Toward Real‐World Tetracycline Sensing: Label‐Free Carbon Quantum Dot Fluorescence From Molecular Design to Matrix‐Driven Challenges

ABSTRACT

Carbon quantum dot (CQD)‐based label‐free fluorescent sensing platforms have emerged as promising analytical approaches for the detection of tetracycline residues in food and environmental samples. This review summarizes recent advances in CQD design, fluorescence sensing mechanisms, and practical analytical applications, with an emphasis on precursor engineering, heteroatom doping, and surface‐state modulation. Among antibiotic contaminants, tetracyclines represent an important model target due to their extensive use, environmental persistence, and characteristic molecular properties that enable diverse interactions with CQD surfaces. Recognition‐assisted CQD biosensing architectures incorporating selective elements such as aptamers, antibodies, and molecularly imprinted polymers represent an important complementary strategy; however, this review specifically focuses on label‐free systems in which tetracycline‐induced modulation of CQD photoluminescence provides the sensing response. Reported label‐free CQD sensors demonstrate improved analytical performance and successful application in complex matrices, including milk, honey, serum, and water samples. Nevertheless, challenges related to fluorescence mechanism ambiguity, synthesis variability, insufficient standardization, matrix interference, and limited long‐term validation remain major barriers to practical deployment. Emerging trends, including smartphone‐assisted detection, paper‐based platforms, and sustainable biomass‐derived CQDs, indicate progress toward portable sensing technologies. Future development requires rational CQD design, standardized evaluation frameworks, and robust field‐validation strategies for reliable tetracycline monitoring.

This review presents a structure–property–function perspective of label‐free carbon quantum dot fluorescence sensing for tetracycline monitoring, highlighting CQD molecular design, sensing mechanisms, and matrix‐driven challenges. It identifies key barriers in reproducibility and validation while outlining strategies toward standardized, portable, and practical antibiotic sensing platforms.

1. Introduction

Tetracycline antibiotics represent one of the most extensively used classes of broad‐spectrum antimicrobial agents in modern veterinary and agricultural practices. Their widespread application in livestock production, aquaculture, and clinical medicine has significantly improved disease management and productivity; however, the excessive and uncontrolled use of tetracyclines has generated serious environmental and public health concerns [1, 2, 3, 4]. Residual tetracycline compounds frequently accumulate in food products, surface waters, wastewater streams, and agricultural soils, where they may contribute to antibiotic resistance, ecological imbalance, and chronic human exposure. The persistence of these antibiotics in complex biological and environmental systems has therefore intensified the global demand for rapid, sensitive, and field‐deployable analytical technologies capable of monitoring trace‐level contamination in real‐world matrices [5, 6, 7, 8].

Among different classes of antibiotic contaminants, tetracyclines represent a particularly important model target for CQD‐based fluorescence sensing because of their extensive application in veterinary and agricultural practices, environmental persistence, and characteristic molecular properties. The presence of multiple functional groups, strong UV–visible absorption, metal‐chelating capability, and diverse interaction pathways with carbon‐based nanomaterials enables tetracyclines to induce measurable fluorescence modulation in CQD systems. Therefore, tetracycline is selected in this review as a representative antibiotic class to provide a focused analysis of CQD design strategies, fluorescence response mechanisms, and real‐world analytical challenges. Although several issues discussed throughout this review, including matrix complexity and interference chemistry, are broadly applicable to other antibiotic sensing platforms, tetracycline provides a well‐defined case study for evaluating the practical limitations and future development of CQD‐based fluorescence sensors.

Conventional analytical methods for tetracycline determination, including high‐performance liquid chromatography (HPLC) [9, 10], liquid chromatography–mass spectrometry (LC–MS) [11, 12], capillary electrophoresis, and electrochemical assays, provide excellent sensitivity and selectivity. Nevertheless, these approaches often require sophisticated instrumentation, extensive sample preparation, highly trained personnel, and centralized laboratory infrastructure. Such limitations restrict their applicability for real‐time environmental surveillance and on‐site food safety monitoring [13, 14, 15]. In recent years, fluorescence‐based nanosensors have emerged as attractive alternatives because of their operational simplicity, rapid response, high sensitivity, and compatibility with portable analytical platforms [13, 16]. Among various fluorescent nanomaterials, carbon quantum dots (CQDs) have attracted extraordinary attention owing to their low toxicity, tunable photoluminescence, chemical stability, water dispersibility, and cost‐effective synthesis [17, 18, 19].

CQDs are quasi‐spherical carbonaceous nanostructures generally smaller than 10 nm that exhibit unique optical properties arising from quantum confinement, surface‐state emission, and defect‐mediated electronic transitions. Unlike conventional semiconductor quantum dots containing toxic heavy metals, CQDs offer superior biocompatibility and environmental sustainability, making them particularly attractive for sensing applications in food and environmental systems. Their fluorescence behavior can be readily tailored through precursor engineering, heteroatom doping, surface passivation, and post‐synthetic functionalization [20, 21, 22, 23]. Consequently, CQD‐based fluorescent probes have been extensively explored for the detection of metal ions, biomolecules, pesticides, pharmaceutical residues, and antibiotics, especially tetracycline derivatives.

CQD‐based fluorescence sensors can be broadly classified into label‐free platforms and recognition‐assisted biosensing architectures. In label‐free systems, the analytical signal originates from direct interactions between tetracycline molecules and CQD emissive states, resulting in fluorescence modulation through mechanisms such as inner filter effects, static interactions, charge transfer, or surface‐state alteration. Alternatively, recognition‐assisted CQD biosensors employ selective components, including aptamers, antibodies, enzymes, and molecularly imprinted polymers, to improve molecular specificity and reduce interference in complex samples. Although these hybrid approaches have expanded the scope of CQD‐based sensing, the present review focuses specifically on label‐free fluorescence strategies to provide a mechanistic understanding of CQD–tetracycline interactions and matrix‐dependent analytical limitations.

Despite the rapid growth of CQD‐based tetracycline sensing research, several fundamental scientific and translational challenges remain unresolved. A large proportion of reported sensing systems rely predominantly on fluorescence quenching mechanisms such as inner filter effects, static quenching, or electron‐transfer processes, yet these mechanisms are frequently proposed without rigorous spectroscopic validation. Furthermore, the optical behavior of CQDs is highly sensitive to synthetic conditions, precursor composition, surface oxidation state, and environmental parameters, leading to substantial variability between studies [24, 25, 26, 27]. This lack of standardization complicates direct comparison of analytical performance and limits reproducibility across laboratories.

Another major challenge arises from the complexity of real analytical matrices. Food products such as milk and honey, as well as environmental samples including river water and wastewater, contain diverse organic and inorganic constituents capable of interfering with fluorescence signals through absorption, scattering, competitive binding, and chemical transformation processes. Tetracycline molecules themselves exhibit pH‐dependent speciation and strong metal‐chelating behavior, further complicating accurate quantification under realistic conditions. Although many CQD‐based sensors demonstrate promising recoveries in spiked samples, relatively few studies critically evaluate matrix‐induced interference, long‐term operational stability, or practical field deployment [28, 29, 30].

In parallel, the field is increasingly shifting toward portable and intelligent sensing technologies. Smartphone‐assisted fluorescence analysis, paper‐based fluorescent strips, and biomass‐derived CQDs illustrate the growing emphasis on sustainable, low‐cost, and user‐accessible analytical platforms. However, issues related to calibration robustness, device reproducibility, environmental adaptability, and mechanistic understanding continue to hinder translation from proof‐of‐concept laboratory systems to reliable real‐world monitoring technologies.

This review examines the recent progress in CQD‐based fluorescent sensing of tetracycline antibiotics, with particular emphasis on synthetic engineering strategies, matrix‐dependent analytical challenges, sensing mechanisms, and translational perspectives. Rather than focusing solely on fluorescence enhancement or detection‐limit improvement, the present work highlights the broader relationship between CQD structural design, mechanistic reliability, and real‐world applicability. By integrating advances in precursor chemistry, heteroatom doping, surface‐state tailoring, and portable sensing architectures, this review aims to provide a comprehensive framework for the future development of standardized, intelligent, and field‐deployable CQD‐based antibiotic monitoring systems.

