Chemosensors

28 pages, 7598 KiB

Open AccessReview

Nanoporous Layer Integration for the Fabrication of ISFET and Related Transistor-Based Biosensors

by Cristian Ravariu, Elena Manea, Cătălin Pârvulescu and Gabriel Dima

Chemosensors 2025, 13(8), 316; https://doi.org/10.3390/chemosensors13080316 - 20 Aug 2025

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More and more chemosensors and biosensors are turning to electronic transistors, as they are ideal transducers, precise in current response, miniaturized in size and capable of providing sub-picomolar detection limits. Among these devices, ISFET transistors—Ion-Sensitive Field-Effect Transistors—have the capacity of integrating ion-sensitive layers [...] Read more.

More and more chemosensors and biosensors are turning to electronic transistors, as they are ideal transducers, precise in current response, miniaturized in size and capable of providing sub-picomolar detection limits. Among these devices, ISFET transistors—Ion-Sensitive Field-Effect Transistors—have the capacity of integrating ion-sensitive layers together with field effect transistors of ultimate generations. Recent studies have indicated that nanoporous materials deposited or grown within the transistor gate space offer a dual advantage—a favorable environment for an optimal capture of liquid state receptors through capillary effects, but also of direct anchoring of these nanoporous structures on a Si wafer. This article aims to review the constructive evolutions of ISFET transistors, along with some newer nanowire devices, as well as their co-integration techniques with nanoporous materials, which are beneficial in the optimization of many chemosensors but of enzymatic biosensors in particular. Full article

(This article belongs to the Special Issue Feature Review Papers in Chemical/Bio-Sensors and Analytical Chemistry in 2025)

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14 pages, 4106 KiB

Open AccessArticle

AIPE-Active Fluorophenyl-Substituted Ir(III) Complexes for Detecting Trinitrophenols in Aqueous Media

by Jiahao Du, Ruimin Chen, Xiaoran Yang, Xiaona Li and Chun Liu

Chemosensors 2025, 13(8), 315; https://doi.org/10.3390/chemosensors13080315 - 20 Aug 2025

Viewed by 185

Abstract

Three fluorophenyl-substituted cyclometalated Ir(III) complexes (Ir1–Ir3) have been synthesized by changing the position of the fluorine atom. All complexes exhibit distinct aggregation-induced phosphorescence emission (AIPE) characteristics in CH₃CN/H₂O and demonstrate satisfactory detection performance for 2,4,6-trinitrophenols [...] Read more.

Three fluorophenyl-substituted cyclometalated Ir(III) complexes (Ir1–Ir3) have been synthesized by changing the position of the fluorine atom. All complexes exhibit distinct aggregation-induced phosphorescence emission (AIPE) characteristics in CH₃CN/H₂O and demonstrate satisfactory detection performance for 2,4,6-trinitrophenols (TNPs) with limits of detection of 124 nM, 101 nM, and 127 nM, respectively. In addition, Ir1–Ir3 possess excellent selectivity and anti-interference capability for TNP detection, showing outstanding performance even in different common water samples. The ultraviolet–visible absorption spectra and luminescence lifetimes of the complexes show that their quenching processes include both a static process and dynamic process, and the detection mechanism may be assigned to a combination of photo-induced electron transfer and an inner-filter effect. Full article

(This article belongs to the Special Issue Recent Advances in Chemical Sensors in Dalian University of Technology: Fundamental Science and Applications)

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13 pages, 1289 KiB

Open AccessArticle

Elemental Feature Extraction from Historical Pigments Through X-Ray Fluorescence Spectroscopy and Unsupervised Machine Learning

by Ivan Oliverio, Claudia Scatigno and Giulia Festa

Chemosensors 2025, 13(8), 314; https://doi.org/10.3390/chemosensors13080314 - 19 Aug 2025

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Abstract

The analysis of historical pigments contributes significantly to understanding the materials and techniques used in artworks and in preserving cultural heritage. This work introduces a novel methodology for classifying historical pigments combining X-ray fluorescence (XRF) spectroscopy with machine learning techniques. We applied this [...] Read more.

The analysis of historical pigments contributes significantly to understanding the materials and techniques used in artworks and in preserving cultural heritage. This work introduces a novel methodology for classifying historical pigments combining X-ray fluorescence (XRF) spectroscopy with machine learning techniques. We applied this approach to a representative heterogeneous dataset of historical pigments from the open-access spectral library INFRA-ART, as well as commercial oil colors and pigments with different particle sizes. A comparative analysis through principal component analysis (PCA) and hierarchical cluster analysis (HCA) demonstrates the advantages of the full-spectrum method over conventional peak-based strategies, offering improved classification performances and robustness. Employing the entire spectrum, it is possible to access additional key features for pigment discrimination that are discarded during the computation of the traditional methods and it is possible to have an efficient feature extraction even in more complex samples. This approach offers significant advantages by allowing the simultaneous processing of extensive datasets, which is useful for interpreting real-world scenarios in cultural heritage that are characterized by high heterogeneity. Full article

(This article belongs to the Special Issue Chemometrics Tools Used in Chemical Detection and Analysis)

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16 pages, 277 KiB

Open AccessReview

Manganese Nanoparticles for Heavy Metal Detection vs. Noble and Base Metal Nanoparticles; Prospects, Limitations, and Applications in Electroanalysis

by Vasiliki Keramari and Stella Girousi

Chemosensors 2025, 13(8), 313; https://doi.org/10.3390/chemosensors13080313 - 17 Aug 2025

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Abstract

This review examines the emerging role of manganese-based nanoparticles (Mn-NPs) in detecting heavy metal pollutants in environmental matrices. Heavy metals such as cadmium, lead, zinc, and copper pose serious environmental and health concerns due to their tendency to persist in ecosystems and accumulate [...] Read more.

This review examines the emerging role of manganese-based nanoparticles (Mn-NPs) in detecting heavy metal pollutants in environmental matrices. Heavy metals such as cadmium, lead, zinc, and copper pose serious environmental and health concerns due to their tendency to persist in ecosystems and accumulate in living organisms. As a result, there is a growing need for reliable methods to detect and remove these pollutants. Manganese nanoparticles offer unique advantages that scientists could consider as replacing other metal nanoparticles, which may be more expensive or more toxic. The physicochemical properties of Mn-NPs—including their multiple oxidation states, magnetic susceptibility, catalytic capabilities, and semiconductor conductivity—enable the development of multi-modal sensing platforms with exceptional sensitivity and selectivity. While Mn-NPs exhibit inherently low electrical conductivity, strategies such as transition metal doping and the formation of composites with conductive materials have successfully addressed this limitation. Compared to noble metal nanoparticles (Au, Ag, Pd) and other base metal nanoparticles (Bi, Fe₃O₄), Mn-NPs demonstrate competitive performance without the drawbacks of high cost, complex synthesis, poor distribution control, or significant aggregation. Preliminary studies retrieved from the Scopus database highlight promising applications of manganese-based nanomaterials in electrochemical sensing of heavy metals, with recent developments showing detection limits in the sub-ppb range. Future research directions should focus on addressing challenges related to scalability, cost-effectiveness, and integration with existing water treatment infrastructure to accelerate the transition from laboratory findings to practical environmental applications. Full article

(This article belongs to the Special Issue Feature Review Papers in Chemical/Bio-Sensors and Analytical Chemistry in 2025)

37 pages, 3861 KiB

Open AccessReview

Research Progress on Biomarkers and Their Detection Methods for Benzene-Induced Toxicity: A Review

by Runan Qin, Shouzhe Deng and Shuang Li

Chemosensors 2025, 13(8), 312; https://doi.org/10.3390/chemosensors13080312 - 16 Aug 2025

Viewed by 429

Abstract

Benzene, a well-established human carcinogen and major industrial pollutant, poses significant health risks through occupational exposure due to its no-threshold effect, leading to multi-system damage involving the hematopoietic, nervous, and immune systems. This makes the investigation of its toxic mechanisms crucial for precise [...] Read more.

