased from Avra Pvt. Ltd, and thiourea (CH4N2S) was purchased from Fisher Scientific. All chemicals were used as received without further purification.

2.2. Synthesis of g-C3N4 powder

For the synthesis of g-C3N4 powder, our previously reported method was utilized.44 In a typical experimental procedure for the synthesis of g-C3N4, melamine was used. 5 g of melamine was kept in a crucible and calcined in a muffle furnace at 550 °C for 4 h at 5 °C per min ramp rate. The obtained yellow mass was allowed to remain in the muffle furnace until it attained room temperature and then ground carefully to get fine powder.

2.3. Synthesis of the SnS2/g-C3N4 nanocomposite

The SnS2/g-C3N4 nanocomposite was synthesized by an in situ hydrothermal method with g-C3N4, SnCl4·5H2O and thiourea as precursors. Typically, 1 g of g-C3N4 nanosheets was dispersed in deionised water by sonication under stirring. Then, a certain amount of SnCl4·5H2O and thiourea was dissolved in deionised water under magnetic stirring at room temperature. Then, both these solutions were added into g-C3N4 aqueous dispersion drop by drop under magnetic stirring. Then, the mixture was transferred into a 100 mL Teflon-lined stainless steel autoclave and heated at 150 °C for 12 h. After the completion of the reaction, the autoclave was naturally cooled to ambient temperature, the obtained yellow product was washed thoroughly with deionised water followed by ethanol, separated by centrifugation and dried at 60 °C in a vacuum oven for 24 h before being used for further characterization. The mass ratios of SnS2 to g-C3N4 were set as 2.5%, 5%, 10%, 20% and 30% by adjusting the amount of the added precursors, and the obtained products were denoted as X% SnS2/g-C3N4 (X = 2.5, 5, 10, 20 and 30). For comparison, pristine SnS2 was synthesized using the same hydrothermal method without adding g-C3N4.

2.4. Catalyst characterization methods

The detailed crystal structure and phase of the prepared nanocomposites were analysed by powder X-ray diffraction (XRD) using a Rigaku MiniFlex equipped with a monochromator and Ni-filtered Cu Kα radiation with a wavelength of 1.5418 Å, in the 2θ range of 5–80° at a scan rate of 1° min −1. Field emission scanning electron microscopy (FE-SEM, HITACHI S-4800) was performed to find the surface morphology of the as-synthesized nanocomposite. Field emission TEM (FE-TEM) and selected area electron diffraction (SAED) were also performed using a TALOS F200S G2 at an operating voltage of 200 kV. Diffuse reflectance UV-visible spectra (DRS) were recorded using a Shimadzu UV-vis-NIR spectrophotometer (Model UV-3600) in the wavelength range of 200 to 800 nm at room temperature. A Shimadzu RF-5301pc spectroflurophotometer was used to record photoluminescence (PL) spectra at the room temperature. To analyse the composition of the surface elements and the chemical states of the atoms, X-ray photoelectron spectroscopy (XPS) measurement was performed using a PHI Genesis spectrometer with Al Kα radiation (photon energy = 1486.6 eV, 15 kV, 150 W). The specific Brunauer–Emmett–Teller (BET) surface areas of g-C3N4, SnS2 and g-C3N4/SnS2 composites were determined using (Quanta Chrome NOVA touch LX1) N2 adsorption isotherms at liquid N2 temperature. Before BET analysis, the samples were degassed in a vacuum at 150 °C for 2 h.

2.5. Photocatalytic activity measurement

The photocatalytic activity of the prepared nanocomposite was evaluated by measuring evolved H2via water splitting.

2.5.1. Photocatalytic H2 generation

Here, we used a cylindrical quartz vessel (100 ml, height 17 cm, including a 14 mm neck and diameter 6.5 cm) to measure the photocatalytic performance of the prepared g-C3N4, SnS2 and SnS2/g-C3N4 nanocomposites for H2 generation via water splitting. To measure the amount of evolved H2 gas, the system was sealed with a rubber septum, and the evolved H2 gas was collected using a gas-tight syringe. Under vigorous magnetic stirring, the sealed quartz reactor was placed under a 400 W mercury vapour lamp. To minimize the heating effect due to the light source, the mercury lamp was fitted in a quartz condenser having an outer water circulation arrangement. To measure the photocatalytic activity, 25 mL of distilled water was added to a quartz reactor containing 20 mg of the prepared catalyst, with 1 wt% preloaded Pt as a co-catalyst, along with 5 mL of a methanol solution. Then, 0.1 M Na2S and 0.1 M Na2SO3 were added as sacrificial agents in the above solution. Nitrogen gas was bubbled for 15 min to remove the dissolved gases from the reaction mixture. The reactor was then carefully sealed with a rubber septum and properly tightened with Teflon tape. The sealed reactor vessel was stirred under a 400 W mercury vapour lamp. After regular time intervals, 0.5 mL of the evolved H2 gas was removed from the reactor using a gas tight syringe and then immediately quantified using a gas chromatograph (Shimadzu, Model GC 2014) equipped with a Porapak Q column and a thermal conductivity detector. To calculate the amount of hydrogen gas evolved, the standard fitted curve was used.

2.5.2. Photoconductivity measurement

The photoconductivity of synthesized g-C3N4, SnS2 and SnS2/g-C3N4 nanocomposites was also investigated to support the photocatalytic activity. For photoconductivity measurements, pre-patterned silver interdigitated electrodes (CI1001, ECM, USA), jet-printed on a paper substrate using a Nordson PICO Pulse contact dispensing valve printer, were used, on which g-C3N4, SnS2 and SnS2/g-C3N4 nanostructured powder films were deposited. The electrodes maintained a spacing of 200 µm with a total path length of 30 mm. A 6 mm diameter open mask was applied over the pre-patterned silver electrode to ensure a consistent deposition area of the powder film for each photoconductivity measurement. The deposited electrodes were used directly for I–V measurements, which were conducted at room temperature with a Kelvin probe connected to spring-loaded pressure contacts. To minimize electrical noise, the entire setup was housed within a metallic chamber shield. I–V measurements were performed using a Keithley 4200 Semiconductor Characterization System (SCS) integrated with a photo-emission setup, consisting of a 1000 W xenon lamp and a 1.5 AM (air-mass) ratio.

3. Results and discussion

3.1. X-ray diffraction analysis

The phase structures of pristine g-C3N4, pristine SnS2 and SnS2/g-C3N4 nanocomposites were identified by XRD investigation, and the outcomes are shown in Fig. 1. In the XRD pattern of pristine g-C3N4, the typical diffraction peaks at 13.2° and 27.5° are attributed to the (100) and (002) crystal planes of g-C3N4, respectively.88 These peaks correspond to the characteristic interplanar stacking and interlayer structural packing. In the XRD pattern of pure SnS2, the diffraction peaks at 2θ = 15, 28.1, 32.1, 41.8, 46.1, 49.9, 52.4, 54.9, 58.3, 60.6, 62.9, and 67.1 coincide with the (001), (100), (101), (102), (003), (110), (111), (103), (200), (201), (004) and (202) crystal planes of pure SnS2, respectively, having a hexagonal crystal structure. The peaks in the XRD pattern show the formation of the hexagonal phase of SnS2 (JCPDS card no. 23-0677).89 In the XRD pattern of the SnS2/g-C3N4 nanocomposite material, the main characteristic peaks of g-C3N4 and SnS2 are seen. But after the introduction of different wt% of SnS2, the XRD peak intensities of SnS2 and g-C3N4 show an opposite trend. Intensity of SnS2 peaks goes on increasing with increasing wt% of SnS2, while the intensity of the g-C3N4 peak goes on decreasing, and a slightly broader peak is seen.90 These results indicate that the successful formation of the SnS2/g-C3N4 nanocomposite.

Fig. 1. XRD patterns of pristine g-C3N4, pristine SnS2, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4, and 30% SnS2/g-C3N4.

