Glucose Detection Research Articles

Next-Generation Hybrid Multi-Material Surface Plasmon Resonance Biosensor for Non-Invasive Glucose Detection with Machine Learning Optimization

Next-Generation Hybrid Multi-Material Surface Plasmon Resonance Biosensor for Non-Invasive Glucose Detection with Machine Learning Optimization

Cost-Effective and Visual Electrochromic Detection of Glucose Using a Closed Bipolar Electrode Platform

Abstract In this study, a novel potential-integrated electrochromic (EC) visual sensor was developed for glucose detection using a closed bipolar electrode (BPE)-enabled electrochromic device. The sensor consists of a flexible thin film of graphene oxide (GO) or GO-poly(3,4-ethylenedioxypyrrole) (GO-PEDOP) and an electrochromic slime electrolyte containing ethyl viologen as the electrochromic indicator. The setup includes a reporting cell integrated with a GO or GO-PEDOP-based closed BPE and a separate silver (Ag)-coated filter paper containing various glucose concentrations as analytical cell. This design facilitates the electrochemical detection of glucose, achieving a linear range of up to 2 mM with a detection limit of approximately 0.66 mM. The use of GO-PEDOP offers enhanced flexibility and sensitivity, making the sensor highly effective for electrochemical glucose sensing. The proposed closed BPE-enabled device demonstrates low cost, simplicity, and ease of use, offering a promising platform for diverse glucose sensing applications with visual readouts. These attributes make it a promising candidate for widespread adoption in point-of-care diagnostics.

Cu2O Nanostructures Formed by Potential-Controlled Dissolution-Redeposition of Layered Copper Hydroxide for Nonenzymatic Glucose Detection

Cu₂O Nanostructures Formed by Potential-Controlled Dissolution-Redeposition of Layered Copper Hydroxide for Nonenzymatic Glucose Detection

The Rational Design of Pt Single Atoms‐Bridged Nanozyme with Enhancing Direct Electron Transfer Pathway for Glucose Oxidation

Abstract Nanozymes are promising tools in chemical synthesis, environmental remediation, and diagnostic sensing owing to their enzyme‐like catalytic properties. However, the inherent limitations of nanozymes stemming from their biological catalytic pathway dependency have fundamentally hindered their broader application. In this work, nanozyme with a direct electron transfer mechanism, mimicking natural glucose oxidase for glucose oxidation, is synthesized to offer a stable and direct catalytic pathway. Theoretical and experimental results demonstrate that Pt single atom sites on the nanozyme trigger robust metal‐support interaction for Au nanoparticles, forming a positively charged region on the Au surface. As a result, the Au could directly capture electrons from the oxygen atom in glucose to form the self‐powered electrochemical signal through direct electron transfer pathway, which is distinct from the common cascade reaction pathway for glucose oxidase. Herein, a self‐powered sensor based on a microfluidic chip is fabricated, showing high sensitivity for the detection of glucose with a detection limit of 10 nm. Its successful application in the detection of glucose in blood and real human sweat samples, and also a real‐time detection of glucose in sweat during the cycling and running offers insights into nanozyme innovations and provides promising commercialization potentials for noninvasive testing.

A fluorescent MTP‐based Detection Platform for Hydrogen Peroxide, Glucose, and Lactate

Hydrogen Peroxide (H2O2) is an important small metabolite often quantified with commercially available multi‐step fluorescence‐based assays. We developed a new microtiter plate (MTP) based platform that allows a rapid, one‐step assay with a ratiometric readout function. Specifically, we embedded 10‐Acetyl‐3,7‐dihydroxyphenoxazine (ADHP) in a polyurethane‐based hydrogel sensor membrane. For a ratiometric set‐up the membranes were loaded with polystyrene nanoparticles containing a Cy5‐based reference which allowed for the compensation for variations in membrane thickness. These knife‐coated µm‐thin films were mounted onto bottomless MTPs with double‐sided adhesive tape. Optimized membranes provided measurement times of 3 minutes upon sample addition and an LOD in PBS that was 10x lower than that of the ADHP‐using Amplex Red® commercial kit of 100 nmol·L‑1 H2O2. These ADHP hydrogels could be stored at room temperature for at least 22 months. Horseradish peroxidase (HRP) was nanospotted alone or together with either lactate oxidase or glucose oxidase for the detection of H2O2, lactate and glucose, respectively. With 50 v% glycerol as cryoprotectant in the spotting solution the HRP ADHP platform was stable for at least 13 weeks at – 20 °C. Enhanced simplicity and comparable performance to multi‐step assays suggest that the platform can simplify MTP‐based assays in the future.