Benzene, a well-established human carcinogen and major industrial pollutant, poses significant health risks through occupational exposure due to its no-threshold effect, leading to multi-system damage involving the hematopoietic, nervous, and immune systems. This makes the investigation of its toxic mechanisms crucial for precise prevention and control of its health impacts. Programmed cell death (PCD), an orderly and regulated form of cellular demise controlled by specific intracellular genes in response to various stimuli, has emerged as a key pathway where dysfunction may underlie benzene-induced toxicity. This review systematically integrates evidence linking benzene toxicity to PCD dysregulation, revealing that benzene and its metabolites induce abnormal subtypes of PCD (apoptosis, autophagy, ferroptosis) in hematopoietic cells. This occurs through mechanisms including activation of Caspase pathways, regulation of long non-coding RNAs, and epigenetic modifications, with recent research highlighting the IRP1-DHODH-ALOX12 ferroptosis axis and oxidative stress–epigenetic interactions as pivotal. Additionally, this review describes a comprehensive monitoring system for early toxic effects comprising benzene exposure biomarkers (urinary t,t-muconic acid (t,t-MA), S-phenylmercapturic acid (S-PMA)), PCD-related molecules (Caspase-3, let-7e-5p, ACSL1), oxidative stress indicators (8-OHdG), and genetic damage markers (micronuclei, p14ARF methylation), with correlative analyses between PCD mechanisms and benzene toxicity elaborated to underscore their integrative roles in risk assessment. Furthermore, the review details analytical techniques for these biomarkers, including direct benzene detection methods—direct headspace gas chromatography with flame ionization detection (DHGC-FID), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and portable headspace sampling (Portable HS)—alongside molecular imprinting and fluorescence probe technologies, as well as methodologies for toxic effect markers such as live-cell imaging, electrochemical techniques, methylation-specific PCR (MSP), and Western blotting, providing technical frameworks for mechanistic studies and translational applications. By synthesizing current evidence and mechanistic insights, this work offers novel perspectives on benzene toxicity through the PCD lens, identifies potential therapeutic targets associated with PCD dysregulation, and ultimately establishes a theoretical foundation for developing interventional strategies against benzene-induced toxicity while emphasizing the translational value of mechanistic research in occupational and environmental health. Full article

(This article belongs to the Special Issue Green Electrochemical Sensors for Trace Heavy Metal Detection)

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14 pages, 681 KiB

Open AccessArticle

Breathprint-Based Endotyping of COPD and Bronchiectasis COPD Overlap Using Electronic Nose Technology: A Prospective Observational Study

by Vitaliano Nicola Quaranta, Mariafrancesca Grimaldi, Silvano Dragonieri, Alessio Marinelli, Andrea Portacci, Maria Rosaria Vulpi and Giovanna Elisiana Carpagnano

Chemosensors 2025, 13(8), 311; https://doi.org/10.3390/chemosensors13080311 - 16 Aug 2025

Viewed by 339

Abstract

Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome with multiple clinical and inflammatory phenotypes. The coexistence of bronchiectasis, known as bronchiectasis–COPD overlap (BCO), identifies a subgroup with increased morbidity and mortality. Non-invasive breath analysis using electronic noses (e-noses) has shown promise in [...] Read more.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome with multiple clinical and inflammatory phenotypes. The coexistence of bronchiectasis, known as bronchiectasis–COPD overlap (BCO), identifies a subgroup with increased morbidity and mortality. Non-invasive breath analysis using electronic noses (e-noses) has shown promise in identifying disease-specific volatile organic compound (VOC) patterns (“breathprints”). Our aim was to evaluate the ability of an e-nose to differentiate between COPD and BCO patients, and to assess its utility in detecting inflammatory endotypes (neutrophilic vs. eosinophilic). In a monocentric, prospective, real-life study, 98 patients were enrolled over nine months. Forty-two patients had radiologically confirmed BCO, while fifty-six had COPD without bronchiectasis. Exhaled breath samples were analyzed using the Cyranose 320 e-nose. Principal component analysis (PCA) and discriminant analysis were used to identify group-specific breathprints and inflammatory profiles. PCA revealed significant breathprint differences between BCO and COPD (p = 0.021). Discriminant analysis yielded an overall accuracy of 69.6% (AUC 0.768, p = 0.037). The highest classification performance (76.8%) was achieved when distinguishing eosinophilic COPD from neutrophilic BCO. These findings suggest distinct inflammatory profiles that may be captured non-invasively. E-nose technology holds potential for the non-invasive endotyping of COPD, especially in identifying neutrophilic BCO as a unique inflammatory entity. Breathomics may support early, personalized treatment strategies. Full article

(This article belongs to the Special Issue Detection of Volatile Organic Compounds in Complex Mixtures)

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13 pages, 1789 KiB

Open AccessArticle

A LAP-Specific Hydrolyzable Fluorescent Probe for Assessing Combined Toxicity in Pesticide Mixtures

by Zhihao Xu, Xin Zhao, Ming Zhang, Yan Gao and Jingnan Cui

Chemosensors 2025, 13(8), 310; https://doi.org/10.3390/chemosensors13080310 - 16 Aug 2025

Viewed by 259

Abstract

Addressing the lack of dynamic monitoring methods for assessing the combined toxicity of mixed pesticides, this study developed a fluorescent probe, CCHL, specifically responsive to leucine aminopeptidase (LAP). The probe utilized Cy7-COOH (CCH) as the fluorophore, with fluorescence recovery triggered [...] Read more.

Addressing the lack of dynamic monitoring methods for assessing the combined toxicity of mixed pesticides, this study developed a fluorescent probe, CCHL, specifically responsive to leucine aminopeptidase (LAP). The probe utilized Cy7-COOH (CCH) as the fluorophore, with fluorescence recovery triggered by enzymatic hydrolysis. Spectral characterization confirmed a linear response between the probe and LAP activity within a concentration range of 0–0.9 μg/mL (R² = 0.992), along with excellent selectivity in the presence of coexisting biomolecules. Application experiments demonstrated that the combination of chlorfenapyr and beta-cyfluthrin significantly reduced LAP activity, revealing a notable antagonistic effect. The novel sensing strategy developed here provides a real-time, visualized analytical tool for evaluating the combined effects of mixed pollutants, demonstrating significant potential for environmental toxicology monitoring. Full article

(This article belongs to the Special Issue Recent Advances in Chemical Sensors in Dalian University of Technology: Fundamental Science and Applications)

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19 pages, 2963 KiB

Open AccessArticle

Theoretical Design of Composite Stratified Nanohole Arrays for High-Figure-of-Merit Plasmonic Hydrogen Sensors

by Jiyu Feng, Yuting Liu, Xinyi Chen, Mingyu Cheng and Bin Ai

Chemosensors 2025, 13(8), 309; https://doi.org/10.3390/chemosensors13080309 - 15 Aug 2025

Viewed by 242

Abstract

Fast, spark-free detection of hydrogen leaks is indispensable for large-scale hydrogen deployment, yet electronic sensors remain power-intensive and prone to cross-talk. Optical schemes based on surface plasmons enable remote read-out, but single-metal devices offer either weak H2 affinity or poor plasmonic quality. Here [...] Read more.