Fig. 1

3.2. Fourier transform infrared (FT-IR) spectrum analysis

The FT-IR results of the as-prepared pure g-C3N4, SnS2 and SnS2/g-C3N4 nanocomposites are presented in Fig. 2. The FT-IR spectrum of g-C3N4 displays different characteristic peaks within the 800–1600 cm−1 region corresponding to various stretching and bending vibration modes of carbon–nitrogen (C–N) and nitrogen–carbon–nitrogen (N–C Created by potrace 1.16, written by Peter Selinger 2001-2019 N) bonds. A sharp and prominent peak around 810 cm−1 acts as a structural fingerprint for the individual symmetric stretching of triazine rings of g-C3N4. A weak and smaller peak at 887 cm−1 specifically attributed to the deformation mode of N–H bonds.90 The peaks observed between 1200 cm−1 and 1650 cm−1 are attributed to the aromatic heterocyclic stretching vibrations of C–N and C Created by potrace 1.16, written by Peter Selinger 2001-2019 N. Additionally, a broad peak in the 2800–3400 cm−1 region is generally due to the stretching vibrations of –NH groups. The FT-IR spectrum of SnS2 shows a broad peak around 520–625 cm−1 corresponding to Sn–S stretching vibrations.91 The FT-IR spectrum of SnS2/g-C3N4 primarily reflects the preserved structure of the g-C3N4 framework, with a subtle indication of the SnS2 presence; this is due to the amount of SnS2 being less. This indicates a strong interaction between g-C3N4 and SnS2 within the synthesized nanocomposite, which is also reflected in the XRD data.

Fig. 2. FT-IR spectra of pristine g-C3N4, pristine SnS2, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4, and 30% SnS2/g-C3N4.

Fig. 2

3.3. Optical characterization

3.3.1. UV-visible diffuse reflectance spectroscopy (UV-DRS)

Ultraviolet-Visible Diffuse Reflectance Spectroscopy (UV-DRS) for pristine g-C3N4, pristine SnS2 and SnS2/g-C3N4 nanocomposites was used to characterize their optical absorption properties (Fig. 3a) and determine their band gap energies (Fig. 3b). Pristine g-C3N4 exhibits a strong absorption edge at 450 nm and pristine SnS2 exhibits an absorption edge at 625 nm. After the introduction of SnS2, the optical absorption edge of g-C3N4/SnS2 typically shifts towards higher wavelength compared with pristine g-C3N4, and the absorption intensity in the visible region increases as the wt% of SnS2 increases.73 This shift can be attributed to the synergistic interaction between g-C3N4 and SnS2. Pristine g-C3N4 and pristine SnS2 have band gap energies of 2.79 eV and 2.13 eV, respectively. The SnS2/g-C3N4 nanocomposites exhibit band gap energies between 2.77 eV and 2.59 eV, as depicted in Table 2 and confirmed by the Tauc plot (Fig. 3b). This slight band gap narrowing suggests an enhanced ability to capture visible light in the SnS2/g-C3N4 nanocomposites.

Fig. 3. (a) UV-DRS spectra and (b) Tauc plot of pristine g-C3N4, pristine SnS2, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4, and 30% SnS2/g-C3N4.

Fig. 3

Table 2. The band gap, specific surface area, pore volume (BJH) and average pore radius of pristine SnS2, pristine g-C3N4, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4, and 30% SnS2/g-C3N4.
Sr. no. Catalyst name Band gap (eV) Specific surface area (m2 g−1) Pore volume BJH (cm3 g−1) Average pore radius (nm)
1 SnS2 2.13 31.1 0.06949 4.93
2 g-C3N4 2.79 26.1 0.10793 8.61
3 2.5% SnS2/g-C3N4 2.77 28.2 0.12276 9.05
4 5% SnS2/g-C3N4 2.75 30.9 0.13359 8.94
5 10% SnS2/g-C3N4 2.71 45.2 0.14866 7.36
6 20% SnS2/g-C3N4 2.64 47.3 0.15775 6.82
7 30% SnS2/g-C3N4 2.59 51.8 0.15863 6.52

3.3.2. Photoluminescence (PL) spectroscopy

Photoluminescence (PL) spectroscopy was employed to investigate the photoproduced charge carrier transfer and separation characteristics of pristine g-C3N4, pristine SnS2 and SnS2/g-C3N4 nanocomposites. PL emission intensity can reflect the recombination rate of photogenerated electrons and holes. A higher recombination rate of photogenerated electrons and holes leads to a higher PL intensity; in contrast, a weak PL emission intensity indicates a low recombination rate of photogenerated electrons and holes. Fig. 4 shows the PL spectra of pristine g-C3N4, pristine SnS2 and SnS2/g-C3N4 nanocomposites. The PL spectra revealed significant changes in PL intensity, as shown in Fig. 4. The strong emission peak of pristine g-C3N4, centred at 430 nm with an excitation wavelength of 350 nm, indicates a high recombination rate of photogenerated electron–hole pairs. The PL intensity of all SnS2/g-C3N4 nanocomposites exhibited significant quenching compared with that of pristine g-C3N4, indicating that the recombination rate of holes and electrons in the g-C3N4/SnS2 nanocomposites is low.92 This behaviour indicates that the formation of a heterojunction between g-C3N4 and SnS2 effectively suppresses the recombination of charge carriers. As a consequence, the photogenerated electron–hole pairs in the SnS2/g-C3N4 nanocomposite are efficiently separated, promoting rapid charge transfer across the heterostructure interface and thereby enhancing photocatalytic performance.

Fig. 4. Photoluminescence spectra of pristine g-C3N4, pristine SnS2, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4, and 30% SnS2/g-C3N4.

Fig. 4

3.3.3. Time-resolved photoluminescence (TRPL) spectroscopy analysis

The time resolved PL spectroscopy analysis was carried out to determine the lifetime of charge carriers, as shown in Fig. 5, fitted by the following biexponential model functions (eqn (1) and (2)).

R(t) = A1 exp{−t/τ1} + A2 exp{−t/τ2} 1
3.3.3. 2

where τ1 and τ2 are the decay times for the faster and slower components, and A1 and A2 are the PL amplitudes, respectively.

Fig. 5. Time-resolved photoluminescence spectra of pristine SnS2, pristine g-C3N4, and 10% SnS2/g-C3N4.

Fig. 5

The slow component (τ2) originates from the indirect formation of self-trapped excitations, whereas the fast component (τ1) corresponds to the direct formation of free electrons and holes. It has been noted that the lifetime of charge carriers for 10% SnS2/g-C3N4 is around 1.73 ns (shown in Table 1), higher than those of pristine SnS2 and g-C3N4. This higher τ1 gives more time for the photogenerated electrons and holes for further reaction. Furthermore, the lifetime of charge carriers for SnS2 and g-C3N4 is only 1.09 and 1.43 ns, respectively, resulting in slightly faster recombination of electron–hole pairs.

Table 1. Slow component (τ2) and fast component (τ1) observed in TRPL for prepared SnS2, g-C3N4 and 10% SnS2/g-C3N4.
Sr. no. Catalyst name τ 1 ns τ 2 ns
1 SnS2 1.09972 ± 0.00758 7.8665 ± 0.50062
2 g-C3N4 1.43267 ± 0.00975 6.66675 ± 0.12964
3 10% SnS2/g-C3N4 1.73129 ± 0.01073 6.59913 ± 0.13650

For pristine g-C3N4, the fitted parameters were A1 = 0.58811 and A2 = 0.04029, and for 10% SnS2/g-C3N4, the corresponding values were A1 = 0.56405 and A2 = 0.12984. By solving eqn (2), average lifetimes of approximately 2.70 ns and 4.01 ns were obtained for g-C3N4 and the 10% SnS2/g-C3N4 composite, respectively. Thus, the slow decay component decreases slightly from 6.67 to 6.60 ns, while the amplitude-weighted average lifetime increases by approximately 48.5% for the 10% SnS2/g-C3N4 composite. This increase indicates substantially modified charge-carrier recombination dynamics and is consistent with an improved carrier lifetime in the heterostructure.

