Hierarchical Plasmonic Au@ZnO Chemosensor Enhanced the Sensitivity and Detection Limit of Pb²⁺ Metallic Ions

Abstract

Pb²⁺ contamination poses significant environmental and health risks that can be detected from Au-doped ZnO (Au@ZnO) nanograins as selective and sensitive chemosensors. Microstructural analysis reveals that the crystallite size and bandgap decreased from 18 to 9 nm and from 3.2 to 2.91 eV, while the strain increased from 3.3 × 10^–3 to 6.39 × 10^–3 as the Au concentration increased from 0 to 5 at. %, respectively, and further confirmed by DFT calculations. XPS analysis confirmed the substitution of Zn with Au, inducing tensile stress and enhancing charge transfer. Localized surface plasmon resonance (LSPR) effects improved the light absorption and carrier generation with the highest Pb²⁺ detection limit (1.78 mM at 369 nm for Au = 2 at. %). Recent studies demonstrated the selectivity and stability across four cycles in the presence of competing ions (Co²⁺, Cd²⁺, and Hg²⁺). These findings of Au2@ZnO established a promising platform for Pb²⁺ detection, offering stability, sensitivity, and operational longevity for environmental remediation and heavy metal monitoring.

1. Introduction

Lead (Pb²⁺) is one of the most toxic pollutants that negatively affects all living entities, including humans, birds, and animal organs, that can enter the human body through the skin, respiratory, or digestive systems, leading to various neurological, breathing, urinary, and cardiovascular disorders, which is attributed to immune modulation, oxidative, and inflammatory mechanisms. Initially, Pb²⁺ triggers inflammatory responses, disrupting oxidant–antioxidant systems and physiological functions. Pharmaceutical systems should be considered the quantitative permissible level of heavy metallic contaminations, which is also included in ayurvedic medicines. According to the Centers for Disease Control and Prevention (CDCP), USA, the standard Pb levels in the blood are requisite of 10 μg/dL for adults and 5 μg/dL for children. Overcoming such a furious problem has led to the development of sensitive and efficient systems for evaluating and/or removing metallic ions for a sustainable environment.

Few analytical approaches have been employed to estimate the quantitative level of metal ions in an aqueous system, particularly edible things, such as atomic absorption spectrometry (AAS), UV–visible spectroscopy, ICP-OES, anodic stripping voltammetry­(ASV), pH, and ionchromatography (ICM). Nanostructured metal oxides (ZnO, MnO₂, MoO₃, SnO₂, Fe₂O₃, In₂O₃, TiO₂, and CuO) have extensively been employed for the detection of metal ions due to their advantageous properties, such as nontoxic, cost-effective, ease of fabrication, and environmentally friendly. , Among metal oxides, ZnO is preferred owing to its wide bandgap (3.37 eV), high excitonic binding energy (60 meV), exhibiting enhanced mobility of conduction electrons, and showcasing stability both physically and chemically. Various surface morphologies (nanowires, nanorods, nanosheets, and quantum dots) of ZnO can be produced using diverse techniques, including hydrothermal, thermal evaporation, and metal-catalyzed growth.

Chemosensors are analytical systems designed to reversibly bind target analytes under specific experimental conditions, producing measurable optical signals in response. These systems primarily rely on noncovalent interactions, such as hydrogen bonding and electrostatic forces, for analyte recognition. Additionally, metal complexes capable of forming labile and readily exchangeable bonds with analytes can also act as effective chemosensors. Unlike molecular probes, which provide a static snapshot of a sample’s composition, chemosensors dynamically adjust to changes, enabling real-time monitoring of various (bio)­chemical and (bio)­physical processes, such as enzymatic reactions and analyte diffusion through membranes. This adaptability makes chemosensors highly versatile tools for continuous analysis. With applications spanning the detection of heavy metals, pollutants, and biomolecules, chemosensors play a crucial role in environmental safety, food quality assurance, and health diagnostics. However, their effectiveness can be challenged by interference from complex matrices and issues of reproducibility. To address these limitations, advancements focus on integrating chemosensors with portable devices, improving multianalyte detection capabilities, and incorporating artificial intelligence for efficient data analysis. These developments are positioning chemosensors as indispensable tools in modern science and technology, potentially revolutionizing dynamic and precise monitoring across various fields.

Plasmonic nanostructures of gold (Au), silver (Ag), copper (Cu), and aluminum (Al) nanoparticles (NPs) have become a crucial category of optically active materials owing to their high UV–vis optical cross sections, thus resulting in enhancement of oscillating electric fields around and within the nanostructures. Plasmonic NPs can focus light energy at their surface utilized in numerous applications, including surface-enhanced Raman spectroscopy (SERS), the enhancement of second harmonic generation, and improved sensing of metal ions. Recently, surface plasmon-enhanced emission (SPE) has received significant interest in sensing due to increased optical scattering rates from molecules within the plasmon-induced electric field. AuNPs are extensively used in biological analysis and gas sensing, especially recent biochips and Localized LSPR sensor applications. Palani et al. explored the spectral and sensing properties of various AuNP (spheres, rods, and bipyramids), emphasizing the role of spectral heterogeneity in enhancing the performance of LSPR-based sensors in the spectral domain. Farooq et al. developed a novel, label-free LSPR immunosensor with spherical AuNPs, capable of detecting dengue NS1 antigen at a quantification limit of 0.07 μg/mL (1.50 nM), presenting a new paradigm for immunosensor design. These materials are investigated for their potential to estimate the sensing of metallic ions. The incorporation of ZnO and Au in the produced microstructure has attracted significant interest due to the SERS functionalities of each component, even though the sol–gel hydrothermal process has been preferred to synthesize nanostructured ZnO due to the ease of dopant concentrations and the alternation/tunning of the microstructure and optical characteristics with controlled growth parameters. Chou et al. deposited the AuNP-modified ZnO thin films on ITO glass substrates using chemical bath deposition (CBD) and investigated the LSPR peak tuning (redshift) in four different refractive media from 524, 534.5, 535.5, and 539 nm, corresponding to air (1.00), water (1.33), ethanol (1.36) and methanol (1.44), respectively. Kim et al. fabricated the fiber-optic-based LSPR sensors with AuNP-ZnO nanowires and achieved 171% response concerning the refractive index with LODs of 2.06 pg/mL for 2D and 0.51 pg/mL for 3D of the prostate cancer. Gogurla et al. reported enhanced UV photodetection and tunable light-induced NO gas sensor using nanostructured Au@ZnO, where the LSPR effect enhanced the sensitivity over CO and VOCs under the visible region with an LOD of 0.1 ppb at 335 nm. The LSPR effect of Au is well-studied with ZnO and highlights the sensitivity of Au@ZnO nanocomposites for the detection of gases and biomolecules. Despite the existing study of nanostructured Au@ZnO for various sensors, few literature is available for metallic detection. Therefore, it is indeed required to utilize and establish Au@ZnO chemosensors for metallic ion detection in edible things with high LOD and sensitivity.