Fast, spark-free detection of hydrogen leaks is indispensable for large-scale hydrogen deployment, yet electronic sensors remain power-intensive and prone to cross-talk. Optical schemes based on surface plasmons enable remote read-out, but single-metal devices offer either weak H2 affinity or poor plasmonic quality. Here we employ full-wave finite-difference time-domain (FDTD) simulations to map the hydrogen response of nanohole arrays (NAs) that can be mass-produced by colloidal lithography. Square lattices of 200 nm holes etched into 100 nm films of Pd, Mg, Ti, V, or Zr expose an intrinsic trade-off: Pd maintains sharp extraordinary optical transmission modes but shifts by only 28 nm upon hydriding, whereas Mg undergoes a large dielectric transition that extinguishes its resonance. Vertical pairing of a hydride-forming layer with a noble metal plasmonic cap overcomes this limitation. A Mg/Pd bilayer preserves all modes and red-shifts by 94 nm, while the predicted optimum Ag (60 nm)/Mg (40 nm) stack delivers a 163 nm shift with an 83 nm linewidth, yielding a figure of merit of 1.96—surpassing the best plasmonic hydrogen sensors reported to date. Continuous-film geometry suppresses mechanical degradation, and the design rules—noble-metal plasmon generator, buried hydride layer, and thickness tuning—are general. This study charts a scalable route to remote, sub-ppm, optical hydrogen sensors compatible with a carbon-neutral energy infrastructure. Full article

(This article belongs to the Special Issue Innovative Gas Sensors: Development and Application)

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13 pages, 2518 KiB

Open AccessArticle

A Biosensor Based on Commercial R-SAW for Rapid and Sensitive Detection of E. coli

by Li Lv, Zhuoer Xu, Yicheng Zhou, Jayne Wu, Xueyong Zhang and Haochen Qi

Chemosensors 2025, 13(8), 308; https://doi.org/10.3390/chemosensors13080308 - 14 Aug 2025

Viewed by 328

Abstract

Escherichia coli (E. coli) is one of the most common strains that produce Shiga toxin, which can contaminate food and water, causing serious diseases and even endangering life. Therefore, the detection of E. coli is crucial for protecting public health. At [...] Read more.

Escherichia coli (E. coli) is one of the most common strains that produce Shiga toxin, which can contaminate food and water, causing serious diseases and even endangering life. Therefore, the detection of E. coli is crucial for protecting public health. At present, most traditional methods have disadvantages such as long detection cycles, high cost, and complex operations. This article proposed a novel commercial Rayleigh surface acoustic wave (R-SAW) biosensor for the detection of trace amounts of E. coli, which utilized the coordination reaction between carboxyl (-COOH) groups and aluminum ions (Al³⁺) to form the bio-enhanced probes, enabling the 5-terminal -COOH-modified aptamers to be preferentially enriched and directionally immobilized on the electrode surface. The biosensor could complete the detection within 100 s, with a linear detection range of 10³–10⁸ cells/mL, a limit of detection (LOD) as low as 732 cells/mL, and a selectivity ratio of 3270:1. This article conducted spiked detection on six types of food, indicating that the biosensor had the advantages of rapid speed, high sensitive, wide detection range, low LOD, strong specificity, and low cost, providing an economical and convenient solution for detecting trace amounts of E. coli in food. Full article

(This article belongs to the Section (Bio)chemical Sensing)

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21 pages, 4409 KiB

Open AccessArticle

Development and Application of Analytical Methods to Quantitate Nitrite in Excipients and Secondary Amines in Metformin API at Trace Levels Using Liquid Chromatography–Tandem Mass Spectrometry

by Ilyoung Ahn, Soyeon Lee, Min Ji Jung, Yeongeun Jeong, Ji Yun Kim, Minjeong Kim, Pan Soon Kim, Byung-Hoon Lee, Yong Moon Lee and Kyung Hun Son

Chemosensors 2025, 13(8), 307; https://doi.org/10.3390/chemosensors13080307 - 13 Aug 2025

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Abstract

Nitrosamine impurities have provoked numerous global medicine recalls due to their possible presence during drug manufacturing or storage. Regarding formulation of nitrosamine impurities, a key risk involves reactions between nitrosating agents (nitrite) in excipients and vulnerable amines as impurities or degradants. Rapid detection [...] Read more.

Nitrosamine impurities have provoked numerous global medicine recalls due to their possible presence during drug manufacturing or storage. Regarding formulation of nitrosamine impurities, a key risk involves reactions between nitrosating agents (nitrite) in excipients and vulnerable amines as impurities or degradants. Rapid detection across various sample types is essential to support pharmaceutical manufacturing. In this study, two methods were developed to detect nitrite in excipients and crucial secondary amines in active ingredient metformin hydrochloride at trace levels, respectively. The former method was developed based on the reaction of nitrite ions with 2,3-diaminonaphthalene to form 1-[H]-naphthotriazole (NAT), whereas the latter was based on amine tosylation. Mass spectrometric conditions were optimized using electrospray ionization in the positive mode. Multiple reaction monitoring transitions were determined at m/z 170 → 115 for NAT, and m/z 200.1 → 91 for dimethylamine (DMA) and 228.1 → 91 for diethylamine (DEA). These methods were validated using selected eight excipients or metformin hydrochloride in terms of specificity, linearity, accuracy, precision, robustness, limit of quantification (LOQ), and limit of determination according to the ICH guidelines. The results of the validation were within the acceptable criteria. Applicability of the methods was evaluated using 170 pharmaceutical samples donated by industries. The nitrite content in the excipients ranged from <LOQ to 4.74 ppm, with observed levels 1.3 to 6 times higher than the average (0.8 ppm) in the samples. The DMA levels in the metformin hydrochloride were within the limit (500 ppm) but varied significantly (0.2–209.2 ppm) among manufacturers. DEA was detected at lower levels (0.7–0.9 ppm). To mitigate the nitrosamine content in the metformin products, the excipient compositions were investigated by selecting those with low nitrite levels. As the types of impurities detected have become increasingly diverse and detection cycles have become more frequent, the requirement for preemptive safety management to relieve public anxiety is essential for regulatory aspects. Nitrite and secondary amines are crucial precursors to N-nitrosamine, and the suggesting approach could be a means to mitigate N-nitrosamine contamination. Full article

(This article belongs to the Section Analytical Methods, Instrumentation and Miniaturization)

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13 pages, 1923 KiB

Open AccessArticle

Construction of a Photonic Crystal (PC) Film Sensing Platform Based on Calcium Alginate Hydrogel for the Trichlorfon Detection

by Junjie Ren, Xia Li, Zhongxing Wang and Li Yu

Chemosensors 2025, 13(8), 306; https://doi.org/10.3390/chemosensors13080306 - 13 Aug 2025

Viewed by 273

Abstract

Trichlorfon, an organophosphorus pesticide widely used in agriculture and other fields, poses a severe risk to both food safety and human health. We developed a photonic crystal film sensing platform for detecting trichlorfon, a hazardous organophosphorus pesticide. The method exploits trichlorfon’s inhibition of [...] Read more.