3.4. Morphological and nanostructural analysis

3.4.1. FE-SEM analysis

The surface morphologies of the produced nanocomposites, pure SnS2 and g-C3N4 were studied by FE-SEM to check the distribution of SnS2 on the surface of g-C3N4, as shown in Fig. 6. Pristine SnS2 indicates the creation of hexagonal-shaped thin plates having a size of around 0.4 micron and an average plate thickness of around 10 to 20 nm. These quasi hexagonal SnS2 plates are oriented such that they appear like a rose blossom-like morphology, as illustrated in Fig. 6a and a′.93 Pristine g-C3N4 shows smooth, two dimensional, irregular layered sheets with a relatively featureless surface, as illustrated in Fig. 6b and b′.94 Inclusion of varied wt% of SnS2 on the g-C3N4 surface leads to a noticeable alteration with well-spread SnS2 hexagonal sheets all over the g-C3N4 surface (Fig. 6c–g). At lower concentrations, 2.5% SnS2 nanosheets (Fig. 6c and c′) and 5% SnS2 nanosheets (Fig. 6d and d′) are well dispersed, sparsely and uniformly, over the surface of g-C3N4. At these percentages, SnS2 already begins to add surface roughness to the smooth g-C3N4 layers. In the 10% SnS2/g-C3N4 nanocomposite, a dense and homogeneous deposition of SnS2 on the g-C3N4 nanosheets is observed, as illustrated in Fig. 6e and e′. The close contact between the two phases implies the creation of a strong interfacial heterojunction, which is important for efficient charge carrier separation. As the SnS2 content is increased to 20% and 30%, FE-SEM images indicate a high surface coverage, as illustrated in Fig. 6f, f′ and g, g′, respectively. While the nanocomposites keep their heterostructured nature, some clumps of SnS2 nanosheets are observed on the g-C3N4 surface, which may affect the overall active surface and reduce catalytic activity.

Fig. 6. FE-SEM images of (a and a′) pristine SnS2, (b and b′) pristine g-C3N4, (c and c′) 2.5% SnS2/g-C3N4, (d and d′) 5% SnS2/g-C3N4, (e and e′) 10% SnS2/g-C3N4, (f and f′) 20% SnS2/g-C3N4 and (g and g′) 30% SnS2/g-C3N4.

Fig. 6

3.4.2. FE-TEM analysis

The nanoscale morphology and interfacial properties of the prepared catalysts were elucidated using FE-TEM analysis. Fig. 7 shows the FE-TEM images of pristine g-C3N4, which exhibits a typical sheet-like morphology (Fig. 7a and b).92 The HR-TEM image of g-C3N4 (Fig. 7c) indicates a mostly low crystallinity polymeric network and shows the interplanar spacing d = 0.32 nm for the (002) plane of g-C3N4, which corresponds to the hazy diffuse concentric ring observed in its SAED pattern (Fig. 7d). The HAADF image for elemental mapping is shown in Fig. 7e and f. The TEM associated elemental mapping confirms the uniform distribution of C and N throughout the g-C3N4 nanosheet, as shown in Fig. 7g and h.

Fig. 7. FE-TEM images of prepared g-C3N4 nanosheets, (a and b) TEM images, (c) HR-TEM image, (d) SAED pattern, (e) HAADF image for elemental mapping and (f–h) TEM associated elemental mapping.

Fig. 7

Fig. 8 shows the FE-TEM images of pristine SnS2 with highly defined hexagonal-shaped plate-like architecture and a uniform surface (Fig. 8a and b). Fig. 8c is the HR-TEM image of SnS2, which exhibits parallel lattice fringes with interplanar spacings d = 0.28 nm and d = 0.339 nm, indexing to the (101) and (110) planes, respectively.92 The SAED profile (Fig. 8d) of SnS2 shows bright, distinct spots arranged in sharp concentric circles corresponding to the (101), (110) and (100) planes. The HAADF image for elemental mapping is shown in Fig. 8e. The TEM-associated elemental mapping (Fig. 8f–h) shows perfectly co-localized Sn and S.

Fig. 8. FE-TEM images of prepared SnS2 nanosheets, (a and b) TEM images, (c) HR-TEM image, (d) SAED pattern, (e) HAADF image for elemental mapping and (f–h) TEM-associated elemental mapping.

Fig. 8

The TEM analysis (Fig. 9) confirms that the 10 wt% loading results in a uniform distribution of SnS2 on the surface of g-C3N4 nanosheets. Fig. 9a and b clearly demonstrate the successful integration of hexagonal SnS2 plates with the g-C3N4 nanosheets. The HR-TEM image (Fig. 9c) reveals distinct lattice fringes of SnS2 in two randomly selected areas, with measured interplanar spacings of d = 0.28 nm and d = 0.339 nm, corresponding to the (101) and (100) planes of SnS2, respectively.73,92 The SAED image (Fig. 9d) displays a superimposed pattern showing the diffraction rings of crystalline SnS2 emerging over the faint, diffuse g-C3N4 substrate. The HAADF image for elemental mapping is shown in Fig. 9e. TEM-associated elemental mapping (Fig. 9f–i) shows C and N continuously across the entire background matrix, while Sn and S signals appear as isolated, smaller clusters distributed evenly over the matrix. Fig. S1 in the SI shows TEM-associated EDS spectra of g-C3N4, SnS2 and 10% SnS2/g-C3N4, confirming the existence of corresponding elements in the prepared catalysts. Overall, TEM analysis supports the XRD and FESEM analyses and confirms the formation of the SnS2/g-C3N4 heterojunction.

Fig. 9. FE-TEM images of the prepared 10% SnS2/g-C3N4 nanocomposite, (a and b) TEM images, (c) HR-TEM image, (d) SAED pattern, (e) HAADF image for elemental mapping and (f–i) TEM-associated elemental mapping.

Fig. 9

3.4.3. BET surface area analysis

The Brunauer–Emmett–Teller (BET) N2 adsorption–desorption analysis was carried out to determine the specific surface area (SBET) and corresponding pore structure. The SBET, average pore radius, pore size distribution, pore volume of pristine SnS2, pristine g-C3N4, and SnS2/g-C3N4 nanocomposites are depicted in Table 2. Fig. 10a shows the nitrogen sorption isotherm curves of pristine SnS2, pristine g-C3N4, and SnS2/g-C3N4 nanocomposites, which show a type IV isotherm, indicating the presence of mesoporous nature and a type H3 hysteresis loop.90 The SBET values of pristine SnS2, pristine g-C3N4, and the 10% SnS2/g-C3N4 nanocomposite are observed to be 31.1, 26.1 and 45.2 m2 g−1, respectively. In comparison with pristine g-C3N4, the SBET of SnS2/g-C3N4 nanocomposites increases due to the introduction of SnS2 and may be due to its layered structure, which can offers ample surface active sites during the photocatalytic process. The pore size analysis of pristine SnS2, pristine g-C3N4, and SnS2/g-C3N4 nanocomposites (Fig. 10b) shows varying pore levels. The prepared materials have a pore diameter below 15 nm, with a maximum diameter of around 7 nm, indicating that they are mesoporous in nature.

Fig. 10. (a) BET N2 gas adsorption–desorption isotherm curve and (b) BJH pore size distribution curves of pristine SnS2, pristine g-C3N4, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4, and 30% SnS2/g-C3N4.