To provide an integrated overview of the review, Table 1 summarizes the conceptual pathway linking CQD molecular design, label‐free fluorescence modulation, matrix‐dependent analytical behavior, performance validation, and translation toward field‐deployable tetracycline sensing platforms.

TABLE 1.

Integrative framework of label‐free CQD fluorescence sensing for tetracycline: from molecular design to real‐world analytical translation.

Core domain	Key determinants	Mechanistic or analytical role	Principal evaluation criteria	Major unresolved limitation	Recommended design or validation priority	Related section
Review scope and target selection	Tetracycline use, environmental persistence, molecular functionality, optical absorption, and metal‐chelating behavior	Establishes tetracycline as a representative antibiotic target for focused evaluation of CQD fluorescence sensing	Relevance to food, biological, and environmental monitoring	Some matrix‐related challenges are not exclusive to tetracyclines	Clearly distinguish tetracycline‐specific interactions from challenges broadly applicable to other antibiotic classes	Introduction; Section 3
CQD precursor engineering	Molecular or biomass precursor, carbonization pathway, precursor purity, and compositional uniformity	Governs carbon‐core formation, defect distribution, surface chemistry, and emission reproducibility	Particle‐size distribution, structural order, surface composition, quantum yield, and batch consistency	Biomass heterogeneity and insufficient control of carbonization produce variable emissive states	Correlate precursor composition and reaction kinetics with reproducible structural and optical descriptors	Sections 2.1 and 2.4
Heteroatom and surface‐state engineering	Dopant identity and configuration, oxidation state, functional groups, passivation, and ligand density	Modulates electronic states, analyte accessibility, fluorescence intensity, colloidal stability, and interfacial interactions	XPS bonding states, FTIR signatures, fluorescence lifetime, emission stability, and surface charge	Total dopant content is often reported without resolving chemically active configurations	Combine quantitative surface characterization with spectroscopic and computational structure–function analysis	Sections 2.2 and 2.3
Sensing architecture and molecular recognition	Direct CQD–tetracycline interaction, spectral overlap, adsorption, and surface affinity	Label‐free systems generate signals through direct modulation of CQD photoluminescence; recognition‐assisted systems provide complementary selectivity	Signal magnitude, selectivity, response time, binding behavior, and cross‐reactivity	Label‐free responses may be nonspecific, whereas aptamer‐, antibody‐, and MIP‐assisted systems introduce additional interface complexity	Define the label‐free scope while considering recognition elements as complementary routes for improving molecular specificity	Introduction; Sections 4 and 5
Fluorescence‐response mechanism	Inner filter effect, static or dynamic quenching, electron transfer, energy transfer, and surface‐state alteration	Converts CQD–analyte interactions into measurable fluorescence changes	Absorption–excitation overlap, lifetime variation, Stern–Volmer behavior, temperature dependence, and spectral shifts	Mechanisms are frequently assigned from steady‐state fluorescence data alone	Require orthogonal validation using lifetime, absorption, temperature‐dependent, and structural measurements	Sections 4.1 and 5.1
Matrix‐dependent analytical behavior	pH, tetracycline speciation, proteins, lipids, metal ions, natural organic matter, turbidity, and coexisting antibiotics	Controls analyte availability, competitive binding, optical attenuation, scattering, and apparent fluorescence response	Matrix‐matched calibration, recovery, precision, interference panels, and comparison with reference methods	Spiked and extensively pretreated samples may underestimate real matrix complexity	Evaluate naturally contaminated or minimally processed samples using matrix‐specific controls and reference analysis	Section 3; Section 4.3
Analytical performance and comparability	Limit of detection, linear range, sensitivity, recovery, precision, selectivity, stability, and response time	Determines whether fluorescence improvements translate into reliable quantitative sensing	Standardized LOD calculation, calibration robustness, intra−/interbatch variation, and interlaboratory reproducibility	Inconsistent definitions and experimental protocols prevent meaningful cross‐study comparison	Establish harmonized synthesis, calibration, reporting, and validation protocols	Sections 4.1, 4.3 and 5.2
Portable and intelligent deployment	Paper substrates, smartphone RGB analysis, dual‐readout systems, digital processing, storage stability, and sustainable CQD production	Enables decentralized, rapid, low‐cost, and user‐accessible tetracycline monitoring	Device‐to‐device reproducibility, illumination control, shelf life, field recovery, robustness, and user operability	Camera variability, ambient lighting, uneven reagent distribution, and limited field validation compromise quantitative reliability	Integrate internal calibration, standardized imaging, robust device fabrication, long‐term testing, and intelligent data analysis	Sections 4.4, 4.5 and 5.3
Translational pathway	Predictive material design, scalable synthesis, mechanistic certainty, regulatory validation, and lifecycle considerations	Connects laboratory fluorescence probes with standardized, field‐deployable sensing technologies	Scale‐up consistency, operational durability, environmental impact, external validation, and regulatory readiness	Current CQD sensors remain predominantly empirical and laboratory‐centered	Converge rational molecular design, mechanistic validation, standardized benchmarking, and digital integration	Sections 5.1, 5.4; Conclusion

Abbreviations: CQD: carbon quantum dot; FTIR: Fourier‐transform infrared spectroscopy; LOD: limit of detection; MIP: molecularly imprinted polymer; RGB: red–green–blue; XPS: X‐ray photoelectron spectroscopy.

Figure 1 summarizes the central logic of this review by connecting CQD molecular engineering with label‐free tetracycline sensing, matrix‐dependent interference, and practical translation. Precursor selection, heteroatom doping, and surface functionalization regulate CQD electronic structure, emissive states, water dispersibility, and analyte accessibility. Tetracycline then modulates fluorescence through inner filter effects, static quenching, electron transfer, and surface‐state interactions. In real samples, pH‐dependent speciation, metal ions, proteins, organic matter, turbidity, and suspended particles can alter binding and optical signals. Reliable deployment therefore requires mechanistic validation, standardized protocols, reproducible fabrication, storage stability, and field evaluation under realistic food and environmental conditions and operational constraints.

FIGURE 1.

Conceptual framework linking CQD engineering, label‐free tetracycline fluorescence responses, matrix interference, and translational requirements for reliable real‐world sensing and deployment.

2. CQD Synthetic Engineering and Surface Modulation

2.1. Precursor Engineering and CQD Structure Control

The precursor chemistry employed during CQD synthesis fundamentally dictates the nucleation pathway, carbonization degree, graphitic ordering, and distribution of emissive domains. Although many studies continue to emphasize facile and low‐cost preparation routes, increasing evidence suggests that precursor selection is not merely a synthetic convenience but rather the primary factor governing reproducibility and photoluminescence consistency. Small molecular precursors such as citric acid, glucose, and ethylenediamine typically yield CQDs with relatively controllable particle size distributions and abundant oxygen‐containing functionalities [31, 32, 33]. In contrast, biomass‐derived precursors introduce chemically heterogeneous carbon frameworks due to the intrinsic complexity of lignocellulosic, proteinaceous, or polysaccharide‐rich feedstocks. While biomass routes are frequently promoted as “green” alternatives, their compositional variability often leads to batch‐to‐batch inconsistencies that remain insufficiently addressed in the literature.

Recent synthetic strategies have therefore shifted toward precursor rationalization rather than precursor availability alone. The use of molecularly defined aromatic compounds, amino acids, and polymeric intermediates has enabled better control over sp²/sp³ carbon ratios, defect density, and surface passivation efficiency. Importantly, precursor polarity and decomposition kinetics strongly influence the formation of surface trap states that dominate fluorescence behavior. Nevertheless, many reports still correlate optical performance solely with particle size despite growing recognition that emission properties originate predominantly from surface‐state heterogeneity rather than quantum confinement alone [34, 35].

Another emerging direction involves hybrid precursor systems integrating biomass resources with molecular dopants to balance sustainability and structural precision. Such approaches offer improved tunability while partially mitigating precursor unpredictability. However, systematic comparative studies remain scarce, and the field still lacks standardized precursor selection criteria capable of linking molecular composition to final sensing functionality. Consequently, precursor engineering remains one of the most underdeveloped yet decisive aspects in advanced CQD design.