Trichlorfon, an organophosphorus pesticide widely used in agriculture and other fields, poses a severe risk to both food safety and human health. We developed a photonic crystal film sensing platform for detecting trichlorfon, a hazardous organophosphorus pesticide. The method exploits trichlorfon’s inhibition of acetylcholinesterase (AChE). Normally, AChE catalyzes acetylcholine hydrolysis to produce acetic acid, which decomposes CaCO₃ to release Ca²⁺. This triggers calcium alginate hydrogel formation, increasing solution viscosity and trapping water. When trichlorfon inhibits AChE, hydrogel formation fails, leaving the solution in a low-viscosity sol state with abundant free water. Immersing the film in trichlorfon-containing sodium alginate solutions causes water absorption and film swelling due to free water. Higher trichlorfon concentrations reduce hydrogel formation, increase free water, and amplify film swelling, resulting in proportionally higher reflectivity. The platform demonstrates a wide linear range (1–250 ng/mL) and a low detection limit (0.4 ng/mL) for trichlorfon. Successful analysis of real samples confirms its practicality for residue detection. This label-free thin-film sensor shows significant potential for monitoring trichlorfon and other organophosphorus pesticides. Full article

(This article belongs to the Special Issue Feature Papers on Luminescent Sensing (Second Edition))

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18 pages, 4654 KiB

Open AccessArticle

Principal Component Analysis of Transient Potential Signals from Ion-Selective Electrodes for the Identification and Quantification of Different Ions

by José Antonio González-Franco, José Manuel Olmos, Alberto Ruiz and Joaquín Ángel Ortuño

Chemosensors 2025, 13(8), 305; https://doi.org/10.3390/chemosensors13080305 - 13 Aug 2025

Viewed by 329

Abstract

This study investigates the potential of transient potentiometric signals generated by an array of ion-selective electrodes (ISEs) as the basis for a potentiometric electronic tongue capable of identifying and quantifying a range of inorganic and organic cations. Six distinct polymeric membrane ISEs were [...] Read more.

This study investigates the potential of transient potentiometric signals generated by an array of ion-selective electrodes (ISEs) as the basis for a potentiometric electronic tongue capable of identifying and quantifying a range of inorganic and organic cations. Six distinct polymeric membrane ISEs were fabricated, differing in plasticizer type (either NPOE or DEHS), and in the presence or absence of a lipophilic ion exchanger (KTClPB) and/or an ionophore (DB18C6). Transient potential responses were recorded following the exposure of the electrode array to various cations at different concentrations. A total of 810 transient signals were analyzed through visual inspection and principal component analysis (PCA), revealing characteristic dynamic patterns influenced by membrane composition, ion type, and ion concentration. PCA was conducted both on the transient signals from each individual electrode and on the aggregated dataset comprising signals from the full six-electrode array (electronic tongue). The electronic tongue exhibited a markedly enhanced capacity for discriminating and quantifying ion concentrations in comparison to any single electrode. Full article

(This article belongs to the Special Issue Chemometrics in Electroanalysis and Electrochemical Sensing)

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14 pages, 1057 KiB

Open AccessArticle

Electrochemically Activated Screen-Printed Graphene Electrochemical Sensor for Daidzein Determination in Edible Peanut Oils

by Matias Alberto Cárdenas, Rubén Darío Alaníz, Robert D. Crapnell, Sebastian Noel Robledo, Héctor Fernández, Fernando Javier Arévalo, Adrian Marcelo Granero, Craig E. Banks and Gastón Darío Pierini

Chemosensors 2025, 13(8), 304; https://doi.org/10.3390/chemosensors13080304 - 13 Aug 2025

Viewed by 364

Abstract

In this work, we designed a novel and simple electrochemical approach for the determination of daidzein antioxidant (Dz) in peanut oil samples. The Dz determination was based on anodic stripping linear voltammetry using screen-printed graphene electrodes (SPGEs) activated in acidic media, where a [...] Read more.

In this work, we designed a novel and simple electrochemical approach for the determination of daidzein antioxidant (Dz) in peanut oil samples. The Dz determination was based on anodic stripping linear voltammetry using screen-printed graphene electrodes (SPGEs) activated in acidic media, where a strong adsorption of Dz on activated graphene was obtained. In this regard, electroanalytical parameters such as the scan rate, supporting electrolyte, pH, and accumulation step were optimized to ensure the best conditions for the selective and sensitive Dz quantification. The electrochemical method developed for the determination of Dz exhibits a linear behavior of the anodic peak current in the concentration range from 0.05 to 1 μM, with a limit of detection of 0.012 μM. The electrochemical sensor demonstrated to the capacity to quantify Dz in peanut oil samples at low concentrations without the necessity of an extensive sample pretreatment. Therefore, the electrochemical method proposed can be used as a new portable analytical tool for the in situ quality control of peanut oil samples. Full article

(This article belongs to the Special Issue Nanostructured Materials for Electrochemical Sensing)

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18 pages, 5524 KiB

Open AccessArticle

A Low-Power Portable Gas Sensor System with Adaptive ROIC and Wi-Fi Communication for Biomedical Applications

by Jun-Nyeong Kim, Soon-Kyu Kwon, Byung-Choul Park and Hyeon-June Kim

Chemosensors 2025, 13(8), 303; https://doi.org/10.3390/chemosensors13080303 - 12 Aug 2025

Viewed by 369

Abstract

This study presents a portable gas sensor system that achieves high performance while minimizing power consumption and production costs for biomedical applications. The proposed system integrates a low-power readout integrated circuit (ROIC) capable of processing large-amplitude sensor signals using a 1.2 V ADC, [...] Read more.

This study presents a portable gas sensor system that achieves high performance while minimizing power consumption and production costs for biomedical applications. The proposed system integrates a low-power readout integrated circuit (ROIC) capable of processing large-amplitude sensor signals using a 1.2 V ADC, significantly reducing the power consumption compared with conventional high-voltage solutions. To address the inherent limitations of single-core/single-thread microcontrollers, an optimized Wi-Fi communication algorithm is implemented, enabling real-time data transmission and accurate signal reconstruction without data loss. Experimental validation using a hydrogen gas detection setup demonstrated that the system achieves less than 0.15% error in reconstructed signals, while substantially reducing overall power consumption and component cost. Comparative analysis confirms that the proposed approach achieves a performance comparable to conventional systems while offering significant reductions in energy usage and hardware expense. These results demonstrate the feasibility of a scalable, low-cost solution for portable gas sensing, particularly in biomedical applications requiring precise and reliable monitoring. Full article

(This article belongs to the Special Issue Low-Cost Chemosensors for Applications in Environment, Health, Food, and Industry Process Control, 2nd Edition)

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25 pages, 1045 KiB

Open AccessReview

Harnessing the Potential of Nanotechnology for Liquid Biopsy of Cancer

by Prince Allawadhi, Vishakha Singh, Sachin Allwadhi, Anil Kumar Banothu, Kala Kumar Bharani and Amit Khurana

Chemosensors 2025, 13(8), 302; https://doi.org/10.3390/chemosensors13080302 - 12 Aug 2025

Viewed by 422

Abstract

Liquid biopsy offers dynamic and noninvasive analysis of cellular biomarkers, thereby presenting enormous potential for early detection of cancer, cancer staging, prediction of relapse, real-time examination of therapeutic efficacy, perception of therapeutic targets, and understanding the resistance mechanisms. Nanotechnology has emerged as a [...] Read more.