Fig. 10

3.5. X-ray photoelectron study

X-ray photoelectron spectroscopy (XPS) was employed to investigate the surface chemical composition and binding energies of prepared photocatalysts, as shown in Fig. 11. In the survey scan spectrum of pristine g-C3N4 (Fig. 11a), two distinct peaks were detected at binding energies of around 288 and 399 eV due to C 1s and N 1s, respectively. The high resolution spectrum of C 1s (Fig. 11b) for pristine g-C3N4 was well deconvoluted into two peaks at 284.5 and 287.9 eV, which are related to the C–C and N–C Created by potrace 1.16, written by Peter Selinger 2001-2019 N functional group, respectively.95 The high resolution deconvoluted spectra of N 1s (Fig. 11c) show three main peaks at 398.3, 399.0 and 400.5 eV, corresponding to the C–N Created by potrace 1.16, written by Peter Selinger 2001-2019 C, C–N–C and N–H functional groups, respectively. The survey scan XPS spectrum of pristine SnS2 (Fig. 11d) shows distinct peaks for Sn and S. The high resolution deconvoluted spectrum of Sn 3d for pristine SnS2 (Fig. 11e) shows two main peaks at 486.7 and 495.1 eV, assigned to Sn 3d5/2 and Sn 3d3/2, respectively. The high resolution deconvoluted spectrum of S 2p for pristine SnS2 (Fig. 11f) shows two main peaks at 161.6 and 162.7 eV, assigned to S 2p3/2 and S 2p1/2, respectively.88 The survey scan XPS spectrum of the 10% SnS2/g-C3N4 nanocomposite (Fig. 11g) shows several characteristic peaks related to Sn 3d, S 2p, C 1s and N 1s, which confirms the presence of Sn, S, C and N in the prepared nanocomposite. Fig. 11h–k represents the corresponding high resolution deconvoluted XPS spectrum of Sn 3d, S 2p, C 1s and N 1s for the 10% SnS2/g-C3N4 nanocomposite. The deconvoluted Sn 3d spectrum (Fig. 11h) shows two main peaks at 486.3 and 494.8 eV, corresponding to Sn 3d5/2 and Sn 3d3/2, respectively. The deconvoluted S 2p spectrum (Fig. 11i) shows two main peaks at 160.9 and 161.9 eV, corresponding to S 2p3/2 and S 2p1/2, respectively. The deconvoluted C 1s spectrum (Fig. 11j) shows two main peaks at 284.5 and 288.1 eV, corresponding to C–C and N–C Created by potrace 1.16, written by Peter Selinger 2001-2019 N, respectively, and the deconvoluted N 1s spectrum (Fig. 11k) shows three main peaks at 398.5, 399.2 and 400.7 eV, corresponding to the C–N Created by potrace 1.16, written by Peter Selinger 2001-2019 C, C–N–C and N–H functional groups, respectively. In comparison with the pristine SnS2 and pristine g-C3N4, the XPS peaks of Sn 3d and S 2p in the 10% SnS2/g-C3N4 nanocomposite shifts to slightly lower binding energies, while the XPS peaks of C 1s and N 1s in the 10% SnS2/g-C3N4 nanocomposite shift to slightly higher binding energy values, which is probably due to the transfer of electrons between g-C3N4 and SnS2 after the formation of the SnS2/g-C3N4 heterojunction nanocomposite.95,96Fig. 12 displays the XPS valence band spectra of SnS2 and g-C3N4, respectively. The valence band maximum edge was predicted to be ∼1.77 and ∼1.46 eV for SnS2 and g-C3N4, respectively. The band gaps of these samples are known from the Tauc plot (Fig. 3b), and we can thus compute the conduction band minima. The conduction band minimum for SnS2 is ∼−0.36 eV and for g-C3N4 is about −1.33 eV. The valence band maximum of g-C3N4 is more positive than that of SnS2, and its conduction band is more negative. The band locations are aligned, so electrons transfer from g-C3N4 to SnS2, and a heterojunction can be created at the interface. This could boost the charge carrier separation efficiency of the SnS2/g-C3N4 nanocomposite heterojunction and hence improve the overall efficiency.

Fig. 11. Survey XPS spectra of (a) g-C3N4, (d) SnS2 and (g) 10% SnS2/g-C3N4, high resolution XPS spectra of (b) C 1s and (c) N 1s of g-C3N4, (e) Sn 3d and (f) S 2p of SnS2, and high resolution XPS spectra of (h) Sn 3d, (i) S 2p, (j) C 1s and (k) N 1s of 10% SnS2/g-C3N4.

Fig. 11

Fig. 12. XPS valence band spectra of (a) SnS2 and (b) g-C3N4.

Fig. 12

3.6. Photocatalytic activity measurements

The photocatalytic activity of pristine SnS2, pristine g-C3N4 and SnS2/g-C3N4 nanocomposites were investigated by H2 evolution under a 400 W mercury vapour lamp. The H2 generation performance of as-prepared pristine SnS2, pristine g-C3N4 and SnS2/g-C3N4 nanocomposites with different wt% of SnS2 loaded is shown in Fig. 13. Among the prepared composites, the 10% SnS2/g-C3N4 composite showed the highest H2 generation of around 1094.7 µmol 0.1 g−1 within four hours of irradiation time. As shown in Table 3, the SnS2/g-C3N4 with SnS2 amounts of 2.5%, 5%, 20%, and 30%, pristine SnS2, and pristine g-C3N4 generated 860.2 µmol, 910.2 µmol, 939.6 µmol, 719.4 µmol, 501.9 µmol and 654.2 µmol of hydrogen per 0.1 g of catalyst, respectively. The SnS2/g-C3N4 nanocomposite with 10 wt% of SnS2 showed almost 1.67 times higher photocatalytic activity as compared to pristine g-C3N4. The highest photocatalytic activity towards H2 generation is due to effective electron–hole (e−/h+) pair separation. When the wt% of SnS2 exceeds 10%, SnS2 covers the effective surface area of the g-C3N4 nanosheets. Although the BET surface area increased with increasing SnS2 loading (Table 2), the photocatalytic H2 evolution did not increase proportionally. This indicates that the decrease in H2 evolution at higher SnS2 loading cannot be explained by surface area alone. The UV-vis diffuse reflectance spectra (Fig. 3a) of the composites with different SnS2 contents show a progressive modification of the optical response with increasing SnS2 loading, indicating increased optical attenuation within the composite. At excessive SnS2 loading, the increased fraction of SnS2 can partially shield the underlying g-C3N4 and reduce the effective utilization of incident photons. Consequently, the enhanced surface area of the 20% and 30% composites does not compensate for the adverse effects associated with reduced effective light utilization and less efficient charge separation. The superior H2 evolution observed for 10% SnS2/g-C3N4 therefore reflects an optimum balance between accessible surface area, light absorption, interfacial charge separation, and active-site availability. To further compare photocatalytic performance, the % Apparent Quantum Efficiency (AQE) was calculated (Table 3), showing an AQE of around 1.77% for the 10% SnS2/g-C3N4 nanocomposite. The 1.77% polychromatic AQE appears lower than monochromatic benchmarks due to the inclusion of unabsorbed visible/IR flux, but this is considered in the calculation in the denominator, a limitation commonly noted in full-spectrum studies. Therefore, this value represents efficient utilization of the full, unfiltered spectrum. The comparison in the SI (Table S2) demonstrates how the choice of light source, filtering, and the spectral range affects the % AQE. Table S1 in the SI represents a comparison of the photocatalytic performance of various representative photocatalysts for H2 generation via water splitting. Also, Table S3 in the SI summarizes a comparison of the present SnS2/g-C3N4 photocatalyst with representative recently reported SnS2/g-C3N4-based systems. The comparison includes the synthesis method, irradiation conditions, H2 evolution rate, and AQE, where available. For the reported systems, their major advantages are highlighted, while for the present work, both the key advantages and limitations are discussed to provide a balanced assessment. The nanocomposite described in this study showed the outstanding performance.

Fig. 13. Photocatalytic H2 generation using pristine SnS2, pristine g-C3N4, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4 and 30% SnS2/g-C3N4.

Fig. 13

Table 3. The amount of hydrogen generation and apparent quantum efficiency of prepared nanostructures.