2.2. Heteroatom Doping Strategies for Electronic Structure Manipulation

Heteroatom incorporation has emerged as one of the most influential approaches for tailoring the electronic and optical characteristics of CQDs. Doping with nitrogen, sulfur, phosphorus, boron, or multiple heteroatoms simultaneously modifies the local electron density, introduces defect‐mediated energy states, and alters radiative recombination pathways. Among these, nitrogen doping has received the greatest attention because of its comparable atomic radius to carbon and its ability to enhance electron‐donating capacity without severely disrupting the carbon lattice [36, 37]. Nevertheless, the extensive preference for nitrogen‐doped systems has arguably led to conceptual oversimplification, where fluorescence enhancement is often attributed to nitrogen incorporation without rigorous mechanistic validation.

The actual influence of heteroatoms depends strongly on their bonding configuration within the carbon framework. Pyridinic, pyrrolic, and graphitic nitrogen species produce markedly different electronic effects, yet many studies report only total elemental percentages without distinguishing the specific dopant environment. Similarly, sulfur doping may induce both electron‐withdrawing and electron‐donating effects depending on the oxidation state of sulfur‐containing groups. Such structural ambiguities complicate attempts to establish universal structure–performance relationships.

Co‐doping strategies have recently gained momentum because synergistic interactions between heteroatoms can simultaneously improve quantum yield, conductivity, and environmental stability. However, many published systems rely heavily on empirical optimization rather than predictive design principles [38, 39, 40]. The excessive use of multi‐element doping without mechanistic clarity risks transforming CQD synthesis into a combinatorial exercise rather than a scientifically rational process.

Moreover, heteroatom doping frequently affects not only fluorescence intensity but also colloidal stability, hydrophilicity, and resistance to ionic interference. These secondary effects are particularly important for sensing applications in complex matrices but are often underreported. Future progress in this area requires a more rigorous correlation between dopant chemistry, electronic band structure, and functional performance through advanced spectroscopic and computational investigations rather than phenomenological interpretation alone.

Figure 2 provides important spectroscopic evidence for the role of heteroatom incorporation in modulating the electronic structure of CQD‐based nanocomposites. The XPS survey spectrum (Figure 2a) confirms the presence of Ni, O, C, and Ce, verifying the successful introduction of cerium into the composite framework without detectable impurities. The high‐resolution Ni 2p spectrum (Figure 2b) reveals characteristic Ni²⁺ states, indicating that the host lattice retains its main oxidation environment after dopant incorporation. In Figure 2c, the deconvoluted C 1s spectrum displays contributions from C−C/C=C, C−O−C, and O−C=O species, demonstrating the coexistence of graphitic carbon domains and oxygen‐containing surface functionalities relevant to charge redistribution. The O 1s spectrum (Figure 2d) further supports the presence of chemically distinct oxygen environments associated with lattice oxygen and surface groups. Collectively, these XPS results illustrate that heteroatom doping should not be interpreted solely in terms of elemental composition; rather, the local bonding configuration and associated electronic perturbation are critical for understanding how dopants modify charge density, defect states, and interfacial reactivity, consistent with the mechanistic perspective.

FIGURE 2.

XPS characterization of the CQDs/Ce‐NiO nanocomposite: (a) survey spectrum, (b) Ni 2p high‐resolution spectrum, (c) C1s deconvoluted spectrum, and (d) O 1s spectrum, evidencing dopant incorporation and chemically distinct bonding environments. Adapted with permission from Ref. [39]. Copyright 2021 Elsevier B.V.

2.3. Surface‐State Tailoring and Functional Interface Design

The optical behavior of CQDs is now widely understood to be governed predominantly by surface states rather than by the carbon core itself. Surface functional groups create localized energy levels that regulate electron relaxation pathways, fluorescence emission profiles, and interfacial interactions with surrounding media. Consequently, surface‐state tailoring has become a central strategy for constructing CQDs with tunable optical properties and enhanced environmental adaptability.

Oxygen‐containing groups such as hydroxyl, carboxyl, and carbonyl moieties are commonly generated during hydrothermal and oxidative synthesis processes. These functionalities improve water dispersibility and provide anchoring sites for subsequent chemical modification [41, 42, 43]. However, excessive oxidation may simultaneously increase nonradiative recombination centers, reducing fluorescence efficiency. Achieving a balance between surface passivation and defect generation therefore remains a major synthetic challenge.

Recent studies increasingly employ post‐synthetic functionalization approaches to introduce amine‐rich ligands, polymers, ionic species, or aromatic molecules onto CQD surfaces. Such modifications not only stabilize emissive states but also regulate electron‐transfer behavior and steric accessibility at the nano‐bio interface. Importantly, surface chemistry also determines resistance to pH fluctuations, ionic strength variation, and nonspecific adsorption in real matrices. Despite this significance, many reports continue to characterize CQDs using only basic FTIR or XPS analysis without quantitatively evaluating surface‐state distribution or ligand density.

Another unresolved issue concerns the origin of excitation‐dependent fluorescence. While surface heterogeneity is frequently proposed as the dominant explanation, the coexistence of multiple emissive centers complicates definitive interpretation. This uncertainty limits the rational engineering of highly reproducible CQD systems [44, 45]. From a broader perspective, surface‐state engineering should not be viewed solely as a fluorescence optimization strategy. Instead, it represents a critical platform for modulating colloidal behavior, environmental compatibility, and interfacial selectivity. The next generation of CQDs will likely depend less on increasing quantum yield alone and more on constructing chemically programmable surfaces with predictable functional responses.

2.4. Synthetic Methodologies: Balancing Scalability, Structural Precision, and Sustainability

The rapid expansion of CQD research has generated a wide range of synthetic methodologies, including hydrothermal treatment, solvothermal synthesis, microwave irradiation, electrochemical oxidation, laser ablation, pyrolysis, and ultrasonic approaches. Each method offers distinct advantages in terms of reaction speed, particle uniformity, energy consumption, and scalability. However, the field still faces a persistent contradiction between laboratory‐scale optical optimization and industrial‐scale reproducibility.

Hydrothermal synthesis remains the dominant route because of its operational simplicity and compatibility with diverse precursors. Nevertheless, hydrothermal systems frequently produce CQDs with broad size distributions and poorly defined surface chemistry due to simultaneous carbonization and passivation processes occurring under uncontrolled kinetic conditions. Microwave‐assisted synthesis partially addresses these limitations by providing rapid and homogeneous heating, thereby improving reaction efficiency and reducing synthesis time [45, 46, 47, 48]. Yet microwave methods often suffer from limited scalability and inconsistent energy distribution in larger reaction volumes.

Top‐down strategies such as electrochemical exfoliation and laser ablation generate CQDs with relatively high crystallinity and fewer residual organic impurities. Despite these advantages, such methods usually require sophisticated instrumentation and exhibit lower production efficiency compared with bottom‐up techniques. Furthermore, the environmental sustainability frequently claimed for CQD synthesis deserves more critical examination. Many “green” protocols still rely on high temperatures, strong acids, or energy‐intensive purification procedures that diminish their practical sustainability profile.

An additional challenge involves the absence of standardized synthetic reporting. Variations in precursor concentration, heating rate, reaction atmosphere, and purification strategy can profoundly alter CQD properties, yet these parameters are often incompletely described. This lack of methodological transparency severely restricts reproducibility across laboratories. Future synthetic development should therefore prioritize controllable manufacturing protocols capable of integrating structural precision, economic feasibility, and environmental responsibility simultaneously [48, 49, 50]. Without such integration, the translational potential of CQDs may remain constrained despite impressive laboratory‐scale performance.

2.5. Structure–Property–Function Relationships in CQD‐Based Tetracycline Sensing

The sensing performance of CQDs is ultimately determined by the interplay between their structural features, electronic properties, surface chemistry, and molecular interactions with tetracycline. Although precursor engineering, heteroatom doping, and surface functionalization are frequently reported as independent optimization strategies, their effects are strongly interconnected because each modification alters the carbon framework, defect distribution, emissive states, and analyte accessibility. Therefore, understanding CQD‐based tetracycline sensing requires moving beyond empirical performance comparisons toward a structure–property–function perspective.