Liquid biopsy offers dynamic and noninvasive analysis of cellular biomarkers, thereby presenting enormous potential for early detection of cancer, cancer staging, prediction of relapse, real-time examination of therapeutic efficacy, perception of therapeutic targets, and understanding the resistance mechanisms. Nanotechnology has emerged as a novel tool to widen the application horizon of liquid biopsy. Several nanomaterials, nanodevices, nanostructures, and nanosensors have been explored for improved application of liquid biopsy for biomarker detection. The circulating tumor cells (CTCs), circulating tumor proteins (CTP), miRNA and extracellular vesicles (EVs) are some of the important biomarkers for detection by liquid biopsy in bodily fluids. Herein, we have discussed the state of the art and beyond in advances in nanotechnology and in increasing the specificity, sensitivity, and purity with which we detect liquid biopsy biomarkers. The opportunities and prospects of these advanced innovative nanomaterials and technologies in clinical applications are explored. Furthermore, various isolation and biosensing strategies for visualization and signal amplification using nanomaterials are summarized. The utilization of nanotechnology-based liquid biopsy may provide greater insights for improved treatment, diagnosis, and prognosis of cancer. Full article

(This article belongs to the Special Issue Advanced Biosensors for Diagnostic Applications)

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6 pages, 207 KiB

Open AccessEditorial

Advances in Chemical Sensors and Biosensors: Celebrating the 60th Birthday of Professors Huangxian Ju and Xueji Zhang

by Lin Ding, Haifeng Dong and Zhihui Dai

Chemosensors 2025, 13(8), 301; https://doi.org/10.3390/chemosensors13080301 - 11 Aug 2025

Viewed by 357

Abstract

Chemical sensors and biosensors, as a critical interdisciplinary field bridging analytical chemistry and chemical/biomedical engineering, have achieved remarkable progress over recent decades [...] Full article

(This article belongs to the Special Issue Dedicated to Professor Huangxian Ju and Professor Xueji Zhang on the Occasion of Their 60th Birthday for Their Outstanding Contributions to the Field of Chemical/Bio Sensors)

34 pages, 2273 KiB

Open AccessReview

The Development, Characteristics, and Challenges of Biosensors: The Example of Blood Glucose Meters

by Hsuan-Yu Chen and Chiachung Chen

Chemosensors 2025, 13(8), 300; https://doi.org/10.3390/chemosensors13080300 - 11 Aug 2025

Viewed by 550

Abstract

Numerous research projects on biosensors have been conducted, and a substantial number of academic studies and conference papers on biosensors are published annually. However, only a few biosensors have been commercialized. In this review, we took blood glucose meters as an example to [...] Read more.

Numerous research projects on biosensors have been conducted, and a substantial number of academic studies and conference papers on biosensors are published annually. However, only a few biosensors have been commercialized. In this review, we took blood glucose meters as an example to review the development, characteristics, and challenges of biosensors in the literature. The four subsystems of the physical sensors are illustrated to emphasize the importance of standardization and traceability in the sensors. The development of physical sensors, chemical sensors, and biosensors is introduced. The importance of reference materials as a standard for evaluating sensor performance is emphasized. The basic technique and four types of chemical transducers are described, and we show that the biosensors’ response must be processed with these chemical sensors. The characteristics of the glucose meter are introduced to explain the success of this sensor, especially the sensing materials of glucosidases. Two types of highly developed and competitive biosensors, continuous glucose monitoring (CGM) and paper-based biosensors, are introduced, and the trends and future implications of both biosensors are illustrated. The challenges facing biosensor development are summarized into several key factors, and future research directions are discussed. A list of factors for the successful commercialization of biosensors is also proposed. Full article

(This article belongs to the Special Issue Electrochemical Sensors and Biosensors: Recent Progress, Challenges, and Future Perspectives)

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35 pages, 3865 KiB

Open AccessReview

Sensors and Biosensors as Viable Alternatives in the Determination of Contaminants in Corn: A Review (2021–2025)

by Lívia M. P. Teodoro, Letícia R. G. Lacerda, Penelopy Costa e Santos, Lucas F. Ferreira and Diego L. Franco

Chemosensors 2025, 13(8), 299; https://doi.org/10.3390/chemosensors13080299 - 9 Aug 2025

Viewed by 725

Abstract

Corn is one of the most produced cereals in the world and exerts a significant economic impact on a billion-dollar market. It is utilized globally as a food source for humans and livestock and as a source of carbohydrates, fiber, vitamins, minerals, and [...] Read more.

Corn is one of the most produced cereals in the world and exerts a significant economic impact on a billion-dollar market. It is utilized globally as a food source for humans and livestock and as a source of carbohydrates, fiber, vitamins, minerals, and antioxidants, and also for fuel production and industrial products. However, their production is adversely affected by chemical contamination, primarily by mycotoxins, pesticides, and trace elements. Sensors and biosensors have become reliable alternatives to traditional spectroscopic and chromatographic methods for detecting these substances to enhance processes from harvesting to consumption. Here, we thoroughly evaluated studies on sensors and biosensors as alternatives to the growing demand for the determination of these contaminants as point-of-care devices in the past five years. This review reports innovative systems, using cutting-edge technology in expanded interdisciplinary research, supported by computational simulations to elucidate the interaction/reaction prior to experimentation, exploring the latest developments in nanostructures to create devices with excellent analytical performance. Many systems meet the demands of multiple and simultaneous determinations with fast results, in loco analyses with portable devices connected to personal smartphones, and simple operations to assist farmers, producers, and consumers in monitoring product quality throughout each stage of corn production. Full article

(This article belongs to the Special Issue Electrochemical Sensors and Biosensors for Food, Environmental and Biomedical Analysis)

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20 pages, 2235 KiB

Open AccessReview

Resistive-Based Nanostructured CeO₂ Gas Sensors: A Review

by Mahmoud Torkamani Cheriani, Ali Mirzaei and Jae-Hun Kim

Chemosensors 2025, 13(8), 298; https://doi.org/10.3390/chemosensors13080298 - 9 Aug 2025

Viewed by 270

Abstract

Air pollution and the emission of toxic gases represent a critical global concern, posing significant threats to human health and environmental stability. Resistive gas sensors are widely employed to detect toxic gases, owing to their cost-effectiveness, high stability, sensitivity, and swift dynamics. Among [...] Read more.

Air pollution and the emission of toxic gases represent a critical global concern, posing significant threats to human health and environmental stability. Resistive gas sensors are widely employed to detect toxic gases, owing to their cost-effectiveness, high stability, sensitivity, and swift dynamics. Among various sensing materials, comparatively less attention has been paid to CeO₂ despite its good catalytic activity and high stability. In this review paper, we are focusing on CeO₂ gas sensors in pristine, doped, decorated, and composite forms. Using numerous examples, we have shown the great potential of CeO₂ for gas sensing. The main features of CeO₂ as a gas sensor include excellent environmental stability, the abundance of oxygen vacancies, high mechanical strength, cost-effectiveness, and good catalytic activity. However, low electrical conductivity is the main shortage of CeO₂ as a gas sensor. With a high emphasis on the sensing mechanism, we believe that this review paper is highly useful for researchers working in this field. Full article

(This article belongs to the Special Issue Feature Review Papers in Chemical/Bio-Sensors and Analytical Chemistry in 2025)

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16 pages, 2496 KiB

Open AccessArticle

Silicon Nanowires Sensor Modified with Cu (II) Phthalocyanine Derivative for Phosphate Monitoring

by Milaine Jebali, Zina Fredj, Sameh Daboussi, Mounir Ben Ali and Mohamed Hassen

Chemosensors 2025, 13(8), 297; https://doi.org/10.3390/chemosensors13080297 - 9 Aug 2025

Viewed by 408

Abstract

This study reports the development of a highly sensitive electrochemical sensor for phosphate ion detection, utilizing silicon nanowires (SiNWs) as the transducing elements and a novel copper (II) phthalocyanine-acrylate polymer adduct (Cu (II) Pc-PAA) as the functional sensing layer. Silicon nanowires were fabricated [...] Read more.