In this paper, Au@ZnO nanograins were synthesized using the hydrothermal method in a single step, with varying Au concentrations (0–5 at. %). X-ray diffraction (XRD) peak profile analysis determined the crystalline phase and structural parameters. The superficial microstructure of Au@ZnO was confirmed by field emission-scanning electron microscopy (FE-SEM) and high-resolution-transmission electron microscopy (HR-TEM). The crystalline structure of Au@ZnO was also confirmed by the selected area electron diffraction (SAED) pattern. The bandgap (E _g) of nanostructured Au@ZnO was calculated from the Tauc’s plot. X-ray photoelectron spectroscopy (XPS) determined the elemental composition and chemical states. Microstructural and optical parameters of synthesized materials were also estimated from DFT calculations that verified the experimental one. An extensive analysis of the sensing parameters of Au@ZnO is conducted for the accurate and reliable quantification of metallic ions. The selectivity of the material for specific metal ions and/or to the material, its sensitivity with varying metal ion concentrations, LOD, and the stability of the assay over an extended period of time. Microstructural and optical parameters of synthesized materials were also estimated from DFT calculations that verified the experimental one. An extensive analysis of the sensing parameters of Au@ZnO is conducted for the accurate and reliable quantification of metallic ions. The selectivity of the material for specific metal ions and/or to the material, its sensitivity with varying metal ion concentrations, LOD, and the stability of the assay over an extended period of time are measured using a UV–vis spectrophotometer.

2. Materials and Methods

Analytical-grade reagents and precursors of Zn, zinc nitrate hexahydrate (Zn (NO₃)₂·6H₂O), the dopant hydrogen tetrachloroaurate [III], HAuCl₄, and the surfactant hexamethylenetetramine (HMT) were purchased from Sigma-Aldrich, Bangalore, India and used without any further purification. The deionized (DI) water was used throughout the experimental process to clean the glassware and/or for the nucleation and growth processes of nanostructured materials.

2.1. Synthesis and Characterization of Au@ZnO

Au@ZnO nanograins were synthesized at 180 °C by using the hydrothermal precipitation method. First, the 0.1 M solution of a Zn precursor and HMT was prepared in 40 mL of DI water at room temperature (RT). The prepared solution was transferred to an inline stainless steel Teflon autoclave. The sealed autoclave was then kept in an electric oven, heated to 180 °C for 8 h, and allowed to cool at RT after the nucleation and growth process. The obtained white precipitates were filtered and washed several times with DI water to remove nitrate ions. These filtered solid precipitates were dried in an oven at 60, 80, and 300 °C for 1, 2, and 3 h, respectively, to eliminate the organic residuals. Here, we have fixed the solution’s mole concentration to 0.1 M and varied the dopant concentration (Au = 0, 1, 2, 3, 4, and 5 at. %) to investigate the effect of dopants on the material properties Au@ZnO (Figure a), and the synthesis process is shown in the Figure . The crystal structure modeling, band structure analysis, the density of states, and electron density were also confirmed by the DFT calculations (NanoDcal software) (Figure b). Superficial microstructures of the prepared Au@ZnO were investigated by field emission-scanning electron microscopy (FE-SEM: JEM-7600/JEOL) (Figure c). The crystal structure, dislocation density, and lattice spaces of prepared samples were estimated from X-ray diffraction (XRD: D/MAX-2500/pc/Rigaku). The electronic structure and electrochemical bonding states were investigated using X-ray photoelectron spectroscopy (XPS: Axis Ultra/Kratos) survey and core-level elemental analysis. UV–vis (5000 UV–vis–NIR spectrophotometer/Varian Cary) measurements were conducted to analyze the selectivity of metal ions with the schematic illustration for the detection mechanism (Figure d).

1.

Schematic illustration of the (a) synthesis process (growth and nucleation), (b) simulation, (c) microstructure, and (d) absorbance measurement for the detection of metallic ions (Cd, Co, Hg, and Pb) using the typical nanostructured Au@ZnO.

2.

Synthesis process of ZnO and Au@ZnO nanograins.

2.2. DFT Calculations

To understand the structural properties of Au@ZnO, DFT calculations were used to predict the density of states, band structure, and electronic states of ZnO and Au@ZnO. It is estimated for the analysis of the density of states, band structure, and electronic states of ZnO and Au@ZnO.

2.3. Selectivity of Au@ZnO for Metallic Ions

Examining the selectivity of Au@ZnO for the precise identification of metallic ions is essential for improving the existing analytical methods. To assess the selectivity of synthesized nanomaterials in the assay of detecting metal ions in aqueous solutions, It was examined the changes in the SPR maxima (λ_max) and bandwidth (Δλ) of Au@ZnO. Stock solutions of different metallic concentrations (Co²⁺, Cd²⁺, Pb²⁺, and Hg²⁺) were prepared in DI water and tested UV–vis absorption to determine the best selectivity of the material. In a standard experiment, a 10 mM Au@ZnO concentration was individually mixed with four distinct metallic ions of a 1 mM concentration disseminated in 10 mL of DI water of total volume. UV–vis absorption spectra of the prepared solutions were taken after allowing the interaction of different metallic ions with the AuNP probes for 20 min.

