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ORIGINAL RESEARCH article

Front. Chem., 13 February 2026

Sec. Nanoscience

Volume 14 - 2026 | https://doi.org/10.3389/fchem.2026.1782669

This article is part of the Research TopicMicroenvironment-Responsive Organic, Inorganic, and Hybrid Structured Nanoparticles: Synthesis, Therapeutic Strategies, and Imaging ApplicationsView all 4 articles

Photoelectrochemical sensor based on Au/Fe3O4 for ultrasensitive detection of uric acid corresponding to alzheimer’s disease

Xin Wang
Xin Wang1*Bin WuBin Wu1Jian AnJian An2Yan Cai
Yan Cai2*
  • 1Department of Neurology, Taihe County People’s Hospital, Taihe, China
  • 2School of Chemistry and Chemical Engineering, Nantong University, Nantong, China

Introduction: Uric acid (UA) is a crucial biochemical indicator in the human body. The dynamic balance between its production and excretion is essential for maintaining homeostasis, and detecting UA concentration enables disease diagnosis. To address the limitations of traditional UA detection methods, such as high cost and complex operation, this study constructed a photoelectrochemical (PEC) sensor modified with Au/Fe3O4.

Methods: Fe3O4 and Au nanoparticles (Au NPs) were synthesized via hydrothermal methods, and the Au/Fe3O4 composite was prepared by ultrasonically loading Au NPs onto the surface of Fe3O4.

Results: Under visible light illumination, the Au/Fe3O4 composite exhibited a significant photocurrent response to UA, primarily due to the synergistic effect between the localized surface plasmon resonance (LSPR) induced by Au NPs and the photogenerated electron–hole pairs from Fe3O4. This synergy promotes the redox reaction of UA at the electrode surface, thereby enhancing the photocurrent signal. Under optimized conditions, the Au/Fe3O4/GCE showed a good linear relationship in the range of 0–100 μmol/L with a detection limit as low as 3.3 μmol/L (S/N = 3).

Discussion: The sensor demonstrated excellent anti-interference ability and stability, offering a new approach for UA detection. This method holds promise for practical applications in clinical diagnosis and bioanalysis.

1 Introduction

Uric acid (UA) is the final product of purine metabolism in humans, primarily produced in the liver and excreted by the kidneys. UA plays complex physiological and pathological roles and is a vital biomarker in clinical medicine and disease diagnosis (Selvam et al., 2020). And physiologically, UA is a key antioxidant in the body. The dynamic balance between its production and excretion is crucial for maintaining health. Under normal conditions, serum UA concentration remains within a stable range. Elevated serum UA levels can lead to metabolic syndrome and hyperuricemia, which may further cause complications such as gouty arthritis, hypertension, and coronary heart disease (Copur et al., 2022). Conversely, low serum UA levels may be associated with Parkinson’s disease or multiple sclerosis (Gagliardi et al., 2009; Lippi et al., 2008; Lohsoonthorn and Williams, 2006). Therefore, with the increasing number of patients affected by diseases related to abnormal UA levels, there is a need for rapid, efficient, stable, and highly sensitive methods for UA detection.

Common UA detection methods include enzymatic analysis, high-performance liquid chromatography, spectrophotometry, and electrochemical assays (Sun et al., 2016; Wang et al., 2015; Zuo et al., 2008). Although these methods offer high accuracy, they generally suffer from limitations such as high equipment costs, complex procedures, and long analysis times, making them unsuitable for point-of-care testing. To overcome these limitations, researchers have turned to novel sensing technologies. Advances in nanomaterials and biosensing have led to the development of new detection platforms such as electrochemical sensors, photoelectrochemical (PEC) devices, and fluorescent biosensors (Wang et al., 2025a). These technologies, with their advantages of fast response, high sensitivity, and operational simplicity, have become a focus in UA detection research. In recent years, PEC sensors have emerged as a promising approach due to their high sensitivity, excellent selectivity, stability, and practicality. The photoelectric material is a key factor influencing the performance of PEC sensors.