This study reports the development of a highly sensitive electrochemical sensor for phosphate ion detection, utilizing silicon nanowires (SiNWs) as the transducing elements and a novel copper (II) phthalocyanine-acrylate polymer adduct (Cu (II) Pc-PAA) as the functional sensing layer. Silicon nanowires were fabricated via metal-assisted chemical etching (MACE) with etching durations of 15, 25, 35, 45, and 60 min. The SiNWs etched for 15 min exhibited the highest sensitivity, showing superior electrochemical performance. Functionalized SiNWs were systematically evaluated for phosphate ion (HPO₄²⁻) detection over a wide concentration range (10⁻¹⁰ to 10⁻⁶ M) using Mott–Schottky measurements. The surface morphology of the SiNWs was thoroughly characterized before and after Cu (II) Pc-PAA layer functionalization. The sensing material was analyzed using contact angle goniometry and scanning electron microscopy (SEM), confirming both its uniform distribution and effective immobilization. The sensor displayed a Nernstian behavior with a sensitivity of 28.25 mV/Decade and an exceptionally low limit of detection (LOD) of 1.5 nM. Furthermore, the capacitive sensor exhibited remarkable selectivity toward phosphate ions, even in the presence of potentially interfering anions such as Cl⁻, NO₃⁻, SO₄²⁻ and ClO₄⁻. These results confirm the sensor’s high sensitivity, selectivity, and fast response, underscoring its suitability for environmental phosphate ion monitoring. Full article

(This article belongs to the Special Issue Electrochemical Sensors and Biosensors for Food, Environmental and Biomedical Analysis)

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13 pages, 686 KiB

Open AccessArticle

Development and Validation of an HPLC-MS/MS Method for Quantifying Deoxynivalenol and Zearalenone Biomarkers in Dried Porcine Blood Spots

by Isadora Fabris Laber, Cristina Tonial Simões, Cristiane Rosa da Silva, Luara Medianeira de Lima Schlösser, Janine Alves Sarturi, Luriane Medianeira Carossi Leal, Renê Valmor Theobald and Carlos Augusto Mallmann

Chemosensors 2025, 13(8), 296; https://doi.org/10.3390/chemosensors13080296 - 9 Aug 2025

Viewed by 361

Abstract

Deoxynivalenol (DON) and zearalenone (ZEN) are common mycotoxins in animal feeds, and their metabolites can be detected in exposed animals. Traditional methods focus on mycotoxin detection in feed, whereas biomarker-based approaches are used for evaluating individual exposure. This study aimed to develop and [...] Read more.

Deoxynivalenol (DON) and zearalenone (ZEN) are common mycotoxins in animal feeds, and their metabolites can be detected in exposed animals. Traditional methods focus on mycotoxin detection in feed, whereas biomarker-based approaches are used for evaluating individual exposure. This study aimed to develop and validate a multi-analyte method for the detection of biomarkers of ZEN, DON, and their metabolites α-zearalanol (α-ZAL), zearalanone (ZAN), deepoxy-DON (DOM-1), and 3-acetyl-DON (3-ADON) in swine using dried blood spots (DBSs) on qualitative filter paper. Analysis was performed using high-performance liquid chromatography–tandem mass spectrometry. Blank blood samples from three male pigs were fortified with 20, 40, and 60 μg/L of each analyte. Aliquots of 40 μL were spotted onto filter paper and then extracted and analyzed. Method validation included evaluating limits of detection and quantification, linearity, matrix effects, recovery, repeatability, intermediate precision, and selectivity. All analytes were detectable in DBS. Also, ZEN, ZAN, DON, and DOM-1 met all validation criteria, with recovery values of 89.10%, 79.79%, 101.50%, and 79.50%, respectively. Both α-ZAL and 3-ADON showed lower recoveries (74.66% and 58.66%). The method was successfully validated for simultaneous analysis of ZEN, ZAN, DON, and DOM-1 in swine DBS, offering a practical and minimally invasive tool for biomonitoring mycotoxin exposure. Full article

(This article belongs to the Special Issue GC, MS and GC-MS Analytical Methods: Opportunities and Challenges (Third Edition))

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16 pages, 1719 KiB

Open AccessArticle

Geographical Origin Classification of Oolong Tea Using an Electronic Nose: Application of Machine Learning and Gray Relational Analysis

by Sushant Kaushal, Priya Rana, Chao-Chin Chung and Ho-Hsien Chen

Chemosensors 2025, 13(8), 295; https://doi.org/10.3390/chemosensors13080295 - 8 Aug 2025

Viewed by 330

Abstract

Taiwan accounts for 90% of the total oolong tea production and enjoys a good global reputation for its quality. In recent years, oolong tea from neighboring countries has been imported into Taiwan and sold as Taiwanese oolong at high prices. This study aimed [...] Read more.

Taiwan accounts for 90% of the total oolong tea production and enjoys a good global reputation for its quality. In recent years, oolong tea from neighboring countries has been imported into Taiwan and sold as Taiwanese oolong at high prices. This study aimed to rapidly classify oolong tea from four geographical origins (Taiwan, Vietnam, China, and Indonesia) using an electronic nose (E-nose) combined with machine learning. Color measurements were also conducted to support the classification. The electronic nose (E-nose) was utilized to analyze the aroma profiles of tea samples. To classify the samples, five machine learning models—linear discriminant analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN), artificial neural network (ANN), and random forest (RF)—were developed using 70% of the dataset for training and tested on the remaining 30%. Gray relational analysis (GRA) was applied to measure the relationship between sensor responses and reference tea origins. Multivariate analysis of variance (MANOVA) indicated a statistically significant effect of tea origin on color parameters, as confirmed by both Pillai’s trace and Wilks’ Lambda (Λ) tests (p = 0.000 < 0.05). Among the tested models, LDA and ANN achieved the highest overall classification accuracy (98.33%), with ANN outperforming in the discrimination of Taiwanese oolong tea, achieving 98.89% accuracy. GRA presented higher gray relational grade (GRG) values for Taiwanese tea samples compared to other origins and identified sensors S4, S6, and S14 as the dominant contributors. In conclusion, the E-nose combined with machine learning provides a rapid, non-destructive, and effective approach for geographical origin classification of oolong tea. Full article

(This article belongs to the Special Issue Applications of Electronic Nose (E-Nose) and Electronic Tongue (E-Tongue) in Food Quality)

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12 pages, 5808 KiB

Open AccessArticle

A High-Precision Hydrogen Sensor Array Based on Pt-Modified SnO₂ for Suppressing Humidity and Oxygen Interference

by Meile Wu, Zhixin Wu, Hefei Chen, Zhanyu Wu, Peng Zhang, Lin Qi, He Zhang and Xiaoshi Jin

Chemosensors 2025, 13(8), 294; https://doi.org/10.3390/chemosensors13080294 - 7 Aug 2025

Viewed by 322

Abstract

Humidity and oxygen have significant impacts on the accuracy of hydrogen detection, especially for metal oxide semiconductor sensors at room temperature. Addressing this challenge, this study employs a screen-printed 1 × 2 resistive sensor array made from an identical 1 wt.% platinum-modified tin [...] Read more.