Facile synthesis of ZnO/CuO/rGO nanohybrid for nonenzymatic electrochemical glucose sensor.

In this study, a ZnO/CuO/rGO nanohybrid was synthesized using a hydrothermal technique. The resulting nanohybrid was characterized through various methods, including UV-visible spectroscopy, XRD, and FE-SEM. The electrochemical characteristics of the sensor were examined using CV and amperometric techniques. To create the sensing electrode, the synthesized nanohybrid was applied to a glassy carbon electrode (GCE) via the drop-coating process. The ZnO/CuO/rGO-modified GCE demonstrated excellent electrocatalytic characteristics for glucose oxidation in an alkaline environment. Under optimal conditions, the electrochemical glucose sensor modified with ZnO/CuO/rGO/GCE exhibited a broad linear range (2-10 mM), impressive sensitivity (5660 μA mM-1 cm-2), a low detection limit (0.54 μM), and a rapid response time (3 s) for glucose detection. Moreover, the developed method displayed good repeatability (RSD = 3.8%) and stability, demonstrating its reliability.

Borohydride Synthesis of Silver Nanoparticles for SERS Platforms: Indirect Glucose Detection and Analysis Using Gradient Boosting

In recent years, non-invasive methods for the analysis of biological fluids have attracted growing interest. In this study, we propose a straightforward approach to fabricating silver nanoparticle (AgNP)-coated non-woven polyacrylonitrile substrates for surface-enhanced Raman scattering (SERS). AgNPs were synthesized directly on the substrate using borohydride reduction, ensuring uniform distribution. The optimized SERS substrates exhibited a high enhancement factor (EF) of up to 105 for the detection of 4-mercaptobenzoic acid (4-MBA). To enable glucose sensing, the substrates were further functionalized with glucose oxidase (GOx), allowing detection in the 1–10 mM range. Machine learning classification and regression models based on gradient boosting were employed to analyze SERS spectra, enhancing the accuracy of quantitative predictions (R2 = 0.971, accuracy = 0.938, limit of detection = 0.66 mM). These results highlight the potential of AgNP-modified substrates for reliable and reusable biochemical sensing applications.

A label-free fluorescence polarization technology for the detection of food additives.

A label-free fluorescence polarization technology for the detection of food additives.

Non-enzymatic electrochemical sensors using Polyaniline:Metal orotate nanocomposites for selective dopamine and glucose detection: Predicting sensor performance with machine learning algorithms

Non-enzymatic electrochemical sensors using Polyaniline:Metal orotate nanocomposites for selective dopamine and glucose detection: Predicting sensor performance with machine learning algorithms

Grain boundary/doping/architecture engineering in hierarchical N-doped CuO microflowers derived from Cu-based metal-organic framework architectures for highly efficient nonenzymatic glucose detection.

Grain boundary/doping/architecture engineering in hierarchical N-doped CuO microflowers derived from Cu-based metal-organic framework architectures for highly efficient nonenzymatic glucose detection.

Ru/Co-N,Zn-doped carbon nanocubes with multiple enzyme-like activities for high-efficiency glucose detection and self-supplying cascaded nanodrug in synergistic cancer therapy.

Ru/Co-N,Zn-doped carbon nanocubes with multiple enzyme-like activities for high-efficiency glucose detection and self-supplying cascaded nanodrug in synergistic cancer therapy.