Gold nanoparticles (Au NPs), typically 1–100 nm in size, possess unique physical and chemical properties. They are easily functionalized and their surfaces can be modified with various functional molecules (e.g., thiol compounds, biomolecules) via chemical bonds, enabling specific detection of target analytes (Tao et al., 2024). Additionally, Au NPs exhibit excellent biocompatibility, catalytic activity, and electrical properties, showing great potential in biomedical, catalytic, and sensing applications. Fe3O4 is an excellent photoactive material that, under illumination, generates photogenerated electrons and holes, which participate in redox reactions at the electrode surface to produce a photocurrent signal for target detection (Wang Li. et al., 2020b; Zhang et al., 2025). Furthermore, the difference between the bandgap of Fe3O4 with other composite materials can facilitate more efficient carrier separation and transfer. Due to its active surface and ease of functionalization, Fe3O4 nanomaterials can be surface-functionalized (e.g., with antibodies/aptamers, immobilized enzymes) to construct highly specific bio-recognition interfaces. Combined with photoelectric signal amplification, this enables trace detection of targets such as tumor markers, nucleic acids, and small-molecule metabolites (with detection limits down to nM or fM levels) (Xiang et al., 2026). The magnetic separation capability of Fe3O4 significantly improves the pretreatment efficiency of complex biological samples (e.g., serum, cell lysates) while reducing matrix interference, offering an efficient technical approach for point-of-care testing (POCT) (Hofer, 2021; Van et al., 2025). Fe3O4, as a magnetic material, facilitates electrode recovery and reuse, while Au enhances light absorption and electron transfer efficiency, potentially improving the sensitivity and selectivity of UA detection (Chen et al., 2021).

In this study, Au NPs and Fe3O4 were synthesized via hydrothermal methods, and the Au/Fe3O4 nanocomposite prepared by ultrasonic compounding was used for highly sensitive UA detection. Fe3O4 possesses unique magnetic properties, good biocompatibility, and catalytic performance, while Au exhibits excellent LSPR effects and conductivity. Their combination in a PEC sensor achieves complementary advantages and synergistic enhancement, as illustrated in Scheme 1. The successfully fabricated Au/Fe3O4 PEC sensor enables rapid, highly sensitive, and selective UA detection. This method is expected to facilitate clinical UA detection and provide theoretical support for understanding the relationship between Alzheimer’s disease and uric acid concentration.

Scheme 1
Diagram illustrating photoelectrochemical (PEC) detection of uric acid, featuring a sensor schematic, a graph comparing photocurrent densities of Au, Fe3O4, and Au/Fe3O4, a sun cartoon, uric acid molecule, and illustrations linking uric acid to Alzheimer’s disease, gout, and cardiovascular disease.

Scheme 1. Schematic representation of the Au/Fe3O4 PEC sensing process of uric acid.

2 Experimental section

2.1 Preparation of Au, Fe3O4, and Au/Fe3O4

2.1.1 Synthesis of Au nanoparticles

Au NPs were synthesized via a hydrothermal method (Zhang et al., 2023). Firstly, 0.9 mL citric acid and 2.1 mL 0.1 mol/L sodium citrate were rapidly added to 150 mL of boiling distilled water and stirred for 15 min. Then, 1 mL 25.4 mmol/L chloroauric acid was added to the mixture, followed by stirring for an additional 3 min. The reaction solution was immediately quenched in an ice-water bath. The product was centrifuged, washed, and the obtained precipitate was dispersed in 10 mL of distilled water for subsequent use.

2.1.2 Synthesis of Fe3O4 nanoparticles

A mixture of 0.675 g FeCl3·6H2O, 1.8 g CH3COONa, and 0.5 g polyethylene glycol was dispersed in a certain amount of ethylene glycol solvent. After thorough stirring, the mixture was continuously stirred at 50 °C for 2 h until it turned brown. The solution was then transferred to an autoclave and heated at 200 °C for 4 h. After reaction, the product was washed three times with distilled water and ethanol to remove impurities. After centrifugation, the obtained Fe3O4 nanospheres were left to stand for 48 h, then fully cooled and dried for later use.

2.1.3 Preparation of Au/Fe3O4 nanocomposite

A certain amount of Fe3O4 nanoparticles was dispersed in ethanol and sonicated for 30 min to form a uniform suspension. This suspension was transferred to a container containing the Au NPs solution and stirred under ultrasonication for 1.5 h to allow thorough compounding. Finally, the Au/Fe3O4 composite was separated using a magnet, washed repeatedly with ethanol and deionized water to remove unreacted substances and impurities, and dried in a vacuum oven to obtain the Au/Fe3O4 composite.