Precursor chemistry represents the initial determinant of CQD structure and governs the formation of sp²/sp³ carbon domains, oxygen‐containing groups, nitrogen functionalities, and surface defect states. Molecular precursors with defined chemical compositions generally enable better control over carbonization pathways and surface uniformity, whereas biomass‐derived precursors introduce diverse heteroatom‐containing structures that may enhance interaction sites but also increase batch‐to‐batch variability. These structural differences directly influence fluorescence behavior by modifying radiative and non‐radiative recombination pathways, surface‐state emission, and charge‐transfer capability [41, 42, 43].

Heteroatom doping further regulates the electronic structure of CQDs by introducing additional energy states, modifying electron density, and adjusting surface polarity. Nitrogen incorporation, for example, can generate electron‐rich sites and alter the interaction environment between CQDs and tetracycline molecules, whereas sulfur or phosphorus incorporation may modify surface polarization and defect chemistry. However, improved sensing performance should not be attributed solely to the presence of dopants, because the chemical configuration, bonding environment, and accessibility of dopant‐related sites are more important than total elemental content.

Surface functional groups provide the direct interface responsible for CQD–tetracycline interactions. Oxygenated and nitrogen‐containing groups can participate in hydrogen bonding, electrostatic interactions, π–π stacking, and metal‐mediated coordination with tetracycline molecules. These interactions influence analyte adsorption, local concentration near emissive centers, and subsequent fluorescence modulation through inner filter effects, electron transfer, or other photophysical pathways. Thus, fluorescence response should be considered as the final consequence of a sequence involving material formation, electronic regulation, molecular recognition, and signal generation.

A rational CQD sensor design therefore requires simultaneous optimization of carbon framework structure, surface functionality, defect states, and analyte accessibility rather than maximizing fluorescence intensity alone. Establishing quantitative structure–property–function relationships will enable more predictable development of CQD platforms with improved selectivity, reproducibility, and real‐world sensing reliability.

3. Matrix Effects and Interference Challenges

Although tetracycline is used as the representative analyte throughout this review, the matrix‐related challenges discussed in this section, including chemical heterogeneity, competitive interactions, analyte transformation, and optical interference, are also broadly relevant to fluorescence‐based sensing of other antibiotic classes. Complex food and environmental matrices contain diverse organic and inorganic constituents that can influence analyte availability, molecular interactions, and fluorescence signal stability, regardless of the specific antibiotic structure. Similar challenges may occur during the detection of other widely investigated antibiotics, including sulfonamides, fluoroquinolones, macrolides, and β‐lactams, where coexisting proteins, metal ions, natural organic matter, and chromophoric compounds can alter analytical responses. Therefore, while the mechanistic discussion in this section is centered on tetracycline–CQD sensing systems, the underlying principles of matrix interference, competitive binding, and signal distortion reflect general considerations for the development of reliable fluorescence‐based antibiotic monitoring platforms. Understanding these cross‐cutting limitations is essential for translating CQD sensors from controlled laboratory demonstrations toward practical applications in diverse real‐world samples.

3.1. Chemical Heterogeneity of Real Samples and Its Impact on Tetracycline Speciation

Accurate determination of tetracycline residues in real samples is fundamentally governed by the extreme chemical heterogeneity of food and environmental matrices. Unlike simplified aqueous standards, matrices such as milk, honey, serum, river water, and agricultural runoff contain a dense and chemically active mixture of proteins, lipids, carbohydrates, metal ions, and natural organic matter. This complexity directly alters the chemical speciation of tetracyclines, which exist in multiple protonation states depending on pH and ionic composition. As a result, the analyte does not behave as a single chemically stable entity, but rather as a dynamic ensemble of interconverting species with different binding and optical properties.

One of the most influential factors is pH‐dependent speciation. Tetracyclines possess multiple ionizable functional groups, and slight pH variations can significantly shift the equilibrium between cationic, zwitterionic, and anionic forms. These structural changes strongly influence solubility, molecular conformation, and coordination ability with metal ions [51, 52, 53]. Consequently, even minor pH fluctuations between different sample types can introduce substantial variability in analytical response.

In addition, tetracyclines exhibit strong chelation behavior toward divalent and trivalent metal ions such as Ca²⁺, Mg²⁺, and Fe³⁺. These complexes are frequently present in dairy products and natural waters, where they can significantly reduce the concentration of free, detectable analyte. Importantly, such complexation is not merely a physical interference but a chemical transformation that fundamentally alters the electronic structure of the antibiotic molecule.

Dissolved organic matter, particularly humic and fulvic substances in environmental water, further complicates analytical interpretation [51, 54, 55]. These macromolecular species can interact with tetracyclines through hydrogen bonding, π–π interactions, and hydrophobic association, effectively masking or redistributing the analyte within the matrix. As a result, the nominal concentration of tetracycline does not necessarily reflect its analytically available fraction. Overall, matrix‐driven chemical speciation represents a primary source of uncertainty in tetracycline analysis and challenges the assumption that calibration in simplified media can be directly transferred to real‐world systems.

3.2. Interfering Chemical Interactions and Competitive Binding Phenomena

Beyond speciation effects, tetracycline detection is strongly influenced by competitive chemical interactions within complex matrices. Food and environmental samples contain numerous coexisting species capable of interacting with both the analyte and the analytical interface, leading to signal distortion and reduced selectivity. These interactions are often multifaceted, involving competition for binding sites, redox activity, and secondary complex formation.

Proteins such as casein in milk or albumin in serum can bind tetracycline molecules through hydrophobic pockets and electrostatic interactions. This binding reduces the freely available fraction of analyte, thereby decreasing apparent detection sensitivity. Importantly, such protein–drug interactions are reversible and dynamic, making their analytical impact dependent on incubation time, temperature, and matrix composition [53, 56, 57].

In environmental systems, competing organic molecules may exhibit structural similarity or functional group complementarity with tetracyclines, leading to nonspecific adsorption or co‐binding effects. These interactions can introduce false‐positive or suppressed signals depending on the analytical modality used. Furthermore, the presence of multiple antibiotics in contaminated environments creates additional complexity, as structurally related compounds may compete for identical interaction pathways. Metal ions represent another major interference source. Beyond simple complexation, they may catalyze oxidative transformations of tetracycline molecules under certain conditions, altering their chemical identity during analysis [58, 59, 60]. Such transformations are rarely accounted for in calibration models, yet they can significantly affect analytical accuracy.

An often overlooked aspect is the role of colloidal and particulate matter in environmental samples. Suspended solids can physically adsorb tetracycline, creating heterogeneous distribution and time‐dependent release into the solution phase. This dynamic partitioning complicates the assumption of equilibrium conditions commonly used in analytical calibration. Collectively, these competitive and reactive interactions highlight that tetracycline analysis in real matrices is governed by a complex network of chemical equilibria rather than a simple analyte–signal relationship.

3.3. Matrix‐Induced Optical and Analytical Signal Distortion

In addition to chemical interactions, physical and optical properties of complex matrices significantly influence analytical signal integrity. Many food and environmental samples contain strongly absorbing or scattering components that interfere with optical detection systems used for tetracycline quantification. These interferences are particularly critical in fluorescence‐based measurements, where signal intensity is highly sensitive to background absorption and light propagation effects.

Natural chromophores such as humic substances, carotenoids, and flavins exhibit broad absorption in the UV–visible region, overlapping with the excitation or emission wavelengths of tetracycline and related detection systems. This spectral overlap can result in apparent signal quenching or enhancement depending on the relative absorption profiles, leading to systematic errors in quantification. Turbidity is another major source of distortion, particularly in dairy and environmental samples containing suspended particles or emulsified fat globules [51, 61, 62]. Light scattering induced by these particulates reduces excitation efficiency and alters emission collection pathways, thereby compromising signal linearity. Such effects are often nonlinear and difficult to correct using conventional calibration methods.

Refractive index variations across different matrices further complicate optical measurements by altering photon propagation and detection efficiency. These subtle physical effects are rarely considered in analytical design, despite their potential to introduce significant variability between sample types. Another important limitation arises from fluorescence reabsorption phenomena, where emitted photons are partially absorbed by other matrix components before detection [63, 64, 65].

This secondary absorption process can artificially reduce measured intensity, mimicking analyte quenching even in the absence of true chemical interaction. Importantly, many reported analytical systems do not systematically decouple chemical quenching from physical optical interference, leading to the overestimation of sensor specificity. Without proper matrix‐matched calibration or advanced correction strategies, such distortions remain a persistent source of analytical uncertainty.