Sr. no. Catalyst name H2 generation (µmol 0.1 g−1) % [AQE]38,97
1 SnS2 501.9 0.81
2 g-C3N4 654.2 1.06
3 2.5% SnS2/g-C3N4 860.2 1.39
4 5% SnS2/g-C3N4 910.2 1.47
5 10% SnS2/g-C3N4 1094.7 1.77
6 20% SnS2/g-C3N4 939.6 1.52
7 30% SnS2/g-C3N4 719.4 1.19

3.7. Recyclability of the hydrogen generation behaviour

A crucial parameter for determining the stability and reusability of the catalyst is its recycling performance. For this purpose, the 10% SnS2/g-C3N4 nanocomposite, which exhibits higher photocatalytic activity, was recycled three times for H2 generation (SI, Fig. S2). After each cycle, the catalyst was separated from the suspension by centrifugation, washed with deionised water and ethanol, dried and reused for the next cycle. It was observed that the catalytic activity of the 10% SnS2/g-C3N4 nanocomposite did not exhibit any significant loss after the second and third cycles. After the third cycle, the amount of H2 generated was approximately 1079.1 µmol 0.1 g−1 of recycled catalyst, indicating the high stability of the catalyst towards hydrogen generation. There are no any structural changes seen in the reused catalyst examination by XRD (SI, Fig. S3), but shows slight sharpening of the XRD peak around 2θ = 28°. This is due to slight structural fragmentation induced by continuous mechanical stirring and sample processing during multi-cycle photocatalytic reaction run rather than phase transformation or SnS2 crystallite growth during the photocatalytic reaction. Corresponding Scherrer crystallite size calculations are given in the SI (S1), clearly indicating the good stability of the catalyst.

3.8. Mechanism of photocatalytic H2 generation

Fig. 14 represents the potential photocatalytic mechanism of the charge transport process in the 10% SnS2/g-C3N4 nanocomposite, which showed the highest photocatalytic H2 generation. g-C3N4 has a band gap of 2.79 eV, and SnS2 has a band gap of 2.13 eV (Fig. 3b). On the basis of the energy band structures and XPS valence band spectra (Fig. 12) of these two semiconductors, we propose that the photoinduced electrons transfer from the conduction band (CB) of g-C3N4 to the CB of SnS2 nanosheets because the CB potential of g-C3N4 nanosheets (∼−1.33 V vs. NHE) is more negative than that of SnS2 nanosheets (∼−0.36 V vs. NHE). As a result of effective electron transfer from g-C3N4 to SnS2 nanosheets, the photoinduced holes on the valence band (VB) of SnS2 nanosheets (∼+1.77 V vs. NHE) would transfer to the VB of g-C3N4 (∼+1.46 V vs. NHE) and are consumed by the sacrificial agent at the heterojunction interface.88,96 In this work, methanol and a S2−/SO32− mixture were employed as sacrificial reagents. The concurrent application of an organic alcohol (methanol) with an inorganic sulfur-based redox pair (Na2S/Na2SO3) was meticulously designed to enhance lattice stabilization and promote synergistic hole-scavenging dynamics. Transition metal sulfide catalysts such as SnS2 have significant susceptibility to anodic photocorrosion when subjected to intense visible light, as the buildup of photogenerated holes leads to the oxidation of surface sulfide anions (S2−) into elemental sulfur, thereby compromising the integrity of the host crystal lattice. The inorganic Na2S/Na2SO3 combination establishes a robust localized sacrificial loop; the highly reducing S2− ions swiftly capture entering holes at the SnS2 valence band edge, while SO32− co-ions methodically revert intermediate polysulfides to monomeric forms, maintaining the structural integrity. Simultaneously, methanol functions as a highly mobile organic absorbent. This integrated binary scavenger matrix enhances the total extraction of holes in both components, significantly reducing interfacial charge-transfer resistance and maximizing the availability of long-lived photoelectrons for proton reduction. Furthermore, the deposition of Pt as a co-catalyst on the SnS2/g-C3N4 heterojunction facilitates charge separation by suppressing electron–hole recombination, which in turn improves photocatalytic H2 generation.40 Additionally, electrochemical impedance spectra (EIS) of pristine SnS2, pristine g-C3N4, and 10% SnS2/g-C3N4 samples provided crucial insights into the charge transfer dynamics within the prepared materials. The constructed 10% SnS2/g-C3N4 heterojunction follows a typical type-II staggered band alignment. Upon simulated light irradiation, both components are excited to generate photogenerated carriers. Pristine g-C3N4 possesses a conduction band (CB) at −1.33 V and a valence band (VB) at +1.46 V vs. NHE (based on an experimental Eg of 2.79 eV). Pristine SnS2 exhibits a CB at −0.36 V and a VB at +1.77 V vs. NHE (derived from an experimental Eg of 2.13 eV). Due to the significant potential gradient between the CB of g-C3N4 and SnS2, a strong internal driving force of ∼0.97 V is established. This large energy cascade prompts the photogenerated electrons to rapidly flow in a directional manner from the g-C3N4 matrix onto the SnS2 nanoplates. This highly fluent, energetically favourable channel corresponds perfectly to the drastically diminished interfacial charge-transfer resistance (Rct) observed in the frequency-domain EIS spectra (Fig. S4). Consequently, the accumulated electrons on the SnS2 CB efficiently reduce protons into H2 gas, while spatial separation drastically retards radiative recombination.91,96

Fig. 14. Proposed mechanism of photocatalytic hydrogen evolution by SnS2/g-C3N4.

Fig. 14

3.9. Photoconductivity measurement

Photoconductivity measurements of pristine SnS2, pristine g-C3N4, and SnS2/g-C3N4 nanocomposites were performed in air at room temperature with a bias voltage from −5 V to +5 V under the illumination of solar simulator light to record the photo-induced effect. The I–V characteristics for pristine SnS2, pristine g-C3N4, and SnS2/g-C3N4 nanocomposites under light as well as in the dark are shown in Fig. 15 and SI (Fig. S5), respectively. Under the illumination of solar simulator light, linear changes in photocurrent are observed in pristine SnS2, pristine g-C3N4 and SnS2/g-C3N4 nanocomposites. As the wt% of SnS2 increases, the photocurrent also increases up to 10% SnS2 concentration and then decreases. The 10% SnS2/g-C3N4 shows highest photocurrent, 12.67 × 10−8 A, compared with that of pristine SnS2 (4.99 × 10−8 A), pristine g-C3N4 (5.80 × 10−8 A) and other SnS2/g-C3N4 nanocomposites. The enhanced photocurrent response under illumination indicates improved photoinduced charge-carrier generation and transport in the SnS2/g-C3N4 heterostructure. This observation provides complementary evidence for the enhanced photocatalytic behaviour, although the photocurrent measurements were performed under AM 1.5G irradiation whereas H2 evolution was evaluated under a 400 W Hg lamp.

Fig. 15. Current–voltage characteristics of pristine SnS2, pristine g-C3N4, 2.5% SnS2/g-C3N4, 5% SnS2/g-C3N4, 10% SnS2/g-C3N4, 20% SnS2/g-C3N4 and 30% SnS2/g-C3N4.

Fig. 15

The results are clearly consistent with the enhancement in photocatalytic performance.

4. Conclusion

In this study, an in situ hydrothermal method was effectively used to synthesize a series of SnS2/g-C3N4 heterojunction photocatalysts with different wt% of SnS2 for hydrogen generation via water splitting. The effective production of the SnS2/g-C3N4 heterojunction was validated by comprehensive structural, optical and morphological characterization techniques. Among the prepared photocatalysts, the 10% SnS2/g-C3N4 heterojunction showed higher photocatalytic performance than the other prepared samples. The optimum composition provides a vital balance, offering sufficient catalytically active sites and providing an efficient heterojunction interface to inhibit the charge carrier recombination. The efficient charge separation in 10% SnS2/g-C3N4, which leads to the enhanced photocatalytic activity, is also supported by the photoconductivity investigation. However, greater loadings of 20% and 30% SnS2 reduced the photocatalytic activity. These results highlight the crucial relevance of accurate composition control in heterojunction engineering and position the optimized 10% SnS2/g-C3N4 nanocomposite as a very promising material for scalable, solar-driven hydrogen production.

Author contributions

A. G. K. performed the experimental work, characterized the data, and prepared the original draft of the manuscript. N. S. J. analyzed the data and modified the manuscript. S. C. M. helped in data interpretation and critical revision of the manuscript text. G. G. U. provided the electrochemical analysis support. K. D. D. performed TRPL analysis. J. D. A. performed FE-SEM analysis, and S. S. A. provided the concept and methodology, analyzed the data, supervised the work, validated the results and reviewed the manuscript.