2.1.4 Fabrication of Au/Fe3O4/GCE

A glassy carbon electrode (GCE) was first polished with alumina powders of different particle sizes (500 nm and 50 nm). To further clean the electrode, the polished GCE was ultrasonicated in absolute ethanol and ultrapure water for 30 s each. Then, 10 μL Au/Fe3O4 composite dispersion was drop-coated onto the clean, dry electrode surface and dried under an infrared lamp at 50 °C, resulting in the Au/Fe3O4/GCE.

3 Results and discussion

3.1 Characterization of Au, Fe3O4, and Au/Fe3O4

Figures 1A–C shows the scanning electron microscopy (SEM) images of Au NPs, Fe3O4, and Au/Fe3O4, respectively. The Au NPs exhibited uniform spherical or quasi-spherical morphology (Figure 1A). The Fe3O4 nanoparticles appeared spherical with a size of approximately 200 nm (Figure 1B). In the Au/Fe3O4 composite (Figure 1C), Au NPs were dispersed on the surface of the Fe3O4 nanospheres. X-ray diffraction (XRD) was used to investigate the crystal structure (Figure 1D). The characteristic diffraction peaks of Au NPs appeared at 2θ = 38.21°, 43.96°, 53.45°, 62.69°, and 75.95°, corresponding to the (111), (200), (422), (220), and (311) crystal planes, respectively (Bhardwaj et al., 2024). For Fe3O4, the characteristic peaks were observed at 30.66°, 35.42°, 43.02°, 57.09°, and 62.69°, corresponding to the (220), (311), (400), (511), and (440) planes, respectively (Cheng et al., 2017). The XRD pattern of Au/Fe3O4 (red curve) showed peaks at 35.42°, 38.21°, 43.96°, 53.45°, and 62.69°, corresponding to the (311) plane of Fe3O4 and the (111), (200), (422), and (220) planes of Au, confirming the successful synthesis of the Au/Fe3O4 nanocomposite (Wang et al., 2025b).

Figure 1
Panel A shows a scanning electron microscopy image with numerous small, irregularly shaped particles scattered across a dark background. Panel B presents a higher magnification image displaying more distinct, spherical particles dispersed with some clustering. Panel C provides an even closer view, highlighting individual spherical nanoparticles with clear separation. Panel D features an X-ray diffraction pattern with three sets of peaks in red, blue, and black, labeled Au/Fe3O4, Fe3O4, and Au respectively, displaying distinct crystallographic planes for each material.

Figure 1. SEM images of Au (A); Au/Fe3O4 (B) (C) and XRD pattern of Au/Fe3O4 (D).

3.2 Electrochemical and photoelectrochemical performance of Au, Fe3O4, and Au/Fe3O4

Figure 2A presents the cyclic voltammetry (CV) curves of Au, Fe3O4, and Au/Fe3O4 modified electrodes in a solution containing 5 mM K3 [Fe(CN)6]/K4 [Fe(CN)6] and 0.1 M KCl. The Au/Fe3O4-modified electrode showed a higher oxidation peak current compared to electrodes modified with Au or Fe3O4 alone. This is attributed to the good redox capability of Fe3O4 and the excellent charge transfer ability of Au NPs, whose LSPR effect accelerates charge transfer and suppresses electron–hole recombination (Jian et al., 2021). Electrochemical impedance spectroscopy (EIS) was used to evaluate the conductivity (Figure 2B). The semicircle diameter followed the order: Au/Fe3O4 < Au < Fe3O4, indicating that Au/Fe3O4 exhibited the best charge transfer ability, consistent with the CV results (Inico et al., 2025). Figure 2C displays the transient photocurrent–time response curves in PBS (pH 7.0) containing 50 μM UA under visible light illumination (xenon lamp, interrupted every 20 s). The photocurrent density increased in the order: Au/Fe3O4 > Au > Fe3O4, with the composite showing the highest response. Figure 2D compares the differential pulse voltammetry (DPV) responses of the Au/Fe3O4 electrode under light and dark conditions. The oxidation peak current density was significantly higher under illumination. This enhancement is attributed to the synergistic effect: under visible irradiation, photogenerated electron–hole pairs separate effectively; the holes can oxidize UA easily, while electrons transfer to the external circuit, generating a photocurrent. Fe3O4 provides a large specific surface area and abundant active sites for UA adsorption. Meanwhile, Au NPs enhance light harvesting via LSPR and facilitate electron transfer, reducing electron–hole recombination and amplifying the photocurrent signal.