Smartphone-based colorimetric correction analysis system for long-term urine monitoring of chronic kidney disease.

Smartphone-based colorimetric correction analysis system for long-term urine monitoring of chronic kidney disease.

Ratiometric fluorometry on microfluidic paper-based analytical device for simultaneous glucose and cholesterol detection using MnFe-layered double hydroxides as peroxidase mimic

Ratiometric fluorometry on microfluidic paper-based analytical device for simultaneous glucose and cholesterol detection using MnFe-layered double hydroxides as peroxidase mimic

One-step cascade method via glucose oxidase-copper ion complex for detecting glucose using a portable device.

One-step cascade method via glucose oxidase-copper ion complex for detecting glucose using a portable device.

Enhancing catalytic activity of smart polymer-UiO-66@GOx-HRP through temperature change for colorimetric detection of glucose

Enhancing catalytic activity of smart polymer-UiO-66@GOx-HRP through temperature change for colorimetric detection of glucose

Sparse group LASSO and nonlinear machine learning for frequency-feature optimization in noninvasive blood glucose monitoring via bioimpedance spectroscopy.

Diabetic patients need to test their blood glucose levels (BGL) frequently; however, traditional methods of blood collection and testing cause great pain to patients. In order to improve the quality of life of patients, this paper develops a noninvasive, portable, and continuous monitoring blood glucose detection system, which uses the latest bioimpedance integrated circuit to obtain the bioimpedance spectrum (BIS) of the inner forearm of the human body. The obtained BIS covers most of the frequencies up to 1MHz. A BGL estimation model is developed using sparse group least absolute shrinkage and selection operator combined with a Gaussian kernel function support vector regression to select the optimal frequencies and features for BIS. The correlations between different frequencies and features and BGL are investigated. We test our system on a collected dataset of clinical subjects, and the results show that the average mean absolute relative difference for all subjects is 9.90%, the root mean square error is 14.81 mg/dl, and the mean absolute error is 11.75 mg/dl. 100% of the estimates fall in zones A and B of the Clarke error grid. Preliminary results show that the use of BIS integrated circuits in combination with machine learning techniques promises to enable portable, noninvasive, continuous monitoring of BGLs.

K-doped Co3O4-decorated microneedle clip for non-enzymatic glucose detection in plant health monitoring

K-doped Co3O4-decorated microneedle clip for non-enzymatic glucose detection in plant health monitoring

Deep Learning Driven Volatile Organic Compounds Analysis for Lung Cancer Detection Using HC-PCF and Convolutional Neural Networks

A Volatile Organic Compounds (VOC) detection system for lung cancer diagnosis through deep learning (DL) technology is implemented in a special Hollow-Core Photonic Crystal Fibre (HC-PCF) sensor platform. COMSOL Multiphysics is used to simulate the HC-PCF. A hexagonal lattice structure of silica material with 1 μm pitch dimensions and 0.5 μm air hole diameters allow for exceptional light guidance and VOC interaction when detecting exhaled breath components. The sensor achieves a remarkable refractive index sensitivity of 920 nm/RIU for detecting cancerous and non-cancerous VOC profiles. The refractive index measurements of lung cancer-related VOC samples fell within 1.380 to 1.392, while VOC samples from healthy patients ranged from 1.350 to 1.360. Sensor spectral response data processing relied on a Convolutional Neural Network (CNN) model that was trained to distinguish different VOC signature patterns. When applied to a dataset of 1,200 breath samples consisting of 600 cancer-positive and 600 healthy specimens, the CNN architecture reached a 96.3% overall classification accuracy combined with 94.7% sensitivity and 97.8% specificity. Full Text: PDF References S. Sharma, L. Tharani, "Photonic Crystal Fiber Sensor Design for Enhanced Tumor Detection: Structural Optimization and Sensitivity Analysis", Photonics Lett. Poland 16(2), 25 (2024). CrossRef A. Yasli, "Cancer Detection with Surface Plasmon Resonance-Based Photonic Crystal Fiber Biosensor", Plasmonics 16, 1605 (2021). CrossRef S. Sharma, S. Das, C.S. Shieh et al. "Design and Numerical Analysis of a Gold-Coated Photonic Crystal Fiber Sensor for Metabolic Disorder Detection with Deep Learning Assistance", Plasmonics (2025). CrossRef N. Ayyanar, G.T. Raja, M. Sharma, D.S. Kumar, "Photonic Crystal Fiber-Based Refractive Index Sensor for Early Detection of Cancer", IEEE Sensors Journal 18(17), 7093 (2018). CrossRef S. Sharma, L. Tharani, "Photonics for AI and AI for photonics integration : Materials and characteristics", J. Information and Optimization Sciences 45(3), 805 (2024). CrossRef M. Babińska, A. Władziński, "Enhanced Sensitivity of Absorption Spectroscopy Glucose Detection by Machine Learning", Photonics Lett. Poland 17(1), 16 (2025). CrossRef M. Babińska, A. Władziński, T. Talaśka, M. Szczerska, "Machine Learning Enhanced Optical Fiber Sensor For Detection Of Glucose Low Concentration In Samples Mimicking Tissue", Photonics Lett. Poland 17(1), 20 (2025). CrossRef