3.4. Limitations of Sample Pretreatment and Real‐World Analytical Constraints

To mitigate matrix effects, a wide range of sample pretreatment strategies is commonly employed, including filtration, centrifugation, dilution, protein precipitation, and solvent extraction. While these methods improve analytical clarity, they introduce their own set of limitations that can significantly affect accuracy, reproducibility, and practical applicability. Dilution is the most straightforward approach but inevitably reduces analyte concentration, potentially pushing it below detection thresholds and increasing quantification uncertainty. Protein precipitation techniques, commonly used for biological samples, may also lead to partial analyte loss due to co‐precipitation or adsorption onto removed macromolecules.

Solid‐phase extraction provides improved selectivity but requires additional processing time, specialized materials, and optimized conditions for different matrices. These requirements contradict the objective of developing rapid and field‐deployable analytical systems [1, 60, 66]. Moreover, extraction efficiency can vary significantly depending on sample composition, introducing another layer of variability. Filtration and centrifugation methods are effective for removing particulate matter but do not eliminate dissolved interferents such as metal ions or organic chromophores. Consequently, optical and chemical interferences may persist even after extensive preprocessing.

A critical limitation of most pretreatment strategies is their reliance on equilibrium assumptions and controlled laboratory conditions. Naturally contaminated samples often exhibit non‐equilibrium behavior, particularly in dynamic environmental systems where adsorption–desorption processes continuously occur. Standard pretreatment protocols may therefore fail to capture the true distribution of tetracycline species in situ. Furthermore, excessive sample processing reduces the feasibility of real‐time monitoring applications, which are increasingly important for environmental surveillance and food safety. Each additional processing step introduces a time delay, cost, and potential error propagation [67, 68, 69]. Overall, while sample pretreatment is essential for improving analytical performance, it simultaneously introduces methodological constraints that limit the transition from laboratory‐based detection to practical, real‐world tetracycline monitoring systems.

4. Performance Evaluation of CQD Tetracycline Sensors

4.1. Evolution of Sensitivity and Analytical Performance in CQD‐Based Tetracycline Sensors

Recent CQD‐based fluorescent probes for tetracycline (TC) analysis demonstrate a clear progression toward lower detection limits, wider linear ranges, and improved operational stability. Nevertheless, comparison among reported systems reveals that analytical enhancement is often achieved through empirical optimization rather than mechanistically guided sensor engineering. Early biomass‐derived N‐doped CQDs exhibited respectable analytical performance, with detection limits for TC derivatives ranging between 0.2367 and 0.3739 μM [70]. These systems demonstrated the feasibility of CQD‐based antibiotic sensing while highlighting the importance of nitrogen incorporation for fluorescence enhancement.

Subsequent studies increasingly focused on heteroatom‐doped architectures to improve sensitivity. S,N‐co‐doped CQDs achieved a TC detection limit of 0.56 μM with satisfactory recoveries in milk, honey, and tap water [71]. Although analytically reliable, the relatively narrow linear range and moderate sensitivity indicated that fluorescence enhancement alone was insufficient to overcome limitations associated with quenching efficiency and background interference. Similar observations were reported for N‐CQDs synthesized from glucose and ethylenediamine, where detection limits varied substantially among TC analogues, reaching 0.117 μM for chlortetracycline [72]. Such variability suggests that analyte‐specific spectral overlap and molecular interaction pathways strongly influence sensing behavior, complicating universal sensor design.

The panels in Figure 3 illustrate how the sensing performance of S,N‐CQDs toward tetracycline is governed by well‐defined photophysical pathways rather than uncontrolled empirical effects. The fluorescence‐decay profiles in Figure 3A show that the lifetime of S,N‐CQDs remains essentially unchanged after TC addition, supporting a static‐quenching scenario and confirming that sensitivity enhancement does not arise from excited‐state perturbation. Complementary spectral evidence in Figure 3B demonstrates strong overlap between the UV–Vis absorption of TC and the excitation/emission bands of S,N‐CQDs, establishing the internal filter effect (IFE) as the dominant mechanism responsible for the observed fluorescence attenuation. The absence of any new FTIR signatures further indicates that no ground‐state complex or chemical modification occurs, confirming that signal modulation depends on optical interaction rather than molecular bonding. These mechanistic insights highlight a recurring trend in CQD‐based TC sensors: improvements in detection limits and reliability often stem from optimized spectral coupling and selective quenching pathways rather than fundamental changes in CQD structure—an important distinction for translating fluorescence sensing performance toward real analytical environments.

FIGURE 3.

(A) Fluorescence lifetimes of S,N‐CQDs with/without TC indicating static quenching. (B) UV–Vis absorption of TC overlapping with S,N‐CQD excitation/emission, confirming an internal filter effect–driven sensing mechanism. Adapted with permission from Ref. [71]. Copyright 2022 Elsevier B.V.

More recent studies have shifted toward maximizing quantum yield and signal amplification. Methionine‐doped CQDs achieved a notably lower detection limit of 0.032 μM alongside an exceptionally broad linear range of 0.1–500 μM [73]. This substantial improvement reflects the increasing emphasis on surface‐state engineering and optimized heteroatom coordination. However, the literature frequently equates lower detection limits with superior sensor quality while neglecting reproducibility, long‐term stability, and matrix robustness. Importantly, several reported systems still operate within concentration ranges substantially higher than realistic trace contamination levels encountered in environmental monitoring [53, 59]. Consequently, although analytical sensitivity has improved markedly across studies, practical deployment remains constrained by insufficient standardization, inconsistent calibration strategies, and limited cross‐platform validation.

4.2. Influence of Carbon Source and Doping Strategy on Sensor Functionality

The reported CQD sensors reveal a strong dependence of analytical behavior on precursor selection and doping chemistry. Biomass‐derived systems have attracted particular attention because of their low cost, environmental compatibility, and intrinsic heteroatom content. Rice residue‐derived N‐CQDs exhibited relatively high quantum yield (23.48%) due to synergistic interactions between nitrogen functionalities and oxygen‐containing surface groups [70]. Similarly, self‐nitrogen‐doped CQDs synthesized from mulberry leaves leveraged the naturally high nitrogen content of the precursor to achieve a low detection limit of 158 nM [74]. These findings demonstrate that precursor composition can directly influence emissive‐state formation without requiring extensive post‐synthetic modification.

However, the increasing preference for biomass precursors has also exposed significant reproducibility concerns. Naturally derived feedstocks possess inherently variable molecular compositions depending on cultivation conditions, extraction procedures, and seasonal variation. Despite this, many reports continue to present biomass‐derived CQDs as universally reproducible platforms without critically addressing precursor heterogeneity [45, 60]. For example, marine algae‐derived CQDs displayed excellent stability under varying ionic strength, temperature, and pH conditions [75], yet the broader implications of biological source variability were not systematically investigated.

Doping strategies similarly play a decisive role in determining fluorescence intensity and quenching behavior. Nitrogen doping consistently enhances optical performance by modifying electron density and surface emissive states [70, 72]. Co‐doping with sulfur and nitrogen further improves fluorescence response through additional defect‐state modulation. Nevertheless, mechanistic interpretation often remains superficial. Many studies attribute enhanced sensing performance to “synergistic effects” without directly characterizing dopant configuration or electronic‐state distribution.

Methionine‐derived CQDs represent a more rationalized doping approach in which sulfur‐containing amino acid precursors contribute simultaneously to fluorescence enhancement and rapid response kinetics [73]. In contrast, waste ammonium sulfate‐derived S,N‐CQDs highlighted the growing interest in circular‐economy‐oriented nanomaterial production [76]. Yet despite these advances, most studies still prioritize fluorescence enhancement over scalable manufacturing consistency. As a result, the field continues to face a critical gap between laboratory‐level optical optimization and reproducible large‐scale sensor fabrication.