Figure 2
Panel A shows a cyclic voltammetry plot with current versus potential for Fe₃O₄ (black), Au (blue), and Au/Fe₃O₄ (red), where Au/Fe₃O₄ exhibits higher currents. Panel B is a Nyquist plot of -Z'' versus Z' for Fe₃O₄ (black circles), Au (blue triangles), and Au/Fe₃O₄ (red squares), indicating lower impedance for Au/Fe₃O₄. Panel C presents a photocurrent density versus time plot, demonstrating a significant photocurrent response for Au/Fe₃O₄ (red) compared to Au (black) and Fe₃O₄ (blue). Panel D depicts a plot of photocurrent density versus potential for visible light (red) and without light (black), showing higher response under visible light exposure.

Figure 2. (A) Cyclic voltammetry curves and (B) electrochemical impedance spectroscopy of Au, Fe3O4 and Au/Fe3O4 electrodes in 5 mM K3 [Fe(CN)6]/K4 [Fe(CN)6] and 0.1 M KCl solution. (C) Transient photocurrent and time curves in PBS (pH = 7.0) containing 50 μM uric acid. The light source was xenon lamp, interrupted every 20 s. (D) Differential pulse voltammetry curves of Au/Fe3O4 in PBS (pH = 7.0) containing 50 μM uric acid in the presence and absence of light.

3.3 Optimization of detection conditions for Au/Fe3O4

The effects of pH values and scan rate on the PEC performance were investigated. Under visible light, DPV responses were recorded in PBS (pH 5.0–9.0) containing 50 μM UA (Figure 3A). The oxidation peak current increased with pH from 5.0 to 7.0, reaching a maximum at pH 7.0, and decreased at higher pH. Therefore, pH 7.0 was selected for subsequent experiments. The oxidation peak potential shifted linearly with pH changes (Figure 3B), following the equation: Epa = −0.0416 pH + 0.5392 (R2 = 0.9959). The slope is close to the Nernst value of 0.059 V/pH, indicating a one proton and one electron transfer process (Cui et al., 2017). The influence of scan rate (20–200 mV s-1) was studied by linear sweep voltammetry (LSV) in PBS (pH 7.0) containing 50 μM UA under illumination (Figure 3C). The oxidation peak current increased with scan rate. A linear relationship was observed between peak current (Ipa) and scan rate (ν): Ipa (μA) = 1.6335ν + 93.4194 (R2 = 0.9974) (Figure 3D), suggesting that the electron transfer is adsorption-controlled (Wang et al., 2020a).

Figure 3
Panel A shows a line graph of photocurrent density versus potential at pH values of five to nine, with the highest peak at pH seven. Panel B presents a scatter plot with a linear fit showing a decrease in Epa with increasing pH, equation Epa = -0.0416pH + 0.5392, and R squared value of 0.9959. Panel C illustrates multiple line plots of photocurrent density versus potential for scan rates from twenty to two hundred millivolts per second, with increasing peak current at higher scan rates. Panel D is a scatter plot with a linear fit showing photocurrent density versus scan rate, with the equation Ipa = 1.6335v + 93.4194, R squared 0.9974.

Figure 3. (A) DPVs of Au/Fe3O4 electrode in 0.1 M PBS buffer solution containing 50 μM uric acid under light conditions at different pH values (pH = 5.0, 6.0, 7.0, 8.0, 9.0), (B) Linear relationship between oxidation peak potential and different pH values, (C) Linear voltammetry curves of Au/Fe3O4 electrodes in 0.1 M PBS buffer solution (pH = 7.0) containing 50 μM urate at different scanning rates (20–200 mV∙s−1) under light conditions, (D) Linear relationship between peak oxidation current and scan rate.

3.4 Detection limit of the sensor

DPV was used to evaluate the photocurrent response at different UA concentrations (0–100 μM) in PBS (pH 7.0) under visible light (Figure 4A). The oxidation peak current increased with the increase of UA concentration. A linear calibration curve was obtained (Figure 4B): Ipa = 0.8015C + 23.2649 (R2 = 0.9977), with a detection limit of 3.33 μM (S/N = 3). This demonstrates the high detection capability of the PEC sensor for UA under visible light illumination.