2.4. Sensitivity of Au@ZnO

To determine the quantitative concentration of Pb²⁺ or other ions, the particular metallic concentrations were individually added to a separate sample of DI water containing 10 mM Au@ZnO in 5 mL. The Pb–Au@ZnO solutions were thoroughly mixed and then incubated for 20 min at ambient temperature (25 °C) while observing absorbance intensity and spectrum. Following the incubation process, the reaction mixtures were transferred to the sample holder for the measurement of UV–vis absorption in the 1.0–4.5 mM range. Calibration tests for Pb²⁺ were performed in triplicate, and the LOD was estimated to evaluate the sensitivity of the Au@ZnO. The LOD was estimated using the formula 3σ/k, σ denotes the standard deviation of the blank sample, and k represents the slope relating the absorbance response to the concentration range of Pb²⁺.

2.5. Stability of Au@ZnO

To evaluate the stability of the sample, 10 mM aliquots of Au@ZnO nanograins were dispersed in DI water, and observed the detection at ∼369 nm. Consequently, various Pb concentrations (2, 3, and 4 mM) were added to the Au@ZnO solution, and a detection peak was observed at ∼369 nm. Therefore, the stability of the chemosensor was assessed by recording UV–vis absorbance spectra of Au@ZnO solutions with different concentrations of Pb²⁺ (2, 3, and 4 mM) over an extended period ranging from 20 to 120 min. These studies verified the swiftness and robust stability of ZnO-based chemosensors over a long time span at various Pb²⁺ concentrations.

3. Results and Discussion

Diffraction peaks of ZnO nanograins were observed at 31.8, 62.86, 66.40, 67.91, 69.15, 72.69, and 79.95° corresponding to planes (100), (002), (101), (102), (110), (103), (200), (112), (201), (004), and (202), respectively (Figure a). The hexagonal wurtzite crystal structure of ZnO nanograins matched the standard of JCPDS card no. of ZnO (Card no.89-7102). The absence of additional diffraction peaks corresponding to any other phases of ZnO or Au peaks in the XRD pattern further confirmed the purity of ZnO. For Au@ZnO powders named Au1@ZnO, Au2@ZnO, Au3@ZnO, Au4@ZnO, and Au5@ZnO, the diffraction peaks were observed at (100), (002), (101), (102), (103), (200), (112), (201), (004), and (202) planes similar to bulk ZnO powder. They exhibited the wurtzite hexagonal phase of ZnO along with additional peaks of Au [(111), (002), (220)] detected in the XRD pattern and represented by the star (*). Other than the characteristic peak, the absence of additional Au peaks in the XRD pattern can be attributed to the successful replacement of Zn sites by Au atoms without significantly altering the host material’s crystal structure. This implies that Au atoms are substituting at Zn sites rather than forming a separate phase, thereby preserving the host material’s overall structural integrity and physical properties. While increasing the Au concentration in the ZnO lattice, the diffraction peak intensity of the XRD pattern gradually increases. For doped ZnO, the intensity of XRD initially decreases with increasing Au dopant concentration due to crystal imperfections, lattice distortion, and the introduction of defects, which disrupt the crystal structure and weaken the diffraction signals. By increasing the dopant concentration, the intensity decreases, but a slight increase in intensity can occur at higher concentrations. This is often done due to recrystallization or defect healing, where the lattice becomes more ordered or the saturation of defect sites stabilizes the structure. In some cases, secondary phase formation can also contribute to this slight increase in the intensity. The average crystallite size of Au@ZnO was estimated from Scherrer’s formula: ,

$$D=0.94\frac{\lambda }{\beta \cos \theta }$$ 1

where D represents the average crystallite size (nm), the value 0.94 was considered for spherical shape, β is the full width at half-maximum (fwhm) of the most intense peak, θ is the diffraction angle in radian, and λ is the wavelength (nm) of the X-ray source (0.1504 nm). The most plentiful peak corresponds with the XRD pattern of Au@ZnO nanograins, which were used to estimate the average crystallite size. Figure b shows the variation of fwhm (β) (left Y-axis), strain (τ) (second right Y-axis), and crystalline size (D) (third right Y-axis) of Au@ZnO nanograins. The τ increased from 3.3 × 10^–3 to 6.39 × 10^–3 as the Au concentration increased from 0 to 5 at. %. The crystalline size of Au@ZnO decreased from 18 to 9 nm as the Au concentration increased from 0 to 5 at. % due to the increment of strain, which affects the arrangement of atoms and inhibits the crystal growth. The decreasing D and increasing τ of Au@ZnO are attributed to improvements in the nanostructure. This observation highlights the significant disparity in atomic radii between the Au (144 pm) and Zn (133 pm), contingent upon the coordination number. Therefore, the crystal induces strain, which causes the vacancies surrounding Au atoms. These vacancies are necessary for charge compensation due to the predominant presence of Au in the structure. The crystal strain was also estimated from the WH-plot; it is clear that the stress was observed to be tensile, which is also established by the fact that the atomic radii of Au are more significant than the Zn. The effect of this strain is produced by replacing the Zn site with Au. Au replacement in the stoichiometry of ZnO at the sites of Zn and the impact of tensile stress on the crystal structure are explained further in FE-SEM and XPS characterization.

3.

(a) XRD pattern of Au@ZnO (Au1@ZnO, Au2@ZnO, Au3@ZnO, Au4@ZnO, and Au5@ZnO). (b) Variation of the full width at half-maximum (fwhm), crystallite size (D), and strain (τ). (c) W–H plot of the Au2@ZnO sample.