The panels in Figure 4 clearly illustrate how precursor‐derived nitrogen doping governs the sensing behavior of N‐CQDs toward tetracycline and its analogues, fully consistent with the mechanistic framework. In Figure 4a, the pronounced fluorescence quenching observed only in the presence of TC, CTC, and OTC highlights the decisive role of dopant‐induced emissive states that provide selective interaction sites for structurally related tetracyclines. The UV‐irradiated images in Figure 4b further visualize the dopant‐dependent sensitivity, where nitrogen‐rich surface states enable strong optical contrast and rapid emissive suppression upon exposure to TCs. The concentration‐dependent PL decay in Figure 4c demonstrates that the fluorescence intensity of N‐CQDs decreases systematically with increasing TC concentration, reflecting the direct influence of nitrogen‐mediated electron‐density modulation on quenching efficiency. Finally, the linear I/I₀ behavior in Figure 4d across a defined concentration range underscores how nitrogen doping stabilizes consistent surface interaction pathways, enabling predictable analytical performance across multiple tetracycline analogues. Together, these results show that the sensing mechanism is intrinsically linked to precursor composition and dopant chemistry—validating that the origin of selectivity and quantitative response in N‐CQD sensors arises not from general CQD behavior but from dopant‐specific emissive states shaped by the carbon source and nitrogen incorporation strategy.

FIGURE 4.

(a) PL response of N‐CQDs to various molecules. (b) UV fluorescence images. (c) TC‐dependent intensity decay. (d) Linear I/I₀ calibration demonstrating dopant‐driven sensitivity toward tetracycline analogues. Adapted with permission from Ref. [70]. Copyright 2019 Elsevier B.V.

4.3. Detection Matrices and Real‐Sample Applicability: Progress and Persistent Limitations

One of the most important indicators of practical sensor relevance is performance within real analytical matrices rather than idealized buffer systems. Reported CQD‐based tetracycline sensors have increasingly expanded from model aqueous solutions toward food and environmental applications, including milk, honey, serum, river water, and tap water [70, 73]. This transition reflects growing recognition that matrix complexity critically influences fluorescence reliability and analytical selectivity.

Milk remains the most commonly evaluated food matrix because of the widespread veterinary use of tetracyclines in dairy production. Several CQD probes demonstrated satisfactory recoveries in milk samples, generally ranging between approximately 93% and 102% [75]. While these results appear analytically promising, many studies employ heavily diluted or pretreated samples, thereby reducing matrix complexity prior to analysis. Consequently, the reported recoveries may not fully represent sensor performance under minimally processed real‐world conditions.

Environmental matrices present additional challenges because dissolved organic matter, metal ions, and fluctuating pH conditions can strongly affect fluorescence behavior. River‐water applications demonstrated encouraging recoveries between 98.6% and 102.2% with low relative standard deviation values [74]. Likewise, biomass‐derived N‐CQDs showed good agreement with UV–vis analysis for tetracycline detection in water samples. However, most environmental evaluations remain limited to laboratory‐spiked samples rather than naturally contaminated systems containing multiple coexisting antibiotics and degradation products [13, 59].

Another recurring issue involves selectivity assessment. Many studies evaluate interference using relatively small panels of ions or structurally unrelated compounds [75]. Such simplified selectivity tests do not adequately simulate real food or environmental matrices where numerous fluorescent quenchers and organic contaminants coexist simultaneously. Furthermore, long‐term sensor stability under continuous storage or repeated analytical cycles is rarely examined comprehensively.

Thus, although current CQD sensors demonstrate increasingly successful application in practical matrices, much of the literature still prioritizes proof‐of‐concept validation over rigorous field‐level analytical benchmarking. Bridging this gap remains essential for translating fluorescent CQD platforms into dependable monitoring technologies.

4.4. Current On‐Site Formats and Demonstrated Practical Performance

Recent studies have extended CQD‐based tetracycline sensing beyond solution‐phase fluorescence measurements toward simplified formats intended for rapid and minimally instrumented analysis. Within the available evidence, paper‐supported probes and digital image‐based readouts represent the clearest examples of this transition. Self‐nitrogen‐doped CQDs incorporated into fluorescent test papers produced visually distinguishable responses to tetracycline, demonstrating the feasibility of transferring CQD fluorescence from conventional cuvette measurements to disposable sensing substrates [74]. Such formats reduce instrumental dependence and simplify sample handling, although the reported demonstrations generally remain based on controlled laboratory conditions and predefined analyte concentrations.

Methionine‐derived CQDs provide a complementary example in which fluorescence changes were quantified through smartphone imaging and RGB analysis [73]. The reported agreement with LC–MS/MS measurements indicates that consumer imaging devices may support approximate quantitative analysis when acquisition geometry, illumination, and image‐processing conditions are controlled. The rapid fluorescence response observed for this system also illustrates the potential of CQD probes for time‐sensitive screening. Nevertheless, these outcomes should be interpreted as proof‐of‐concept demonstrations rather than evidence of fully validated field performance because device‐to‐device variation, ambient‐light sensitivity, and matrix‐dependent color rendering were not comprehensively examined. Current studies establish that CQD fluorescence can be transferred to test papers, visual readouts, and digitally quantified formats. Their principal contribution lies in demonstrating practical format compatibility; however, they do not yet provide sufficient evidence of long‐term stability, cross‐device reproducibility, or reliable operation in naturally contaminated samples.

The panels in Figure 5 highlight the increasing relevance of selectivity‐driven fluorescence platforms for portable and on‐site tetracycline monitoring. The stable fluorescence response of S,N‐CQDs in the presence of structurally diverse organic molecules (Figure 5a), metal cations (Figure 5b), and common anions (Figure 5c) demonstrates that the sensing signal remains dominated by tetracycline rather than environmental interferants. Such robustness is essential for field‐deployable systems, where complex sample matrices often compromise quantitative reliability. The ability of S,N‐CQDs to maintain consistent F/F₀ values even at interferant concentrations exceeding tetracycline by fivefold indicates strong molecular recognition fidelity and minimal cross‐reactivity—critical attributes for integration into test papers, smartphone‐readout platforms, and low‐instrumentation fluorescence devices. Overall, these results underscore the sensor's suitability for decentralized, rapid, and user‐friendly tetracycline detection.

FIGURE 5.

(a) Fluorescence response of S,N‐CQDs to interfering molecules, (b) metal cations, and (c) anions, showing minimal cross‐reactivity and strong selectivity toward tetracycline, supporting reliable on‐site and portable sensing performance. Adapted with permission from Ref. [76]. Copyright 2024 Elsevier B.V.

4.5. Molecular Recognition and CQD–Tetracycline Interactions

Although fluorescence quenching mechanisms such as inner filter effect (IFE), photoinduced electron transfer (PET), and Förster resonance energy transfer (FRET) are frequently invoked to explain the fluorescence variation of CQD‐based tetracycline sensors, these mechanisms primarily describe the signal‐transduction process rather than the origin of analyte selectivity. The ability of CQDs to preferentially interact with tetracycline molecules is governed by a combination of surface chemistry, molecular structure, and interfacial interactions between the analyte and emissive states of CQDs.

Tetracycline molecules possess multiple functional groups, including hydroxyl, carbonyl, amino, and aromatic moieties, which provide diverse interaction pathways with functionalized CQD surfaces. Hydrogen bonding, π–π stacking between tetracycline aromatic rings and sp² carbon domains, electrostatic attraction, hydrophobic interactions, and metal‐mediated coordination can promote adsorption and spatial proximity between tetracycline and CQDs [73, 74, 75]. Surface oxygen‐containing groups, nitrogen‐containing functionalities, and heteroatom‐induced defect states introduced during CQD synthesis can further regulate binding affinity and molecular accessibility.

However, most reported studies attribute tetracycline response primarily to fluorescence intensity changes without quantitatively separating molecular adsorption from photophysical quenching. Consequently, high apparent sensitivity does not necessarily indicate true molecular recognition. Selectivity evaluation against structurally related antibiotics and potential interferents provides essential evidence, but many reports remain limited to individual competing species rather than complex multicomponent environments.

Future CQD sensor design should therefore move beyond fluorescence‐response optimization toward rational control of recognition interfaces. Integrating surface functionalization strategies, computational interaction analysis, binding studies, and spectroscopic validation could establish clearer structure–recognition–signal relationships and enable the development of more selective and predictable CQD‐based tetracycline sensing platforms.