Conflicts of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary Material

NA-OLF-D6NA00434B-s001

Acknowledgments

AGK is grateful to Dr M. V. Kulkarni, Director, C-MET, Pune, Dr S. B. Rane, Senior Scientist, C-MET, Pune, and the Principal of S. N. Arts, D. J. Malpani Commerce and B. N. Sarda Science College, Sangamaner, Maharashtra, India, for providing the permission and necessary help for this research work. AGK is thankful to the CSIF, BITS Pilani, Goa, for FE-TEM analysis and SAIF, Chandigarh, for XPS valence band analysis on a paid basis.

Data availability

The data are with the corresponding author and will be made available upon request.

Supplementary information (SI): comparison of the photocatalytic performance for the H2 generation with other photocatalysts, TEM-associated EDS spectra, catalyst recycling study and current–voltage characteristics in the dark. See DOI: https://doi.org/10.1039/d6na00434b.

References

  1. Aravindan M. Madhan K. V. Hariharan V. S. Narahari T. Arun K. P. Madhesh K. Praveen K. G. Prabakaran R. Renewable Sustainable Energy Rev. 2023;188:113791. doi: 10.1016/j.rser.2023.113791. [DOI] [Google Scholar]
  2. Tong R. Ng K. W. Wang X. Wang S. Wang X. Pan H. J. Mater. Chem. A. 2020;8:23202–23230. doi: 10.1039/D0TA08045D. [DOI] [Google Scholar]
  3. Mehtab A. Ali S. A. Sadiq I. Shaheen S. Khan H. Fazil M. Pandit N. A. Naaz F. Ahmad T. ACS Sustainable Resour. Manage. 2024;1:604–620. doi: 10.1021/acssusresmgt.4c00039. [DOI] [Google Scholar]
  4. Gayen D. Chatterjee R. Roy S. Int. J. Environ. Sci. Technol. 2024;21:5285–5310. doi: 10.1007/s13762-023-05380-z. [DOI] [Google Scholar]
  5. Dutta T. Chaturvedi P. Thakur A. Mishra S. K. Energy Fuels. 2025;39:8827–8870. doi: 10.1021/acs.energyfuels.5c00967. [DOI] [Google Scholar]
  6. Ibrahim R. L. Environ. Sci. Pollut. Res. 2022;29:87568–87582. doi: 10.1007/s11356-022-21872-w. [DOI] [PubMed] [Google Scholar]
  7. Gürsan C. De Gooyert V. Renewable Sustainable Energy Rev. 2021;138:110552. doi: 10.1016/j.rser.2020.110552. [DOI] [Google Scholar]
  8. Xu J. Fu C. Yuan Z. Chen Z. Zhao H. Adv. Energy Mater. 2026:e70941. doi: 10.1002/aenm.70941. [DOI] [Google Scholar]
  9. Li F. Zhu G. Jiang J. Yang L. Deng F. Arramel Li X. J. Mater. Sci. Technol. 2024;177:142–180. doi: 10.1016/j.jmst.2023.08.038. [DOI] [Google Scholar]
  10. Pietrosemoli L. Rodríguez-Monroy C. Renewable Sustainable Energy Rev. 2019;105:415–426. doi: 10.1016/j.rser.2019.02.014. [DOI] [Google Scholar]
  11. Hassan Q. Viktor P. Al-Musawi T. J. Mahmood Ali B. Algburi S. Alzoubi H. M. Khudhair Al-Jiboory A. Zuhair Sameen A. Salman H. M. Jaszczur M. Renew. Energy Focus. 2024;48:100545. doi: 10.1016/j.ref.2024.100545. [DOI] [Google Scholar]
  12. Gielen D. Boshell F. Saygin D. Bazilian M. D. Wagner N. Gorini R. Energy Strategy Rev. 2019;24:38–50. doi: 10.1016/j.esr.2019.01.006. [DOI] [Google Scholar]
  13. Jeje S. O. Marazani T. Obiko J. O. Shongwe M. B. Int. J. Hydrogen Energy. 2024;78:642–661. doi: 10.1016/j.ijhydene.2024.06.344. [DOI] [Google Scholar]
  14. Algarni S. Tirth V. Alqahtani T. Alshehery S. Kshirsagar P. Sustainable Energy Technol. Assess. 2023;56:103098. doi: 10.1016/j.seta.2023.103098. [DOI] [Google Scholar]
  15. Ali S. A. Ahmad T. Int. J. Hydrogen Energy. 2022;47:29255–29283. doi: 10.1016/j.ijhydene.2022.06.269. [DOI] [Google Scholar]
  16. Tüysüz H. Acc. Chem. Res. 2024;57(4):558–567. doi: 10.1021/acs.accounts.3c00709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Lam S. S. Nguyen V.-H. Nguyen Dinh M. T. Khieu D. Q. La D. D. Nguyen H. T. Vo D. V. N. Xia C. Varma R. S. Shokouhimehr M. Nguyen C. C. Le Q. V. Peng W. J. Mater. Chem. A. 2020;8:10571–10603. doi: 10.1039/D0TA02582H. [DOI] [Google Scholar]
  18. Hosseini S. E. Butler B. Int. J. Green Energy. 2020;17:13–37. doi: 10.1080/15435075.2019.1685999. [DOI] [Google Scholar]
  19. Ganguly P. Harb M. Cao Z. Cavallo L. Breen A. Dervin S. Dionysiou D. D. Pillai S. C. ACS Energy Lett. 2019;4:1687–1709. doi: 10.1021/acsenergylett.9b00940. [DOI] [Google Scholar]
  20. Christoforidis K. C. Fornasiero P. ChemCatChem. 2017;9:1523–1544. doi: 10.1002/cctc.201601659. [DOI] [Google Scholar]
  21. Tee S. Y. Win K. Y. Teo W. S. Koh L. Liu S. Teng C. P. Han M. Adv. Sci. 2017;4:1600337. doi: 10.1002/advs.201600337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kumar T. Singh R. P. Wankhade A. V. Adv. Sustainable Syst. 2025:2400984. [Google Scholar]
  23. Blanco H. Faaij A. Renewable Sustainable Energy Rev. 2018;81:1049–1086. doi: 10.1016/j.rser.2017.07.062. [DOI] [Google Scholar]
  24. Wang J. Jiang J. Li F. Zou J. Xiang K. Wang H. Li Y. Li X. Green Chem. 2023;25:32–58. doi: 10.1039/D2GC03160D. [DOI] [Google Scholar]
  25. Fujishima A. Honda K. Nature. 1972;238:37–38. doi: 10.1038/238037a0. [DOI] [PubMed] [Google Scholar]
  26. Wang H. Yu L. Peng J. Zou J. Jiang J. J. Mater. Sci. Technol. 2025;208:111–119. doi: 10.1016/j.jmst.2024.05.005. [DOI] [Google Scholar]
  27. Cui E. Lu Y. Li Z. Chen Z. Ge C. Jiang J. Chin. Chem. Lett. 2025;36:110288. doi: 10.1016/j.cclet.2024.110288. [DOI] [Google Scholar]
  28. Jin Z. Yang C. Li L. Jiang J. J. Ind. Eng. Chem. 2025;142:449–462. doi: 10.1016/j.jiec.2024.07.052. [DOI] [Google Scholar]
  29. Grabowska-Musiał E. Drzeżdżon J. Jacewicz D. Int. J. Hydrogen Energy. 2025;158:150545. doi: 10.1016/j.ijhydene.2025.150545. [DOI] [Google Scholar]
  30. Dash S. K. Chakraborty S. Elangovan D. Energies. 2023;16:1141. doi: 10.3390/en16031141. [DOI] [Google Scholar]