3.1. Microstructure Analysis

Figure a–c shows the typical surface morphologies (FE-SEM images) of ZnO NPs, Au2@ZnO, and Au4@ZnO, respectively. For the nucleation and growth of pure ZnO NPs, a very uniform manner in the form of spherical shapes can be seen, where the absence of any additional peak in the XRD pattern confirmed the purity of ZnO. Figure b,c shows the hexagonal perfectly available nanograins of Au@ZnO, which was achieved by applying similar growth conditions of ZnO. As Au dopant concentration increased, the strain also increased, submicrometer cracks and pores expanded, and the cracks became more pronounced, decreasing the particle size.

4.

Microstructures of nanostructured ZnO: (a) ZnO, (b) Au2@ZnO, and (c) Au4@ZnO. The BF-TEM, HR-TEM, and SAED pattern of ZnO (d, g, and j) ZnO (e, h, and k) Au2@ZnO, and (f, i, and l) Au4@ZnO.

Figure d–f shows the bright field-TEM micrographs (BF-TEM images) of ZnO, Au2@ZnO, and Au4@ZnO, respectively. NPs have a spherical and hemispherical morphology, and their size varied as a function of the dopant concentration (Au = 0–5 at. %). The nanoparticles’ size was measured directly from the TEM analysis. Smaller NPs were obtained as the Au concentration increased, while the largest NPs belonged to pure ZnO. A more comprehensive TEM analysis was performed on the ZnO NPs and Au@ZnO aggregates. Figure g–i corresponds to HR-TEM images of a ZnO, Au2@ZnO, and Au4@ZnO nanograins, revealing the hexagonal wurtzite phase of ZnO.

Figure j–l shows the SAED pattern of the ZnO, Au2@ZnO, and Au4@ZnO nanograin aggregates. Diffraction ring patterns illuminate and become more ordered as the concentration of Au increases. These results indicate that the crystallinity of ZnO NPs increases and shifts toward becoming more crystalline. The concentration of Au dopant affects the crystallinity of ZnO NPs. Increasing the concentration of Au enhances the formation rate of ZnO NPs, increasing the crystallinity.

3.2. Chemical States and Elemental Analysis

A UV–vis-diffused reflectance spectroscopy (DRS) measurement was performed to investigate the optical bandgap of Au@ZnO nanograins. The bandgap, E _g, of Au@ZnO, was calculated from Tauc’s plot, and subsequently, the Kubelka–Munk method was used to translate the reflectance to absorption spectra. The Tauc’s relation is given as follows:

$$\alpha =\frac{A{(h\nu -E_g)}^{1/n}}{h\nu }$$ 2

where A, α, hν, and E _g denote the proportionality constant, absorption coefficient, energy of incident radiation, and bandgap energy, respectively. The value of “n” characterizes the nature of electronic transition, such as n = 1/2 for the direct electronic transitions. The E _g of Au@ZnO was assessed from the Tauc’s plot [(αhν)^1/n vs hν].

The E _g of bare ZnO NPs was observed to be ∼3.2 eV, and it further decreased from 3.20 to 2.91 eV as the Au concentration increased (Figure a). Strong quantum confinement and an elevation in their surface area-to-volume ratio caused a drop in E _g. The presence of Au within the Zn site of the ZnO lattice is confirmed by an increase in redshift and a decrease in E _g. The elemental composition and chemical states of Zn, O, and Au were analyzed via an XPS survey to study the interaction between ZnO and Au (Figure b). The Zn 2p3, O 1s, C 1s, and Au 4f peaks were observed in the spectrum. Figure c shows the core level spectrum of Zn 2p3 for ZnO, where the deconvoluted peaks of Zn 2p at Zn 2P _1/2 and Zn 2P_3/2 were observed at 1021.25 and 1044.17 eV, respectively, which coincides with the findings for Zn²⁺ bound to oxygen in the ZnO matrix. In Au-doped ZnO samples, the peaks of Zn 2p are slightly shifted toward the high-energy region. By the addition of Au in ZnO, the electron density of ZnO decreases, and the binding energy increases. Hence, the binding energy peak shifts positively. For O 1s core level, two types of bonds related to oxygen are observed at 532 eV (OI), corresponding to unavoidable oxygen ions chemisorbed or adsorbed from O₂ and H₂O, and the other is at ∼530 eV (OII) attributing to O^2– in wurtzite ZnO (Figure d). For O 1s core level, two different types of oxygen-related bonds are seen: one is at 530 eV (OII), which is attributed to O^2– in wurtzite ZnO, and the other is at 532 eV (OI), which corresponds to unavoidable oxygen ions chemisorbed or adsorbed from O₂ and H₂O. The peak position of OI is unaffected by the mole concentration of Au@ZnO aqueous solution because OI is related to the unavoidable O₂ and H₂O during the hydrothermal process. Nonetheless, as the aqueous mole concentration increases, the peak position of the OII shifts gradually to the region of higher binding energy. Figure e shows the deconvoluted Au 4f core level spectrum peaks for nanostructured Au@ZnO. The figure illustrates the resolution of the Zn 3p binding energy for both Au@ZnO and ZnO samples, which displays many peaks associated with Zn 3p_3/2 (88.1 eV), Zn 3p_1/2 (90.7 eV), Au 4f 7/2 (82.70 eV), and 4f 5/2 (86.65 eV). The figure demonstrates that the binding energy peak location of Zn 3p is shifting toward higher binding energy, suggesting that the chemical state of Zn remains stable despite the presence of Au on the sites of Zn in the complex structure of ZnO augmented to the XRD pattern. The figure demonstrates that the binding energy of Au 4f is pushed toward lower values than pure gold (4f 7/2, 84.00 eV and 4f 5/2, 87.71 eV). The observed shift can be attributed to generating Au NPs with a negative charge, which lacks any chemical interaction with ZnO and exhibit a donor level almost equivalent to the Fermi level of Au, which is 5.4 eV. Consequently, it is plausible that electron transfer might occur from ZnO to Au, resulting in an increase in the charge density on the surface of Au NPs. The chemical shift observed in the Au 4f and O 1s levels from XPS has clearly demonstrated the oxidation of Au, revealing that the resulting oxide is Au₂O₃, which is more stable than that of Au₂O. The increased stability of Au₂O₃ occurred due to a greater degree of hybridization between Au 5d and O 2p states across the valence band region compared to Au₂O. , Additionally, as the oxide forms, there is a slight increase in the E _g with an increase in the dopant concentration. Therefore, the enabled material of Au@ZnO is suitable for detecting metal ions.