4.6. Comparative Appraisal of Translational Readiness Across Reported CQD Sensors

Although reported CQD sensors demonstrate progressively improved sensitivity, response speed, and compatibility with complex samples, their translational readiness remains uneven. A central limitation is that analytical performance is usually established using laboratory‐spiked samples subjected to dilution, filtration, protein precipitation, or other pretreatment procedures. These steps improve fluorescence measurement but simultaneously reduce the chemical complexity that a sensor would encounter during routine food or environmental monitoring. Consequently, high recovery values obtained under optimized conditions cannot automatically be interpreted as evidence of operational robustness.

Cross‐study comparison is further complicated by differences in precursor chemistry, CQD purification, excitation wavelength, calibration procedure, matrix composition, and detection‐limit calculation. Systems derived from rice residues, mulberry leaves, amino acids, marine biomass, and industrial waste are frequently compared through individual performance indicators despite substantial differences in surface chemistry and analytical protocols [70, 73]. Lower detection limits may therefore reflect favorable experimental conditions or calculation methods rather than intrinsically superior sensor design. Storage stability, batch‐to‐batch variation, and performance across independently synthesized CQD batches are also rarely evaluated.

Sustainability constitutes another dimension of translational readiness. Biomass‐ and waste‐derived CQDs are commonly described as environmentally favorable because of their precursor origin. However, hydrothermal energy requirements, purification solvents, precursor variability, waste generation, and end‐of‐life behavior are seldom included in the assessment. Thus, environmental claims should be supported by a broader process‐level evaluation rather than precursor selection alone.

Multifunctional CQDs capable of responding to tetracyclines and additional targets such as Fe³⁺ may support broader environmental screening [70]. Nevertheless, overlapping quenching pathways can increase calibration uncertainty and reduce analyte discrimination when multiple responsive species coexist. Multifunctionality should therefore be evaluated through multicomponent mixtures rather than independent single‐analyte tests.

Taken together, the existing evidence supports technical feasibility but not yet routine deployment. Advancement will require validation using naturally contaminated samples, independent batches, reference analytical methods, prolonged storage, realistic operating conditions, and interlaboratory testing. These unresolved translational requirements provide the basis for the future‐oriented priorities discussed in Section 5.

5. Beyond Fluorescence Optimization: Toward Standardized, Intelligent, and Field‐Deployable CQD Sensing Platforms for Tetracycline

5.1. Fundamental Limitations of Current CQD‐Based Fluorescent Tetracycline Sensors

Despite the rapid expansion of CQD‐based fluorescent platforms for tetracycline detection, the field remains structurally constrained by several fundamental limitations that are often underemphasized in primary reports. First, most sensing systems are still dominated by static laboratory validation rather than dynamic, real‐world operational testing. Although reported detection limits span from micromolar to sub‐micromolar levels, these performance metrics are frequently derived under idealized aqueous conditions that fail to reflect the complexity of food and environmental matrices.

A second limitation concerns the overreliance on fluorescence intensity variation as the sole analytical output. The majority of reported CQD systems operate through “turn‐off” mechanisms based on inner filter effects or nonspecific quenching pathways [53, 75]. Such mechanisms, while experimentally convenient, are inherently vulnerable to false positives arising from overlapping absorption species in complex samples. Even systems demonstrating dual‐mode or enhanced quenching efficiency still rely heavily on intensity‐based calibration, which is susceptible to instrumental variability and environmental noise.

Another critical issue is the lack of mechanistic standardization across studies. Although similar quenching phenomena are repeatedly attributed to inner filter effects, static quenching, or charge transfer, rigorous differentiation between these mechanisms is often absent or incomplete [8, 17]. This ambiguity limits the development of predictive design principles and reduces the comparability of different sensor systems.

Additionally, many CQD platforms exhibit insufficient long‐term stability characterization. While short‐term pH, ionic strength, or UV stability is commonly reported [72, 75], extended operational durability under continuous exposure or storage conditions is rarely addressed. This gap is particularly significant for real‐world deployment where sensor aging and surface reconstruction may significantly alter performance. Collectively, these limitations highlight a persistent disconnect between laboratory‐scale fluorescence optimization and practical analytical reliability, indicating that current CQD sensor development remains largely empirical rather than engineering‐driven.

5.2. Reproducibility, Standardization, and the Crisis of Comparative Evaluation

A major structural challenge in CQD‐based tetracycline sensing research is the absence of standardized synthesis, characterization, and evaluation protocols. Across the literature, identical sensing claims are often supported by fundamentally different synthetic routes, ranging from biomass‐derived hydrothermal methods to chemically defined molecular precursors. This methodological diversity, while scientifically rich, severely limits inter‐study comparability and reproducibility [60, 74].

For instance, nitrogen‐doped CQDs derived from rice residue, mulberry leaves, and glucose‐based systems all report high fluorescence performance and tetracycline sensitivity, yet variations in quantum yield, emission wavelength, and detection limits are substantial. These discrepancies are rarely critically analyzed in terms of structural origin, but are instead attributed generically to “effective doping” or “surface passivation.” Furthermore, analytical performance metrics such as limit of detection, linear range, and recovery rates are not uniformly defined or experimentally standardized. Some studies report detection limits based on signal‐to‐noise ratios, while others rely on regression extrapolation or calibration curve slopes [71, 73]. This inconsistency complicates meaningful comparison and can artificially exaggerate perceived improvements in sensor performance.

Another unresolved issue is the inconsistent reporting of quenching mechanisms. Identical systems are sometimes interpreted through different mechanistic frameworks, including inner filter effect, static quenching, or combined pathways, without rigorous spectroscopic validation [70, 75]. The absence of fluorescence lifetime analysis in many studies further exacerbates this problem. Without standardized protocols for synthesis, optical characterization, and analytical validation, the field risks accumulating a large volume of non‐comparable datasets [60, 70]. This lack of harmonization not only impedes scientific progress but also delays regulatory acceptance of CQD‐based sensing technologies for food safety and environmental monitoring.

5.3. Operational Robustness, Shelf Stability, and Deployment Infrastructure

The practical adoption of CQD‐based tetracycline sensors requires systematic attention to operational properties that extend beyond fluorescence sensitivity and calibration performance. A field‐ready sensing platform must retain its optical response during synthesis‐to‐use storage, transportation, immobilization, and exposure to variable environmental conditions. However, most reported studies evaluate CQD stability over short experimental intervals and under controlled aqueous conditions. The effects of prolonged storage, temperature cycling, humidity, oxygen exposure, photobleaching, and surface reconstruction remain insufficiently characterized.

Future studies should distinguish between the stability of CQDs in solution and their behavior after incorporation into solid substrates, polymer matrices, membranes, or disposable test formats. Immobilization may improve handling and portability but can alter surface accessibility, diffusion kinetics, fluorescence quantum yield, and analyte‐binding equilibria. Substrate uniformity, reagent distribution, drying conditions, and packaging permeability should therefore be treated as controlled manufacturing variables rather than secondary fabrication details. Accelerated aging experiments should be combined with real‐time storage studies to determine usable shelf life and identify the mechanisms responsible for signal deterioration.

Deployment also requires internal quality‐control features capable of identifying invalid measurements. Reference fluorescence channels, blank zones, positive controls, and calibration verification standards could help distinguish tetracycline‐induced responses from changes caused by illumination, sensor aging, sample coloration, or environmental exposure. Such controls are particularly important for intensity‐based turn‐off sensors, where any unrelated signal reduction may produce an apparent positive result. Operational protocols should additionally define acceptable sample volume, incubation time, temperature range, pretreatment requirements, and rejection criteria.

The broader deployment infrastructure must address manufacturing consistency, transportation, user training, contamination control, data recording, and disposal of used sensing materials. Field validation should report not only successful measurements but also failure frequency, invalid‐test rates, environmental conditions, and performance variation between production batches and operators. By integrating material stability with packaging, quality assurance, and standardized operating procedures, CQD sensors can progress from portable laboratory demonstrations toward analytically dependable monitoring tools. This operational perspective is distinct from predictive material design, which is addressed separately in Section 5.4.