Engineered MoSe2-CuO interfaces for next-generation non-enzymatic glucose sensors

The development of highly sensitive, stable, and cost-effective glucose sensors is critical for non-enzymatic glucose detection. Traditional enzymatic sensors suffer from poor stability and operational constraints, while some non-enzymatic sensors are expensive, prone to interference, and have short detection ranges. To address these challenges, the MoSe2-CuO nanocomposite has been prepared as an excellent electrocatalyst for glucose oxidation, leveraging the synergistic properties of two-dimensional (2D) transition metal dichalcogenides and metal oxides. The MoSe2-CuO heterostructures show enhanced electrochemical response due to strong interfacial coupling, improved electron transport, and abundant active sites for glucose adsorption and oxidation. It is found that the MoSe2-CuO nanocomposite-based sensor possesses a fast response time of 3 s, a low limit of detection of 0.025 μM, a high sensitivity of 2406 μA mM−1 cm−2, and a broad linear range for glucose detection. Furthermore, the composite electrode demonstrates excellent selectivity against common interfering species and exhibits long-term stability, ensuring reliability for real-world applications. The practical applicability of the proposed sensor is also validated through glucose detection in a fruit juice sample. Thus, the MoSe2-CuO nanocomposite may pave the way for next-generation non-enzymatic glucose sensors with high efficiency, stability, and affordability for its real-life applications.

Rapid Plasma Synthesis of Gold Nanoparticles Supported on MWCNTs for Electrochemical Detection of Glucose.

In this study, a simple, mild, and eco-friendly cold plasma-solution interaction method is employed to rapidly prepare gold colloids. Through modification with multi-walled carbon nanotubes (MWCNTs), a non-enzymatic glucose-sensing electrode material is successfully fabricated. The prepared electrode material is characterized via X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). The results show that compared with the chemically reduced AuNPs-C-MWCNTs, the plasma-prepared AuNPs-P-MWCNTs exhibits enhanced glucose catalytic performance with a higher sensitivity of 73 μA·mM-1·cm-2 (approximately 3.2 times that of AuNPs-C-MWCNTs), lower response time of 2.1 s, and ultra-low detection limit of 0.21 μM. It also demonstrates excellent selectivity, reproducibility (RSD = 4.37%), repeatability (RSD = 3.67%), and operational stability (RSD = 4.51%). This improvement can be attributed to the smaller particle size and better dispersion of plasma-derived AuNPs on the surface of MWCNTs. Furthermore, the AuNPs-P-MWCNTs surface is enriched with oxygen-containing functional groups, which is conducive to the enhancement of the hydrophilicity of the electrode surface. These synergistic effects facilitate the AuNPs-catalyzed glucose oxidation reaction, ultimately leading to superior glucose catalytic performance.