5.

(a) Bandgap energy (E _g) for pure ZnO and Au@ZnO. (b) XPS full spectra of the core level for ZnO and Au@ZnO (prepared by using 0, 1, 2, 3, 4, and 5 at. % doping). XPS spectra of the core level for the ZnO and Au-ZnO samples, (c) Zn 2p3, (d) O 1s, (e) Au 4f, and Zn 3p.

3.3. DFT Calculations

The crystal structures of undoped ZnO and Au@ZnO heterostructures were constructed, and then their energy band diagram, density of states (DOS), and electron density were estimated using the first-principles density functional theory (DFT). The ZnO structure is shown in Figure a, where the lattice constants a = b = 3.2500 Å and c = 5.2060 Å, the bond angle α = β = 90° and Υ = 120°. These results agree well with the experimental results, where a = b = 3.248 Å and c = 5.2056 Å, α = β = 90° and Υ = 120°. We performed all DFT calculations using the NanoDcal software. We used the supercell approach, and as such, we have modeled structures of ZnO (wurtzite structure, space group P6₃mc). In this case, the Au ion was substituted for a regular Zn ion. In the following analysis, we refer to this defect as the Au ⁿ Ox complex, where n denotes the oxidation state, and x is the number of oxygen ions adjacent to Au. In the wurtzite structure, Zn has the four nearest O ions. Thus, we modeled Au surrounded by four host oxygen ions. Based on the optimized configuration of ZnO, the Au@ZnO heterostructure was designed (Figure a) with a lattice parameter similar to the Au@ZnO nanostructure, which provides a complete depiction of their atomic arrangements.

6.

Atomic structure models simulated using DFTs of ZnO and Au@ZnO (a), energy band structures of ZnO and Au@ZnO (b), DOS of ZnO and Au@ZnO structures (c), and electron density of ZnO and Au@ZnO (d).

The energy band structure and density of states of ZnO and Au@ZnO heterostructures are shown (Figure b,c). For ZnO, the distance between the conduction band’s minimum and the valence band’s maximum indicates an indirect bandgap nature. However, when Au is incorporated into the ZnO matrix, additional electronic states are introduced that facilitate easier electron transitions between the valence and conduction bands, thereby enhancing the overall conductivity of the material on a macroscopic scale. The DFT-calculated bandgap for Au@ZnO was observed to be 2.90 eV, which was smaller than the experimental value of 3.22 eV. The discrepancy between the DFT-calculated bandgap and experimental values occurred due to the approximations involved in the DFT calculations, such as the exchange-correlation functionals used to describe the electron–electron interactions. Different functionalities can yield slightly different electronic structures and bandgaps compared to experimental values. ,

The DOS of Au@ZnO reflects the combined electronic states of the Au and ZnO components. When these components are combined into a heterostructure, their DOS profiles interact to create new electronic states and modify the band alignment. The interactions between Zn 2p and Au 4f states collectively narrow the maximum band value compared with undoped ZnO (Figure c,d). This interaction facilitates efficient charge transfer pathways across the interface, enhancing the conductivity and potentially altering the optical properties of the composite material.

The electron density of Au@ZnO, as shown in Figure d, provides insights into electron localization, which significantly impacts properties such as electrical conductivity and electron transfer capability. In the ZnO structure, electron localization is minimal, which increases for Au@ZnO, illustrating the importance of Au incorporation. The increased electron delocalization indicates that the structural modifications substantially enhance the electron transport capacity of Au@ZnO. These modifications showcase the efficient charge transfer ability of Au@ZnO, which is crucial for applications such as catalysis, energy storage, sensing, and electronics. The introduction of Au into ZnO thus represents a strategic approach to tailor its electronic properties, aiming to optimize the performance characteristics beyond those achievable with ZnO alone. These advancements underscore the potential of composite materials in pushing the boundaries of functional materials engineering.

3.4. Selectivity of Material with Varied Molarity

UV–vis absorption spectra of different samples of Au@ZnO with 0, 1, 2, 3, 4, and 5 at. % doping with different molarities are analyzed for the selectivity of the material. The absorption intensity of the Au2@ZnO sample is higher in all six samples (Figure a–c). The spectrum of the Au2@ZnO sample clearly illustrates two prominent peaks: one in the UV region, around 369 nm, and the other in the visible region, around 550 nm. The peak in the UV region originates from the band edge absorption of ZnO, while the peak in the visible range is attributed to the surface plasmon absorption of the Au NPs. The characteristic plasmon peak of the Au@ZnO nanocomposite was broad in the visible region. This broad visible absorption does not exhibit any shift in the plasmon band with an increasing reaction time due to the wide particle size distribution of Au@ZnO nanocomposites. As the dopant concentration increases, doping levels increase, and the LSPR effect diminishes. This attenuation can be attributed to the introduction of additional free carriers or impurities, through doping, which can enhance the scattering and damping of plasmon oscillations. Furthermore, the formation of oxides or other compounds during the doping process can modify the electronic structure and dielectric environment, further reducing the efficacy of the LSPR effect.

7.

(a–c) UV–vis absorbance spectra of Au@ZnO with three different molarities of the material. (d) UV–vis absorbance spectra of the interaction of Au@ZnO with four different metal ions.