Figure 4
Panel A shows multiple colored differential pulse voltammetry curves of photocurrent density versus potential with increasing uric acid concentration indicated by an upward arrow from 0 to 100 micromolar. Panel B displays a linear calibration plot of photocurrent density versus concentration with data points and a fitted red line. The equation I equals 0.8015 times concentration plus 23.2649 and R squared value of 0.9977 are shown, indicating high linearity.

Figure 4. (A) Differential pulse voltammetry curves of Au/Fe3O4 electrode in PBS (pH = 7.0) with uric acid concentration of 0-100 μM under visible light irradiation; (B) Linear relationship of photocurrent intensity and concentration corresponding to Au/Fe3O4 electrode.

3.5 Anti-interference ability and stability of the PEC sensor

To assess selectivity, potential interferent (0.1 M NaCl, KCl, ascorbic acid (AA), and glucose (Glu)) were added sequentially to PBS (pH 7.0) containing 100 μM UA (Figure 5A). The photocurrent density remained stable within an acceptable range, confirming excellent anti-interference ability and selectivity. The stability was evaluated by recording 100 consecutive CV cycles in the same solution (Figure 5B). The peak current showed only minimal degradation, indicating good stability of the Au/Fe3O4 sensor.

Figure 5
Panel A shows a bar graph comparing photocurrent density in microamperes per square centimeter for five interfering samples, with values ranging around sixteen. Panel B presents a cyclic voltammogram with red curves of photocurrent density versus potential between negative point four and one point two volts.

Figure 5. Photocurrent response of (A) Au/Fe3O4/GCE under visible light irradiation with 100 μM uric acid and interferers added in sequence, the concentration of interferers was 0.1 M, the sequence was as follows: 2-NaCl, 3-KCl, 4-AA, 5-Glu, and (B) CV curves of the Au/Fe3O4/GCE in 50 μM uric acid of 100 cycles.

4 Conclusion

In this study, an Au/Fe3O4 nanocomposite was successfully prepared and applied in a PEC sensor for highly sensitive UA detection. Material characterization, condition optimization, and PEC tests demonstrated that the Au/Fe3O4/GCE sensor exhibits excellent PEC performance, strong anti-interference ability, and high stability, outperforming sensors based on single components. The sensor showed a linear response range of 0–100 μmol/L and a low detection limit of 3.3 μM. This performance is attributed to the synergistic effect between Fe3O4, which provides a large specific surface area, enhances visible light absorption, and improves stability, and Au NPs, which enhance light harvesting and electron transfer via LSPR, thereby amplifying the photocurrent response. The Au/Fe3O4 -based PEC sensor offers a new strategy for UA detection and holds promising application prospects in biomedical testing.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author contributions

XW: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing. BW: Data curation, Investigation, Methodology, Resources, Writing – review and editing. JA: Formal Analysis, Investigation, Methodology, Software, Writing – review and editing. YC: Funding acquisition, Investigation, Resources, Validation, Writing – review and editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This work was sponsored by the Research and Practice Innovation Plan for Graduate Students in Jiangsu Province (SJCX25-2027). This work was supported by the Nantong University Analysis and Testing Center.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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Keywords: Alzheimer, Au/Fe3O4, photoelectrochemical sensor, ultrasensitivity, uric acid

Citation: Wang X, Wu B, An J and Cai Y (2026) Photoelectrochemical sensor based on Au/Fe3O4 for ultrasensitive detection of uric acid corresponding to alzheimer’s disease. Front. Chem. 14:1782669. doi: 10.3389/fchem.2026.1782669

Received: 07 January 2026; Accepted: 27 January 2026;
Published: 13 February 2026.

Edited by:

Ruibo Zhao, Zhejiang Sci-Tech University, China

Reviewed by:

Ke Zhang, Shaanxi University of Science and Technology, China
Yangping Zhang, Jiangsu University of Science and Technology, China

Copyright © 2026 Wang, Wu, An and Cai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xin Wang, WGlud2FuZzM2NTdAMTYzLmNvbQ==; Yan Cai, eWFuY2FpMjAxMEBudHUuZWR1LmNu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.