Humidity and oxygen have significant impacts on the accuracy of hydrogen detection, especially for metal oxide semiconductor sensors at room temperature. Addressing this challenge, this study employs a screen-printed 1 × 2 resistive sensor array made from an identical 1 wt.% platinum-modified tin oxide nanoparticle material. Fabrication variability between the two sensing elements was intentionally leveraged to enhance array output differentiation and information content. Systematic hydrogen-sensing tests were conducted on the array under diverse oxygen and moisture conditions. Three distinct feature types—the steady-state value, resistance change, and area under the curve—were extracted from the output of each array element. These features, integrated with their quotient, formed a nine-feature vector matrix. A multiple linear regression model based on this array output was developed and validated for hydrogen prediction, achieving a coefficient of determination of 0.95, a mean absolute error of 125 ppm, and a mean relative standard deviation of 7.07%. The combined information of the array provided significantly more stable and precise hydrogen concentration predictions than linear or nonlinear models based on individual sensor features. This approach offers a promising path for mass-producing highly interference-resistant, precise, and stable room-temperature hydrogen sensor arrays. Full article

(This article belongs to the Section Materials for Chemical Sensing)

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16 pages, 3021 KiB

Open AccessReview

Microfluidic Paper-Based Sensors and Their Applications for Glucose Sensing

by Phan Gia Le and Sungbo Cho

Chemosensors 2025, 13(8), 293; https://doi.org/10.3390/chemosensors13080293 - 7 Aug 2025

Viewed by 506

Abstract

Recently, the incidence of diabetes has increased across all socioeconomic groups, with a notable increase in developing countries. Although advances in medical devices have enhanced healthcare accessibility, these benefits remain largely out of reach for individuals residing in remote areas. Concurrently, a variety [...] Read more.

Recently, the incidence of diabetes has increased across all socioeconomic groups, with a notable increase in developing countries. Although advances in medical devices have enhanced healthcare accessibility, these benefits remain largely out of reach for individuals residing in remote areas. Concurrently, a variety of devices have been created to detect glucose biomarkers. Among these, microfluidic paper-based sensors have received substantial attention due to their affordability, disposability, and ease of production. Research on microfluidic paper-based glucose sensors has become particularly prominent owing to their considerable potential and wide applicability, especially in the integration of artificial intelligence and machine learning in glucose sensor processing. This review aims to examine recent advancements and progress in the development of microfluidic paper-based glucose sensors over the past five years, highlighting their advantages, limitations, and prospects. The sensors combined with artificial intelligence and machine learning have potential for future applications. Full article

(This article belongs to the Special Issue Feature Review Papers in Chemical/Bio-Sensors and Analytical Chemistry in 2025)

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16 pages, 2057 KiB

Open AccessArticle

Comparison of Two Derivative Methods for the Quantification of Amino Acids in PM_2.5 Using GC-MS/MS

by Jungmin Jo, Na Rae Choi, Eunjin Lee, Ji Yi Lee and Yun Gyong Ahn

Chemosensors 2025, 13(8), 292; https://doi.org/10.3390/chemosensors13080292 - 7 Aug 2025

Viewed by 370

Abstract

Amino acids (AAs), a type of nitrogen-based organic compounds in the atmosphere, are directly and indirectly related to climate change, and as their link to allergic diseases becomes more known, the need for quantitative analysis of ultrafine dust (PM_2.5) will become [...] Read more.

Amino acids (AAs), a type of nitrogen-based organic compounds in the atmosphere, are directly and indirectly related to climate change, and as their link to allergic diseases becomes more known, the need for quantitative analysis of ultrafine dust (PM_2.5) will become increasingly necessary. When sensing water-soluble AAs using a gas chromatograph combined with a tandem mass spectrometer (GC-MS/MS), derivatization should be considered to increase the volatility and sensitivity of target analytes. In this study, two methods were used to compare and evaluate 13 AA derivatives in PM_2.5 samples: N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide with 1% tert-butyldimethylchlorosilane (MTBSTFA w/1% t-BDMCS), which is preferred for silylation, and ethyl chloroformate (ECF) with methanol (MeOH) for chloroformate derivatization. The most appropriate reaction conditions for these two derivative methods, such as temperature and time, and the analytical conditions of GC-MS/MS for the qualitative and quantitative analysis of AAs were optimized. Furthermore, the calibration curve, detection limit, and recovery of both methods for validating the quantification were determined. The two derivative methods were applied to 23 actual PM_2.5 samples to detect and quantify target AAs. The statistical significances between pairwise measurements of individual AAs detected by both methods were evaluated. This study will help in selecting and utilizing appropriate derivative methods for the quantification of individual AAs in PM_2.5 samples. Full article

(This article belongs to the Special Issue GC, MS and GC-MS Analytical Methods: Opportunities and Challenges (Third Edition))

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14 pages, 6958 KiB

Open AccessArticle

A pH-Responsive Liquid Crystal-Based Sensing Platform for the Detection of Biothiols

by Xianghao Meng, Ronghua Zhang, Xinfeng Dong, Zhongxing Wang and Li Yu

Chemosensors 2025, 13(8), 291; https://doi.org/10.3390/chemosensors13080291 - 6 Aug 2025

Viewed by 335

Abstract

Biothiols, including cysteine (Cys), homocysteine (Hcy), and glutathione (GSH), are crucial for physiological regulation and their imbalance poses severe health risks. Herein, we developed a pH-responsive liquid crystal (LC)-based sensing platform for detection of biothiols by doping 4-n-pentylbiphenyl-4-carboxylic acid (PBA) into [...] Read more.

Biothiols, including cysteine (Cys), homocysteine (Hcy), and glutathione (GSH), are crucial for physiological regulation and their imbalance poses severe health risks. Herein, we developed a pH-responsive liquid crystal (LC)-based sensing platform for detection of biothiols by doping 4-n-pentylbiphenyl-4-carboxylic acid (PBA) into 4-n-pentyl-4-cyanobiphenyl (5CB). Urease catalyzed urea hydrolysis to produce OH⁻, triggering the deprotonation of PBA, thereby inducing a vertical alignment of LC molecules at the interface corresponding to dark optical appearances. Heavy metal ions (e.g., Hg²⁺) could inhibit urease activity, under which condition LC presents bright optical images and LC molecules maintain a state of tilted arrangement. However, biothiols competitively bind to Hg²⁺, the activity of urease is maintained which enables the occurrence of urea hydrolysis. This case triggers LC molecules to align in a vertical orientation, resulting in bright optical images. This pH-driven reorientation of LCs provides a visual readout (bright-to-dark transition) correlated with biothiol concentration. The detection limits of Cys/Hcy and GSH for the PBA-doped LC platform are 0.1 μM and 0.5 μM, respectively. Overall, this study provides a simple, label-free and low-cost strategy that has a broad application prospect for the detection of biothiols. Full article

(This article belongs to the Special Issue Feature Papers on Luminescent Sensing (Second Edition))

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15 pages, 630 KiB

Open AccessArticle

Application of a Low-Cost Electronic Nose to Differentiate Between Soils Polluted by Standard and Biodegradable Hydraulic Oils

by Piotr Borowik, Przemysław Pluta, Miłosz Tkaczyk, Krzysztof Sztabkowski, Rafał Tarakowski and Tomasz Oszako

Chemosensors 2025, 13(8), 290; https://doi.org/10.3390/chemosensors13080290 - 5 Aug 2025

Viewed by 280

Abstract

Detection of soil pollution by petroleum products is necessary to remedy threats to economic and human health. Pollution by hydraulic oil often occurs through leaks from forestry machinery such as harvesters. Electronic noses equipped with gas sensor arrays are promising tools for applications [...] Read more.