3.5. Selectivity to Metal Ions

We examined the UV–vis absorption spectra of Au2@ZnO (10 mM) responding to the different metal ions to learn about their sensing capabilities (Figure d). There was an absorption band of Au2@ZnO pure solution prepared in DI water at 369 nm. A new absorption band with a relatively strong absorption strength of about 971 nm emerged following the introduction of Pb²⁺ (Figure a). Adding other metal ions to the solution made no additional absorption bands visible. These findings indicated that Au2@ZnO showed the highest selectivity and sensitivity for Pb²⁺ in DI water. The UV–vis absorption spectra (Figure b) illustrate the selectivity of Au2@ZnO nanoparticles (NPs) toward Pb²⁺ ions. The spectrum for Au2@ZnO mixed with four metallic ions (Co²⁺, Cd²⁺, Hg²⁺, and Pb²⁺) is compared with that of Au2@ZnO mixed solely with Pb²⁺. The data reveal that no additional absorption bands appear in the visible region when Co²⁺, Cd²⁺, and Hg²⁺ ions are added to the system, indicating that these ions do not interfere with the detection process. In contrast, a distinct absorption peak emerges at approximately 550 nm when Au2@ZnO interacts exclusively with Pb²⁺ ions. This selective response highlights the material’s ability to target Pb²⁺ even in the presence of other potentially competing metal ions, making it a reliable candidate for selective sensing in complex mixtures. Figure c depicts the influence of varying concentrations of Au2@ZnO NPs (10, 20, and 30 mM) on detecting Pb²⁺ ions using UV–vis absorption spectroscopy. As the concentration of Au2@ZnO increases, the intensity of the characteristic absorption peak at 550 nm also increases, suggesting enhanced sensitivity due to more active sites available for interaction with Pb²⁺ ions. Importantly, the position of the absorption band remains consistent across all concentrations, confirming that the interaction mechanism between Au2@ZnO and Pb²⁺ remains unchanged. The results indicate that a concentration of 20 mM provides an optimal balance, achieving significant detection efficiency without saturation or diminished performance observed at higher concentrations. These findings demonstrate that Au2@ZnO NPs are both effective and scalable for Pb²⁺ detection under varying conditions.

8.

(a) UV–vis absorbance spectra of the interaction of Au2@ZnO with five different metal ions with 2 mM fixed molarity. (b) UV–vis absorbance spectra of the Au2@ZnO with three different molarities (10, 20, and 30 mM) of the material with Pb²⁺ (4 mM) sensing. (c) UV–vis absorption spectra in the presence of a mixture of metal ions (Co²⁺, Cd²⁺, Hg²⁺, and Pb²⁺) with and without Au@ZnO. Also, UV–vis absorption spectra in the presence of Pb²⁺ with and without Au@ZnO. The characteristic absorption band of Pb²⁺ around 550 nm remains unchanged in the mixed-ion solution.

3.6. Sensitivity to the Pb²⁺

We investigated the sensitivity of Au2@ZnO toward Pb ions in DI water using the most favorable experimental conditions. Spectrophotometric measurements were carried out for 20 min to confirm a consistent absorbance response despite the first quick sensing response. First, the concentration of Au2@ZnO was optimized. Then, these were performed to analyze the absorbance response and ratiometric measurements for Pb ion concentrations ranging from 1 to 4.5 mM. These concentrations were detected at ∼369 and ∼971 nm (Figure a). The absorbance strength of the SPR peak at ∼369 nm decreased in proportion to the Pb ion concentration, and a new peak appeared at ∼971 nm. The increase of the Pb ion concentration was found to be correlated linearly with a decrease in absorbance intensity at ∼369 nm; the coefficient (R ²) was determined to be around 0.9512 (Figure b). The correlation between absorbance changes and the Pb ion concentration permits the accurate and quantitative detection of Pb ions using Au2@ZnO chemosensors. The Au2@ZnO chemosensor provides a precise and quantitative means of determining the Pb ion concentration due to the correlation between changes in absorbance and the Pb ion concentration. The degree of aggregation caused by the Pb ion concentration was shown to rise proportionately with the absorbance intensity at around 971 nm. Based on the Figure c, the estimated correlation coefficient (R ²) was estimated to be 0.9768%. These findings show that the Pb ion concentration can be measured quantitatively using the absorbance ratiometric intensities at 369 and 971 nm. As a result, Pb ion concentrations and ratiometric intensities (A ₉₇₁/A ₃₆₉) were used to build a calibration graph. With an outstanding correlation value (R ²) of around 0.9337, the results produced a promising data set for the detection of Pb ions (Figure c). Using the usual 3σ/slope, the limit of detection (LOD) value was calculated to be approximately 1.78 mM. As a result, the ratiometric method offers a trustworthy and accurate test for millimolar Pb ion detection. When Au2@ZnO nanograins were exposed to light, their LSPR enhanced the absorption and scattering of light, leading to improved sensitivity. These findings show that the assay designed for the quantitative measurement of Pb ions is reliable and practical, making it a promising platform for real-world applications. The volumetric ratio of Au2@ZnO to the metal ions concerning the weight percentage utilized in the analysis is shown in Table . A comparison table on the Au@ZnO sensing metal ions is shown in Table .

9.

(a) UV–vis spectrum of Au@ZnO as a function of the increasing concentration of lead ions in millimolar ranges, (b) absorbance intensities of Au@ZnO at 369 nm, (c) absorbance intensities of Au@ZnO at 971 nm, and (d) ratiometric absorbance response of Au@ZnO (A ₉₇₁/A ₃₆₉) nm.

1. Volumetric Ratio of Pb⁺²vs Au2@ZnO.

concentration of Pb 2+ (mM)	volumetric ratio (Pb 2+ : Au2@ZnO)
1	0.1855
1.5	0.2783
2	0.3711
2.5	0.4638
3	0.5566
3.5	0.6493
4	0.7421
4.5	0.8349

2. Comparison Table on Au@ZnO Sensing Metal Ions.

material	metal ion	LOD	references
Au@ZnO	Pb2+	1.78 mM	this work
Au/ZnS/ZnO photoelectrochemical sensor	Cd2+	0.1–100 μM
Au-ZnO-IIP sensor	Hg2+	7.89 mM (Kd1)
Au-ZnO heterostructure	H2O2	120 mM
Au NP/ZnO NC arrays	crystal violet (CV) molecules	10–10 M

3.7. Stability of Au2@ZnO Nanograins

The response time of Au2@ZnO toward Pb ions was evaluated by measuring the absorbance intensity at 520 nm for three different concentrations (2, 3, and 4 mM). The results showed that the absorbance intensity promptly increased to the maximum within a fraction of a minute and stabilized within 5 min, regardless of the Pb ion concentration. This quick response time enables the efficient and timely detection of the target analyte. However, a common phenomenon in sensors based on the aggregation of metal NPs is the formation of undefined or nondirectional large aggregates. This raises the possibility of false positive results if the metal NP aggregates continue to grow in size over time or cause sedimentation, especially when processing a large number of samples. Therefore, it is crucial to observe the spectral changes for an extended period of time to assess the stability of the developed sensor over time. This allows for a better understanding of the aggregate mechanism and plasmonic coupling events, leading to the development of reliable and promising detection platforms.