5.4. Future Perspectives: From Empirical Nanoprobes to Predictive Sensing Architectures

The long‐term evolution of CQD‐based tetracycline sensing will depend on transitioning from empirically optimized nanoprobes to predictive, design‐driven sensing architectures. At present, most CQD systems are developed through iterative experimental adjustment rather than rational modeling of electronic structure, surface chemistry, and analyte interaction pathways. One of the most critical future requirements is the establishment of structure–function predictive frameworks that can reliably correlate precursor chemistry, dopant configuration, and surface‐state distribution with sensing performance.

Without such frameworks, progress will continue to rely on trial‐and‐error synthesis, limiting scalability and reproducibility. In parallel, there is a need to move beyond single‐analyte detection paradigms. Although CQD systems have demonstrated selective responses to tetracyclines in controlled settings, real‐world environments contain structurally diverse antibiotics and interfering organic compounds [73, 75]. Future platforms must therefore incorporate multiplexed sensing capabilities capable of distinguishing between chemically similar species.

Another key direction involves life‐cycle and environmental impact assessment of CQD production. While biomass‐ and waste‐derived precursors are frequently presented as sustainable alternatives [74, 76], comprehensive evaluations of energy consumption, chemical usage, and post‐use environmental fate remain largely absent. Without such assessments, claims of sustainability remain incomplete. Finally, regulatory translation will require rigorous interlaboratory validation, standardized reporting frameworks, and long‐term stability testing under real environmental conditions. Only through convergence of mechanistic understanding, engineering standardization, and digital integration can CQD‐based tetracycline sensors progress from promising laboratory constructs to reliable analytical technologies suitable for global deployment.

5.5. Predictive Design of CQD Sensors Using Computational and Data‐Driven Approaches

Current CQD‐based tetracycline sensing platforms are largely developed through experimental optimization, where precursor selection, doping strategies, and surface modification are often determined through iterative trial‐and‐error approaches. Although these approaches have generated numerous high‐performance sensors, they provide limited predictive understanding of how specific structural features translate into fluorescence response, molecular recognition, and analytical reliability. Future advancement of CQD sensing therefore requires a transition from empirical optimization toward predictive materials engineering, where sensing performance can be anticipated before experimental fabrication.

Computational approaches, particularly density functional theory (DFT), provide valuable opportunities to clarify the fundamental interactions governing CQD–tetracycline recognition. DFT calculations can reveal adsorption configurations, binding energies, charge redistribution, frontier molecular orbital alignment, and electronic interactions between tetracycline molecules and chemically modified CQD surfaces. Such information can help identify which functional groups, defect states, or heteroatom configurations promote favorable analyte interactions and efficient fluorescence modulation. Combining computational predictions with spectroscopic validation may provide a more reliable interpretation of quenching pathways and distinguish genuine molecular recognition from nonspecific optical attenuation.

Machine learning (ML) represents another emerging strategy for accelerating CQD sensor development by establishing relationships between synthesis parameters, structural descriptors, and sensing performance. Input variables such as precursor composition, reaction conditions, elemental composition, surface functional groups, particle size distribution, and optical characteristics can be integrated into predictive models to estimate analytical outputs, including sensitivity, selectivity, stability, and matrix tolerance. Recent progress in machine learning‐assisted carbon dot synthesis and analysis highlights the potential of data‐driven approaches to identify hidden relationships between preparation conditions and material properties, although reliable implementation still requires standardized datasets and comparable characterization protocols [77].

High‐throughput screening combined with computational modeling and automated experimentation could further accelerate the discovery of optimized CQD architectures. Instead of evaluating individual CQD formulations sequentially, large libraries of precursor–dopant–surface combinations could be systematically screened to identify candidates with desirable electronic and recognition properties. Studies on tunable fluorescent graphene quantum dots demonstrate that controlling electronic structure and surface characteristics can enable application‐specific optical responses, providing valuable design principles for future CQD sensing systems [78]. Moreover, advances in multifunctional carbon‐based nanomaterials suggest opportunities for integrating sensing with additional analytical or biomedical functions, although application‐specific validation remains necessary [79].

Ultimately, predictive CQD sensing will depend on the integration of molecular‐level understanding, standardized experimental databases, computational modeling, and artificial intelligence‐assisted optimization. Establishing reliable structure–property–function relationships will allow CQD sensors to evolve from experimentally optimized fluorescence probes into rationally designed analytical platforms with predictable performance under complex real‐world conditions.

5.6. From Laboratory Validation to Real‐World Deployment

Despite substantial progress in improving CQD‐based tetracycline sensing performance, the transition from laboratory‐scale demonstrations to reliable real‐world applications remains a major challenge. Most reported CQD sensors are evaluated under controlled conditions using prepared solutions or spiked samples, where matrix complexity, environmental variability, and operational uncertainties are minimized. Although such studies provide important mechanistic insights and demonstrate analytical feasibility, they do not fully represent the conditions encountered during routine food safety monitoring or environmental surveillance.

A critical requirement for practical deployment is the validation of CQD sensors using naturally contaminated samples with minimal pretreatment. Real matrices contain diverse interferents, including proteins, organic molecules, inorganic ions, and suspended particles, which may alter tetracycline availability, fluorescence response, and calibration accuracy. Therefore, future studies should prioritize matrix‐matched calibration, comparison with established reference methods such as HPLC or LC–MS, and independent validation across different sample sources.

Scalable manufacturing and reproducibility also represent essential barriers to translation. While many CQDs exhibit excellent laboratory performance, differences in precursor composition, reaction conditions, purification procedures, and surface chemistry can lead to significant batch‐to‐batch variation. Standardized synthesis protocols, quality‐control criteria, and long‐term stability assessments are required before CQD sensors can be considered for commercial implementation.

Future deployment will further depend on integration with practical sensing platforms, including portable devices, smartphone‐assisted analysis, and automated data‐processing systems. However, technological integration alone cannot guarantee reliable operation without appropriate calibration strategies, quality‐control mechanisms, and user‐independent performance evaluation. Ultimately, successful translation of CQD‐based tetracycline sensors will require a multidisciplinary approach combining rational material design, standardized analytical validation, scalable fabrication, and realistic field testing. Such efforts will enable the evolution of CQD sensors from promising laboratory probes into dependable analytical tools for food safety and environmental monitoring.

6. Conclusion

CQD‐based fluorescent sensors have emerged as a versatile analytical platform for tetracycline detection in food and environmental systems, driven by continuous advances in precursor engineering, heteroatom doping, and surface‐state modulation. Despite significant improvements in sensitivity, with detection limits reaching the nanomolar to sub‐micromolar range, the fundamental sensing performance remains strongly dependent on non‐standardized synthetic routes and poorly unified photophysical interpretations. Mechanistic ambiguity in fluorescence quenching, particularly the overlapping roles of inner filter effects, static interactions, and charge‐transfer processes, continues to limit predictive sensor design.

Comparative evaluation of reported systems reveals that while biomass‐derived and heteroatom‐doped CQDs demonstrate promising analytical recoveries in real matrices such as milk, honey, and water, most studies still rely on controlled laboratory conditions rather than complex field environments. Furthermore, although portable and smartphone‐assisted platforms represent a significant step toward practical deployment, issues related to calibration instability, matrix interference, and lack of standard protocols remain unresolved.

From a broader perspective, current CQD‐based tetracycline sensors are still largely empirical rather than rationally engineered systems. Future progress will depend on integrating mechanistic photophysical understanding with reproducible synthetic strategies and standardized analytical validation frameworks. The transition from laboratory‐scale fluorescence probes to robust, field‐deployable, and digitally integrated sensing platforms is essential for real‐world implementation in food safety and environmental monitoring applications.

Author Contributions

Monika Verma: formal analysis, data curation. Kamel A. Saleh: conceptualization, investigation, writing – original draft. Irwanjot Kaur: formal analysis, resources, writing – original draft. Yodgor Kenjaev: investigation, writing – review and editing. Ahmed Aldulaimi: methodology, writing – review and editing. Nada Othman Kattab: visualization, supervision, writing – review and editing. Rasulbek Eshmetov: writing – review and editing, visualization. M. M. Rekha: investigation, writing – original draft, data curation. Shayan Mahmoodi: conceptualization, writing – review and editing, project administration, supervision.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

This article is a review and does not include any new experimental data. All data discussed and analyzed are derived from previously published studies, which are appropriately cited in the manuscript.