Detection of soil pollution by petroleum products is necessary to remedy threats to economic and human health. Pollution by hydraulic oil often occurs through leaks from forestry machinery such as harvesters. Electronic noses equipped with gas sensor arrays are promising tools for applications of pollution detection and monitoring. A self-made, low-cost electronic nose was used for differentiation between clean and polluted samples, with two types of oils and three levels of pollution severity. An electronic nose uses the TGS series of gas sensors, manufactured by Figaro Inc. Sensor responses to changes in environmental conditions from clean air to measured odor, as well as responses to changes in sensor operation temperature, were used for analysis. Statistically significant response results allowed for the detection of pollution by biodegradable oil, while standard mineral oil was difficult to detect. It was demonstrated that the TGS 2602 gas sensor is most suitable for the studied application. LDA analysis demonstrated multidimensional data patterns allowing differentiation between sample categories and pollution severity levels. Full article

(This article belongs to the Special Issue Electronic Nose and Electronic Tongue for Substance Analysis)

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16 pages, 2634 KiB

Open AccessArticle

Optimized SILAR Growth of Vertically Aligned ZnO Nanorods for Low-Temperature Acetone Detection

by Brahim Ydir, Amine Ajdour, Mouad Soumane, Iulia Antohe, Gabriel Socol, Luiza-Izabela Toderascu, Driss Saadaoui, Imade Choulli, Radouane Leghrib and Houda Lahlou

Chemosensors 2025, 13(8), 289; https://doi.org/10.3390/chemosensors13080289 - 5 Aug 2025

Viewed by 408

Abstract

Vertically oriented morphologies of the semiconducting metal oxide (SMO) surface provide a simple and effective means of enhancing gas sensor performance. We successfully synthesized explicitly aligned ZnO nanorods using a simple automated SILAR technique to improve acetone detection. In this work, we found [...] Read more.

Vertically oriented morphologies of the semiconducting metal oxide (SMO) surface provide a simple and effective means of enhancing gas sensor performance. We successfully synthesized explicitly aligned ZnO nanorods using a simple automated SILAR technique to improve acetone detection. In this work, we found that vertically oriented morphologies, such as well-aligned ZnO nanorods, can significantly enhance the sensor response due to an increase in specific active area and electron mobility, allowing a faster response to changes in the gas environment. The optimal operating temperature for our ZnO nanorod-based sensors in detecting acetone gas is 260 °C. At this temperature, the sensors exhibit a 96% response with a rapid response time of just 3 s. The improved sensing performance is attributed to both electronic and chemical sensitization mechanisms, which enhance the formation of active sites and shorten electron diffusion paths. Full article

(This article belongs to the Special Issue Functionalized Material-Based Gas Sensing)

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17 pages, 3360 KiB

Open AccessArticle

Efficient and Selective Multiple Ion Chemosensor by Novel Near-Infrared Sensitive Symmetrical Squaraine Dye Probe

by Sushma Thapa, Kshitij RB Singh and Shyam S. Pandey

Chemosensors 2025, 13(8), 288; https://doi.org/10.3390/chemosensors13080288 - 4 Aug 2025

Viewed by 345

Abstract

A novel near-infrared (NIR) squaraine-based chemosensor, SQ-68, has been designed and synthesized for the sensitive and selective detection of Cu²⁺ and Ag⁺ ions, offering a compact solution for multi-analyte sensing. SQ-68 demonstrates high selectivity, with its performance influenced by the [...] Read more.

A novel near-infrared (NIR) squaraine-based chemosensor, SQ-68, has been designed and synthesized for the sensitive and selective detection of Cu²⁺ and Ag⁺ ions, offering a compact solution for multi-analyte sensing. SQ-68 demonstrates high selectivity, with its performance influenced by the solvent environment: It selectively detects Cu²⁺ in acetonitrile and Ag⁺ in an ethanol–water mixture. Upon binding with either ion, SQ-68 undergoes significant absorption changes in the NIR region, accompanied by visible color changes, enabling naked-eye detection. Spectroscopic studies confirm a 1:1 binding stoichiometry with both Cu²⁺ and Ag⁺, accompanied by hypochromism. The detection limits are 0.09 μM for Cu²⁺ and 0.38 μM for Ag⁺, supporting highly sensitive quantification. The sensor’s practical applicability was validated in real water samples (sea, lake, and tap water), with recovery rates ranging from 73–95% for Cu²⁺ to 59–99% for Ag⁺. These results establish SQ-68 as a reliable and efficient chemosensor for environmental monitoring and water quality assessment. Its dual-analyte capability, solvent-tunable selectivity, and visual detection features make it a promising tool for rapid and accurate detection of heavy metal ions in diverse aqueous environments. Full article

(This article belongs to the Special Issue Chemosensors Based on Advanced Materials for Environmental Detection and Monitoring)

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14 pages, 1443 KiB

Open AccessArticle

Mid-Infrared Spectroscopy with Variable Selection for the Rapid Quantification of Amylose Content in Starch

by Jingyue Qiao, Hongwei Wang, Jianing Bai, Yimin Liu, Xiaocheng Liu, Yanyan Zhang and Leiming Yuan

Chemosensors 2025, 13(8), 287; https://doi.org/10.3390/chemosensors13080287 - 4 Aug 2025

Viewed by 351

Abstract

Amylose content significantly influences the technological, quality, and nutritional properties of starchy foods. This study developed a rapid, non-destructive method to quantify amylose content in starch using mid-infrared (MIR) spectroscopy combined with chemometric techniques. Manually prepared starch mixtures with varying amylose levels were [...] Read more.

Amylose content significantly influences the technological, quality, and nutritional properties of starchy foods. This study developed a rapid, non-destructive method to quantify amylose content in starch using mid-infrared (MIR) spectroscopy combined with chemometric techniques. Manually prepared starch mixtures with varying amylose levels were scanned to obtain MIR spectra, which were preprocessed using smoothing and z-score normalization to reduce operational variability. Three variable selection methods, including bootstrap soft shrinkage (BOSS), competitive adaptive reweighted sampling (CARS), and uninformative variable elimination (UVE), were applied to select the useful spectra. A partial least square (PLS) model was then constructed to correlate selected spectral data with amylose content. The results revealed that the number and position of selected variables differed across different optimization methods, which influenced the model’s performance. It is worth noting that the optimized PLS model significantly reduced the root mean squared error of cross-validation (RMSECV) and improved prediction accuracy in 50 runs. In particular, the CARS-PLS model showed superior performance, achieving a correlation coefficient (R_p) of 0.964 and a root mean squared error of prediction (RMSEP) of 4.59, a 60% improvement over the original PLS model, which had an RMSEP of 11.56. These results highlight MIR spectroscopy’s potential, combined with optimized chemometric models, for accurate amylose quantification in food quality control. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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