UV–vis absorbance spectra were recorded following the coordination of Pb metal ions with Au2@ZnO for 20–120 min to evaluate the stability of the produced chemosensor. The spectral response was seen at three distinct Pb ion concentrations (2, 3, and 4 mM; Figure ). When 2 and 3 nM Pb ions were added to Au2@ZnO, there was a slight increase in absorbance intensity at 369 nm but no sign of a redshift peak (Figure a,b). In contrast, a bathochromic shift of the SPR band toward a longer wavelength at 369 nm was noted for 4 mM Pb ions combined with a slight decrease in the absorbance intensity (Figure c). The stability of the spectral changes suggests the likelihood of detecting Pb ions over an extended period, making it suitable for practical applications. These results indicate that the developed sensor exhibits good long-term stability and feasibility performance for point-of-care (POC) applications. Furthermore, the degree of Au2@ZnO aggregation also depends on the concentration of the target analyte; an increase in the concentration increases the aggregation and intensity of absorbance at larger wavelengths.

10.

Real-time changes in the UV–vis absorbance spectrum of Au@ZnO in the presence of (a) 2 mM, (b) 3 mM, and (c) 4 mM lead ions. (d) Sensing mechanism of lead ions.

3.8. Mechanism of Pb²⁺ Detection

In the mechanism of metallic ion detection of the Au2@ZnO sample, Au atoms provide additional interband electrons to interact with Pb²⁺ under UV illumination. Due to the highest excitonic binding energy of ZnO (60 MeV), some excess electrons from Au were considered in the intraband, which played a major role in the movement of the defect emission. The excited interband electrons can flow to ZnO to increase the charge density or directly interact with the Pb²⁺. The increased charge density of ZnO leads to enhanced interaction with Pb²⁺, resulting in increased photoresistance of the Au2@ZnO sensor (Figure d).

The sensing mechanism under the UV–visible region is primarily attributed to Au’s localized surface plasmon resonance (LSPR) effect. When light interacts with Au, it induces the resonance of a large number of electrons oscillating on its surface. This resonance is highly sensitive to changes in charge density and Au’s dielectric environment. The Pb²⁺ ions have a strong electron affinity, which can easily adsorb onto the surface of Au NPs, capturing electrons. This adsorption reduces the charge density of Au, increasing the sensor’s resistance. The Pb²⁺ ions adsorbed on the Au2@ZnO nanocomposite surface specifically contribute to the sensing response. In the UV region, the sensing response is primarily enhanced by the photogenerated electrons in ZnO, with the electrons from Au playing a relatively smaller role. Since LSPR is mainly a surface phenomenon under visible light illumination, there is a heightened interaction between the adsorbed Pb²⁺ ions and electrons from Au on the surface. The oscillating electrons in AuNPs due to LSPR have been shown to improve interactions with adsorbed Pb ions. Consequently, the sensing response is more significant in the visible region than in the UV region because of the LSPR effect of Au NPs. These findings indicate the potential of plasmonic Au-functionalized ZnO for light-induced sensing applications across different wavelengths, including the visible region at room temperature. Following the nucleation and growth process, the synthesized material Au@ZnO experiences functionalization in the UV light spectrum (Figure a). The material now exhibits Pb²⁺ selectivity when 1 mM metallic ion sol is employed (Figure b). Now, the sensitivity of the material is tested for the increasing concentration of Pb²⁺. The results demonstrate a linear increase in sensitivity with higher concentrations of Pb²⁺, indicating the potential for this material to be used as a selective sensor for heavy metal ions (Figure c).

11.

Systematic presentation for the functionalization, selectivity, and sensitivity of nanostructured Au@ZnO, (a) structure for the nucleation, growth, and functionalization, (b) selectivity of Au2@ZnO to 1 mM sol of different metallic ions and the bar chart for the detection of Pb²⁺, and (c) sensitivity of Au2@ZnO for the detection of Pb²⁺ in the 0.5–4.5 mM range that represented with the bar chart.

3.9. Photobleachability and Stability of the Au@ZnO

Photobleachability refers to the susceptibility of a material to degradation or loss of optical properties when exposed to light, especially during prolonged use. In the context of Au@ZnO, photobleaching is less concerned than conventional fluorophores due to its inorganic composition and the incorporation of AU NPs. They enhance the material’s optical robustness through localized surface plasmon resonance (LSPR), which improves light absorption and minimizes the likelihood of reactive photochemical processes that can degrade optical performance. While the exact mechanisms of photobleaching can involve electronic excitations to reactive triplet states, Au@ZnO is inherently more stable because the ZnO matrix and Au nanoparticles resist the oxidative and photochemical reactions commonly observed in organic fluorophores. This stability is advantageous for applications requiring extended or repeated light exposure, such as chemosensing under UV–vis conditions.

Moreover, Au@ZnO does not require antiphotobleaching agents, which are often necessary for fluorophores but can be toxic in biological systems. Its photostability ensures consistent and reliable performance over multiple sensing cycles, making it a superior choice for applications that demand long-term optical integrity and resistance to photobleaching. The graph illustrates the decrease in absorbance of methylene blue (MB) dye at 664 nm over time upon exposure to Au@ZnO. The rapid decline in absorbance within the first 75 min demonstrates the practical photobleaching ability of Au@ZnO, attributed to its catalytic properties under light irradiation. Beyond 100 min, the absorption stabilizes, indicating near-complete degradation of the dye (Figure a). The bar chart represents the stability of Au@ZnO NPs over four degradation cycles, measured by the percentage degradation of the MB dye. The consistent degradation efficiency across all four cycles demonstrates the material’s excellent reusability and stability. The minimal decline in performance highlights the robust structural integrity of Au@ZnO, making it suitable for repeated applications without significant loss of activity (Figure b).