  31. Rafique M. Hajra S. Irshad M. Usman M. Imran M. Assiri M. A. Ashraf W. M. ACS Omega. 2023;8:25640–25648. doi: 10.1021/acsomega.3c00963. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Bozheyev F. Nemkayeva R. Yerlanuly Y. Gabdullin M. Markhabayeva A. ACS Catal. 2025;15:16449–16462. doi: 10.1021/acscatal.5c03869. [DOI] [Google Scholar]
  33. Thennarasu G. Rajendran S. Kalairaj A. Rathore H. S. Panda R. C. Senthilvelan T. Clean Technol. Environ. Policy. 2025;27:495–516. doi: 10.1007/s10098-024-02960-6. [DOI] [Google Scholar]
  34. Rana P. Soni V. Kumar R. Sonu Chawla A. Parwaz Khan A. A. Singh P. Thakur S. Raizada P. Alzahrani K. A. Fuel. 2025;386:134286. doi: 10.1016/j.fuel.2025.134286. [DOI] [Google Scholar]
  35. Aldosari O. F. Catal. Rev. 2025:1–38. [Google Scholar]
  36. Piracha S. Batool S. Zhang Y. Miao Y.-X. Li G. Hasan M. J. Mater. Sci. 2025;60:5721–5748. doi: 10.1007/s10853-025-10808-7. [DOI] [Google Scholar]
  37. Birla P. N. Arbuj S. S. Chauhan R. Shinde M. D. Rane S. B. Gosawi S. W. Kale B. B. Int. J. Hydrogen Energy. 2025;172:151210. doi: 10.1016/j.ijhydene.2025.151210. [DOI] [Google Scholar]
  38. Yadav N. S. Jawale N. S. Umarji G. G. Damkale S. R. Rane S. B. Arbuj S. S. ACS Appl. Energy Mater. 2025;8:3035–3047. doi: 10.1021/acsaem.4c03179. [DOI] [Google Scholar]
  39. Jawale N. Umarji G. Damkale S. Arbuj S. Next Energy. 2025;6:100205. doi: 10.1016/j.nxener.2024.100205. [DOI] [Google Scholar]
  40. Jawale N. S. Arbuj S. S. Umarji G. G. Rane S. B. ACS Appl. Energy Mater. 2024;7:10877–10887. doi: 10.1021/acsaem.4c01724. [DOI] [Google Scholar]
  41. Verma M. Verma N. Servottam S. B R. P. John N. S. Phys. Chem. Chem. Phys. 2025;27:12963–12978. doi: 10.1039/D5CP00741K. [DOI] [PubMed] [Google Scholar]
  42. Chanda N. Jaksani B. Saha S. Singh A. Joshi H. Sharma N. Pakhira S. Pal U. Ahmadipour M. Int. J. Hydrogen Energy. 2025;140:36–44. doi: 10.1016/j.ijhydene.2025.05.318. [DOI] [Google Scholar]
  43. Chávez-Caiza J. Navlani-García M. Fernández-Catalá J. Bhardwaj A. Lousada C. M. Belova L. M. Berenguer-Murcia Á. Cazorla-Amorós D. Catal. Today. 2025;453:115273. doi: 10.1016/j.cattod.2025.115273. [DOI] [Google Scholar]
  44. Kadlag A. G. Jawale N. S. Tambe A. B. Umarji G. G. Kanade C. K. Lonkar S. P. Motekar S. C. Arbuj S. S. Int. J. Hydrogen Energy. 2026;197:152301. doi: 10.1016/j.ijhydene.2025.152301. [DOI] [Google Scholar]
  45. Zhao H. Fu H. Yang X. Xiong S. Han D. An X. Int. J. Hydrogen Energy. 2022;47:8247–8260. doi: 10.1016/j.ijhydene.2021.12.171. [DOI] [Google Scholar]
  46. Chen P. Liu F. Ding H. Chen S. Chen L. Li Y.-J. Au C.-T. Yin S.-F. Appl. Catal., B. 2019;252:33–40. doi: 10.1016/j.apcatb.2019.04.006. [DOI] [Google Scholar]
  47. Fan Z. Guo X. Jin Z. Li X. Li Y. Langmuir. 2022;38:3244–3256. doi: 10.1021/acs.langmuir.1c03379. [DOI] [PubMed] [Google Scholar]
  48. Jin Z. Li H. Li J. Chin. J. Catal. 2022;43:303–315. doi: 10.1016/S1872-2067(21)63818-4. [DOI] [Google Scholar]
  49. Tayebi M. Lee B.-K. Renewable Sustainable Energy Rev. 2019;111:332–343. doi: 10.1016/j.rser.2019.05.030. [DOI] [Google Scholar]
  50. Samsudin M. F. R. Ullah H. Bashiri R. Mohamed N. M. Sufian S. Ng Y. H. ACS Sustainable Chem. Eng. 2020;8:9393–9403. doi: 10.1021/acssuschemeng.0c02063. [DOI] [Google Scholar]
  51. Liu L. Zhao S. Ji Y. Wang Z. J. Alloys Compd. 2025;1034:181366. doi: 10.1016/j.jallcom.2025.181366. [DOI] [Google Scholar]
  52. Meng A. Li J. Cao Q. Li Z. Li W. Li Z. Zhang J. Fu J. Chem. Res. Chin. Univ. 2025;41:790–798. doi: 10.1007/s40242-025-5081-1. [DOI] [Google Scholar]
  53. Wang J. Wei Y. Zhang B.-H. Huang W. Yang K. Lu K.-Q. J. Mater. Chem. A. 2025;13(46):39488–39509. doi: 10.1039/D5TA06861D. [DOI] [Google Scholar]
  54. Yang M. Zhan X.-Q. Ou D.-L. Wang L. Zhao L.-L. Yang H.-L. Liao Z.-Y. Yang W.-Y. Ma G.-Z. Hou H.-L. Rare Met. 2025;44:1024–1041. doi: 10.1007/s12598-024-02979-0. [DOI] [Google Scholar]
  55. Du J. Liu L. Wang Y. Liu C. Yu S. Xue Y. Liu Q. Wu K. Catal. Lett. 2025;155:221. doi: 10.1007/s10562-025-05053-1. [DOI] [Google Scholar]
  56. Hisatomi T. Yamada T. Nishiyama H. Takata T. Domen K. Nat. Rev. Mater. 2025;10:769–782. doi: 10.1038/s41578-025-00823-0. [DOI] [Google Scholar]
  57. Jia Y. Xu L. Chen J. Zeng Y. Duan Z. Liu T. Liu X. J. Phys. Chem. C. 2025;129:13244–13254. doi: 10.1021/acs.jpcc.5c03590. [DOI] [Google Scholar]
  58. Le Y. T. H. Maček Kržmanc M. Yeh C.-L. Yu W.-Y. Wu J. C. S. Sol. Energy Mater. Sol. Cells. 2026;303:114389. doi: 10.1016/j.solmat.2026.114389. [DOI] [Google Scholar]
  59. Raj K. Jhala R. Sujai S. Pattanayak B. Singh J. Kumar P. Kaladhar M. Singh R. Bisht Y. Gautam A. J. Mol. Struct. 2026;1349:143534. doi: 10.1016/j.molstruc.2025.143534. [DOI] [Google Scholar]
  60. Tambe A. B. Jawale N. S. Arbuj S. S. Umarji G. G. Kadari R. Kulkarni S. Kale B. B. Langmuir. 2025;41:15892–15908. doi: 10.1021/acs.langmuir.5c00719. [DOI] [PubMed] [Google Scholar]
  61. Tambe A. B. Arbuj S. S. Umarji G. G. Kulkarni S. K. Kale B. B. RSC Adv. 2023;13:35369–35378. doi: 10.1039/D3RA07321A. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Gong H. Li Y. Li H. Jin Z. Langmuir. 2022;38:2117–2131. doi: 10.1021/acs.langmuir.1c03198. [DOI] [PubMed] [Google Scholar]
  63. Umaru D. Hafeez H. Y. Mohammed J. Suleiman A. B. Ndikilar C. E. Zakariyya Y. J. Alloys Compd. Commun. 2025;6:100058. [Google Scholar]
  64. Sun Z. Zhu M. Lv X. Liu Y. Shi C. Dai Y. Wang A. Majima T. Appl. Catal., B. 2019;246:330–336. doi: 10.1016/j.apcatb.2019.01.072. [DOI] [Google Scholar]
  65. Jiang J. Yu L. Peng J. Gong W. Sun W. Carbon Lett. 2025;35:417–440. doi: 10.1007/s42823-024-00853-8. [DOI] [Google Scholar]