12.

(a, b) Photobleachability and stability of Au2@ZnO. (c, d) Reversibility and timeline studies of Au@ZnO. (e) Effect of pH on sensing.

3.10. Reversibility Tests and Timeline Studies

Reversible binding is a key characteristic of efficient and reusable metal ion sensors. The Au@ZnO system’s reversibility was evaluated using Na₂EDTA, a well-known chelating agent. UV–vis spectroscopy was employed to monitor the binding dynamics. A distinct absorption peak appeared when Pb²⁺ ions were introduced to the Au@ZnO solution, confirming the successful interaction between the ions and the sensor material. Subsequent addition of Na₂EDTA caused the absorption peak to diminish, indicating the removal of Pb²⁺ ions through chelation. Reintroducing Pb²⁺ ions into the system restored the absorption peak, demonstrating the re-establishment of binding interactions. This process was repeated across three cycles with consistent absorption and emission spectral changes observed in each cycle. These results confirm that the Au@ZnO sensor exhibits reversible binding with Pb²⁺ ions without losing functionality. Such reversibility highlights the potential of Au@ZnO for practical applications in real-time metal ion detection, offering reusability and sustainability in sensing operations.

The graph (Figure c) illustrates the reversibility of the Au@ZnO system over four consecutive cycles of Pb²⁺ ion binding and regeneration using Na₂EDTA. The absorption intensity decreases progressively with each cycle, demonstrating the reversible nature of the system as Pb²⁺ ions are removed by Na₂EDTA and rebound in the next cycle. While there is a slight decrease in the intensity after each cycle, the system remains stable and maintains its functionality throughout all four cycles. This confirms the material’s capacity for reuse and highlights its robustness for Pb²⁺ ion detection. The ability of Au@ZnO to undergo multiple reversible cycles underscores its suitability for real-time monitoring and practical applications in environmental and industrial metal ion sensing. The timeline studies are listed in Figure d. The graph illustrates the timeline studies of Pb²⁺ sensing at three concentrations: 2, 3, and 4 mM. The sensing response increases rapidly at the initial stage for all concentrations, indicating an efficient interaction between the sensing material and Pb²⁺ ions. At lower concentrations (2 mM), the response saturates more slowly and at a lower value than at higher concentrations (3 and 4 mM), where the response stabilizes faster and at higher levels. This trend suggests that higher Pb²⁺ concentrations enhance the sensitivity and saturation levels of the sensor, likely due to the increased availability of analyte ions for detection.

3.11. Effect of pH

The effect of pH on the sensing performance of Au@ZnO was evaluated across a pH range of 3.0–7.0 by altering the pH of the solution during Pb²⁺ detection. Beyond pH 7.0, hydroxyl complexes of Pb²⁺ ions begin to form, which interfere with the sensing mechanism. The investigation was limited to pH values between 3.0 and 7.0. The optimal response was observed at pH 6, where the interaction between the Pb²⁺ ions and functional groups on the Au@ZnO surface was maximized while minimizing protonation effects or hydroxyl complex formation. At pH levels below 4.0, the sensor’s response declined due to the protonation of surface functional groups on Au@ZnO, which inhibited Pb²⁺ binding. Conversely, at pH levels approaching 7.0, forming Pb­(OH)₂ complexes reduced the availability of free Pb²⁺ ions, diminishing the response. Thus, the pH plays a critical role in the sensitivity and selectivity of Au@ZnO for Pb²⁺ detection. A pH value of 6 was selected for subsequent experiments to achieve optimal sensing performance and ensure high efficiency. The graph (Figure c) demonstrates how pH affects the sensing performance of Pb²⁺ ions in Au₂@ZnO. Sensitivity is low at pH 4, likely due to proton competition interfering with Pb²⁺ binding. As the pH increases, the performance improves, peaking at pH 7, where the material achieves its maximum detection capability. This suggests that near-neutral conditions are optimal for Pb²⁺ and sensor-material interaction. Beyond pH 7, the sensitivity stabilizes or slightly declines, possibly due to changes in the surface chemistry or reduced ion availability. This highlights the importance of pH optimization for effective Pb²⁺ sensing.

4. Conclusions

A novel, efficient, and cost-effective hydrothermal synthesis process of Au@ZnO nanograins was performed for detecting Pb²⁺ ions in this research work. Microstructural analysis revealed hexagonal nanograins tuned by the Au dopant concentration. Au content induced a redshift in the absorption peak, reducing the bandgap from 3.2 eV for bare ZnO to 2.9 eV for Au5@ZnO. DFT calculations supported these results, highlighting how Au incorporation modifies ZnO properties. Au@ZnO displayed the selective detection of Pb²⁺, with SPR and LSPR peaks at 369 and ∼550 nm, alongside a new absorption band at 971 nm upon the Pb²⁺ introduction. The developed chemosensor achieved a detection limit of 1.78 mM with a strong correlation (R ² = 0.9635). Additional studies confirmed stability over four cycles, high reversibility, robust photobleachability, and consistent performance under optimal pH conditions (pH 7). A distinct absorption band at 971 nm upon introduction of Pb²⁺ further validates its sensing efficacy. These findings establish Au@ZnO nanograins as an efficient platform for heavy metal sensing, offering sensitivity, scalability, and environmental relevance. Further research is underway to optimize performance and enable practical applications, addressing the growing need for effective technologies to monitor and mitigate heavy metal pollution.

Km. Preetivisualization, writing, editing, and articulation of the article. Sanjeev K. Sharmavisualization, writing, supervision, mentoring, and editing of the article.

The authors declare no competing financial interest.