  66. Lee S. Lee Y. Abbas H. G. Ji S. Kim S. Y. Lee K. Li S. Lee E. J. Choi J. Ahn H. Kim I. Y. In S.-I. Ringe S. Jang Y. J. Yang J. Nano Lett. 2025;25:7351–7360. doi: 10.1021/acs.nanolett.5c00529. [DOI] [PubMed] [Google Scholar]
  67. Chandrasekaran S. Yao L. Deng L. Bowen C. Zhang Y. Chen S. Lin Z. Peng F. Zhang P. Chem. Soc. Rev. 2019;48:4178–4280. doi: 10.1039/C8CS00664D. [DOI] [PubMed] [Google Scholar]
  68. Aslam A. Nadeem N. Balgabayeva B. Khan S. U. Abbas Q. Noreen S. Zahid M. Supiyeva Z. Inorg. Chem. Commun. 2025;181:115191. doi: 10.1016/j.inoche.2025.115191. [DOI] [Google Scholar]
  69. Deng F. Zhao L. Pei X. Luo X. Luo S. Mater. Chem. Phys. 2017;189:169–175. doi: 10.1016/j.matchemphys.2016.12.028. [DOI] [Google Scholar]
  70. Cao Q. Che R. Chen N. Appl. Catal., B. 2015;162:187–195. doi: 10.1016/j.apcatb.2014.06.052. [DOI] [Google Scholar]
  71. Du W. Deng D. Han Z. Xiao W. Bian C. Qian X. CrystEngComm. 2011;13:2071. doi: 10.1039/C0CE00596G. [DOI] [Google Scholar]
  72. Zhang Y. C. Du Z. N. Li S. Y. Zhang M. Appl. Catal., B. 2010;95:153–159. doi: 10.1016/j.apcatb.2009.12.022. [DOI] [Google Scholar]
  73. Liu E. Chen J. Ma Y. Feng J. Jia J. Fan J. Hu X. J. Colloid Interface Sci. 2018;524:313–324. doi: 10.1016/j.jcis.2018.04.038. [DOI] [PubMed] [Google Scholar]
  74. Taufik A. Saleh R. Seong G. Nanoscale. 2024;16:9680–9709. doi: 10.1039/D4NR00706A. [DOI] [PubMed] [Google Scholar]
  75. Carl N. Fiaz M. Oh H.-S. Kim Y.-K. Catalysts. 2024;14:442. doi: 10.3390/catal14070442. [DOI] [Google Scholar]
  76. Ong W.-J. Tan L.-L. Ng Y. H. Yong S.-T. Chai S.-P. Chem. Rev. 2016;116:7159–7329. doi: 10.1021/acs.chemrev.6b00075. [DOI] [PubMed] [Google Scholar]
  77. Putri L. K. Ng B.-J. Ong W.-J. Lee H. W. Chang W. S. Chai S.-P. J. Mater. Chem. A. 2018;6:3181–3194. doi: 10.1039/C7TA09723A. [DOI] [Google Scholar]
  78. Hou H. Shao G. Yang W. J. Mater. Chem. A. 2021;9:13722–13745. doi: 10.1039/D1TA02527A. [DOI] [Google Scholar]
  79. Bhanderi D. Lakhani P. Modi C. K. RSC Sustainability. 2024;2:265–287. doi: 10.1039/D3SU00382E. [DOI] [Google Scholar]
  80. Chandrappa S. Galbao S. J. Furube A. Murthy D. H. K. ACS Appl. Nano Mater. 2023;6:19551–19572. doi: 10.1021/acsanm.3c04740. [DOI] [Google Scholar]
  81. Ahmed M. A. Mahmoud S. A. Mohamed A. A. RSC Adv. 2024;14:25629–25662. doi: 10.1039/D4RA04234D. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Fatima G. Firdous S. Raza Q. Aamir M. Alsaikhan K. Khezami L. Jery A. E. Alamgir M. Jamshaid M. Lim S. Surf. Interfaces. 2026;89:109165. doi: 10.1016/j.surfin.2026.109165. [DOI] [Google Scholar]
  83. Raza Q. Lim S. Micromachines. 2025;16:1313. doi: 10.3390/mi16121313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Raza Q. Fatima G. Altilasi H. H. Aldosari E. Hussain I. Hossain M. A. Gurbanova L. Lim S. Jamshaid M. Int. J. Environ. Sci. Technol. 2026;23:143. doi: 10.1007/s13762-025-06822-6. [DOI] [Google Scholar]
  85. Raza Q. Iqbal S. Tamin T. N. Fareed A. Al-onazi W. A. Elshikh M. S. Iqbal R. Jamshaid M. J. Sol–Gel Sci. Technol. 2025;113:534–547. doi: 10.1007/s10971-024-06633-0. [DOI] [Google Scholar]
  86. Raza Q. Fatima G. Lu B. Bibi I. An J. Lim S. Surf. Interfaces. 2025;72:107203. doi: 10.1016/j.surfin.2025.107203. [DOI] [Google Scholar]
  87. Hayat A. Al-Sehemi A. G. El-Nasser K. S. Taha T. A. Al-Ghamdi A. A. Ali Shah Syed J. Amin M. A. Ali T. Bashir T. Palamanit A. Khan J. Nawawi W. I. Int. J. Hydrogen Energy. 2022;47:5142–5191. doi: 10.1016/j.ijhydene.2021.11.133. [DOI] [Google Scholar]
  88. Wang H. Liu Z. Wang L. Shou Q. Gao M. Wang H. Nazir A. Huo P. J. Mater. Sci.: Mater. Electron. 2023;34:350. doi: 10.1007/s10854-022-09642-3. [DOI] [Google Scholar]
  89. Tran Huu H. Le H. T. T. Huong Nguyen T. Nguyen Thi L. Vo V. Bin Im W. Appl. Surf. Sci. 2021;549:149312. doi: 10.1016/j.apsusc.2021.149312. [DOI] [Google Scholar]
  90. Wang X. Li P. Yu S. Sens. Actuators, B. 2025;429:137292. doi: 10.1016/j.snb.2025.137292. [DOI] [Google Scholar]
  91. Ahmed M. A. Farag M. Ahmed M. A. Mahmoud S. A. Mohamed A. A. Surf. Interfaces. 2025;64:106321. doi: 10.1016/j.surfin.2025.106321. [DOI] [Google Scholar]
  92. Zhang X. Guo Y. Zhao D. Wang X. Sun Y. Chen W. Int. J. Hydrogen Energy. 2025;179:151731. doi: 10.1016/j.ijhydene.2025.151731. [DOI] [Google Scholar]
  93. Mali J. M. Arbuj S. S. Ambekar J. D. Rane S. B. Mulik U. P. Amalnerkar D. P. Sci. Adv. Mater. 2013;5:1994–1998. doi: 10.1166/sam.2013.1667. [DOI] [Google Scholar]
  94. Chen L. Chen M. Jiang D. Xie J. J. Mol. Catal. A: Chem. 2016;425:174–182. doi: 10.1016/j.molcata.2016.10.003. [DOI] [Google Scholar]
  95. Di T. Zhu B. Cheng B. Yu J. Xu J. J. Catal. 2017;352:532–541. doi: 10.1016/j.jcat.2017.06.006. [DOI] [Google Scholar]
  96. Mittal S. Khosya M. Singh M. Khare N. Appl. Surf. Sci. 2024;677:161016. doi: 10.1016/j.apsusc.2024.161016. [DOI] [Google Scholar]
  97. Su T. Hood Z. D. Naguib M. Bai L. Luo S. Rouleau C. M. Ivanov I. N. Ji H. Qin Z. Wu Z. ACS Appl. Energy Mater. 2019;2:4640–4651. doi: 10.1021/acsaem.8b02268. [DOI] [Google Scholar]

Associated Data

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

Supplementary Materials

NA-OLF-D6NA00434B-s001

Data Availability Statement

The data are with the corresponding author and will be made available upon request.

Supplementary information (SI): comparison of the photocatalytic performance for the H2 generation with other photocatalysts, TEM-associated EDS spectra, catalyst recycling study and current–voltage characteristics in the dark. See DOI: https://doi.org/10.1039/d6na00434b.


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