Search Results (887)

The unique contributions of 2D Ti₃C₂ MXenes surface, electrical, and chemical features play a crucial role in determining toxic and flammable gas-sensing behavior. Specifically, its high electrical conductivity (metallic nature), layered nanosheet structure (nanosheets), and surface termination groups (−O, −F, and −OH) collectively contribute to excellent hydrogen (H₂) and ammonia (NH₃) gas-sensing behavior. This review systematically explores the impact of pristine and modified Ti₃C₂ MXene, including its interfaces with various metals and metal oxides for enhancing H₂ and NH₃ detection. Furthermore, the significance of room temperature operation and flexible gas sensing mechanisms is explored. Notably, integration of Ti₃C₂ MXene and sulfur nanosheets demonstrates rapid response and recovery times with detection limits at ppt level. Ti₃C₂ MXene-based interfaces also exhibit excellent long-term stability under various relative humidity conditions. The selective surface termination groups (−OH and −O) facilitate the formation of hydrogen bonds with NH₃ molecules for enhancing gas adsorption and sensing selectivity. In addition, the expansion of the interlayer spacing plays a vital role in improving the gas-sensing performance. Partial oxidation of Ti₃C₂ MXene into TiO₂ increases the interlayer distance, promoting faster diffusion of gas molecules and quicker sensor response. Overall, the intrinsic properties of Ti₃C₂ MXene and its composites significantly achieve high-performance room-temperature H₂ and NH₃ gas-sensing performance. Full article

High-performance ammonia (NH₃) sensors play a critical role in environmental protection and noninvasive medical diagnosis. This work reports a new NH₃ sensor based on Au-microsphere-decorated polyaniline (PANI) manufactured by a precise in situ inkjet printing method on a MEMS micro-hotplate. The in situ oxidative polymerization of aniline was performed directly on the MEMS platform using AuCl₃ as a bifunctional oxidant and precursor, with a hierarchical morphology of microspheres (~750 nm) and nanorods (~250 nm). Reduced from Au³⁺ in the polymerization reaction, Au microparticles achieve substantial catalytic promotion by virtue of chemical sensitization and spillover effect. The optimized Au–PANI MEMS sensor exhibits a superlative response of 201% toward 1 ppm NH₃ at room temperature, with an ultra-low theoretical limit of detection (LOD) of 0.42 ppb. Furthermore, the device demonstrates rapid response/recovery kinetics (76 s/72 s), exceptional selectivity against common interfering gases (SO₂, CO, H₂, etc.), and robust long-term stability with high response retention over two months. This research provides a scalable, cost-effective strategy for the mass production of miniaturized, high-sensitivity gas sensors for industrial and healthcare applications. Full article

Considering the various applications where detection is required—whether for industrial or medical purposes—providing cost-efficient, stable, and highly selective solutions remains challenging. Different industries require hydrogen detectors, because this gas has the potential to serve as a clean and versatile energy carrier; therefore, precise monitoring and feedback in such systems are of enormous importance. Simultaneously, the medical field is developing new therapeutic methods using hydrogen as a medical gas, while also utilizing it as a biomarker in exhaled breath for various gastric diseases. In this paper, a ZnO-based gas sensor, doped with Ag nanoparticles produced via the Solution Chemical Synthesis (SCS) method, was coated with a thin polymer film of poly(1,3,5,7-tetravinyl-1,3,5,7-tetramethylcyclotetrasiloxane) PV4D4 via initiated Chemical Vapor Deposition (iCVD). The results are promising: at a relatively high operating temperature of 350 °C, the sensor showed its highest registered response to H₂ gas (up to 23%). Compared to other gases studied at the same temperature, the sensor also showed potential for detecting 2-propanol, n-butanol, and ethanol, albeit with lower responses. Based on the dynamic response analysis, the fastest reaction time was also recorded at the highest operating temperature, thus showing versatile possibilities for using the specified detector. Full article

Chili products are vulnerable to the addition of unauthorized substances, including Sudan dyes, Rhodamine B, Basic Orange 2, poppy-derived materials and improperly used processing chemicals. Their analysis is complicated by the high contents of lipids, carotenoids, capsaicinoids and other co-extracted matrix components in chili powder, chili oil, chili sauce and composite seasonings. This review critically evaluates conventional and emerging sample-preparation strategies, including solid-phase extraction; the quick, easy, cheap, effective, rugged and safe (QuEChERS) procedure; deep eutectic solvent (DES)-assisted extraction; enhanced matrix removal for lipids (EMR-Lipid); and molecularly imprinted sorbents. Laboratory methods based on high-performance liquid chromatography (HPLC), liquid chromatography–tandem mass spectrometry (LC–MS/MS) and gas chromatography–mass spectrometry (GC–MS) are compared with enzyme-linked immunosorbent assay (ELISA), surface-enhanced Raman spectroscopy (SERS), electrochemical sensors, miniature mass spectrometry and artificial intelligence-assisted hyperspectral imaging (AI–HSI). The comparison considers representative limits of detection and quantification, recovery, precision, sample-preparation burden, cost, portability, validation status and regulatory role. LC–MS/MS remains the preferred confirmatory platform for targeted multi-residue analysis, whereas rapid and portable methods are more appropriate for screening and sample triage. A three-tier workflow linking rapid screening, laboratory confirmation, and emerging-risk identification and traceability is proposed. Future priorities include standardized chili reference materials, open AI training and validation datasets, greener DES-based extraction and interlaboratory validation of field-deployable methods. Full article

Soil pesticide-residue screening is important for ecological protection, food safety, and public health. However, conventional chromatographic and spectroscopic methods often require complex sample pretreatment, expensive instruments, trained operators, and long analysis times, which limits their use for rapid and large-scale screening. In this study, an electronic-nose system was developed for volatile-fingerprint classification of pesticide-treated loess soil. Six commercial pesticide formulations from three chemical categories were evaluated: deltamethrin and cyfluthrin as pyrethroids, glyphosate and chlorpyrifos as organophosphorus pesticides, and zineb and mancozeb as organosulfur pesticides. These compounds were selected to represent commonly used pesticides with different chemical structures and volatile profiles. A mirror-symmetric gas-sensing chamber was designed for a 26-sensor metal oxide semiconductor (MOS) array to improve gas-flow uniformity and response repeatability. A total of 960 pesticide-treated electronic-nose response curves were collected from four soil depths. Eight feature extraction methods and four classifiers were compared. The Synthetic Minority Over-sampling Technique (SMOTE) and Geometric SMOTE (G-SMOTE) were then evaluated using training-fold-only oversampling to reduce data-leakage risk in imbalanced classification. The results showed that k-nearest neighbors (KNN) combined with direct or transform-based features provided strong classification performance under controlled laboratory conditions. For minority-class recognition, SMOTE showed more consistent improvement than G-SMOTE in the tested pesticide–depth–feature combinations, although the effect depended on feature representation and pesticide class. These findings indicate that the proposed chamber/sensor-array/SMOTE framework is feasible for rapid volatile-fingerprint classification of pesticide-treated soil, but larger independent field datasets and quantitative chemical validation are still required before general deployment. Full article

The objective of this research is the development of a copper-based optical sensor for the detection of ovarian cancer marker CA 125 synthesized using low-temperature plasma. Optical materials produced with metals show unique advantages due to their ability to interact with light. There are different methods currently used for the synthesis of optical materials that can be associated with longer processing times and low material yield. The novelty of this study is the development of copper-based optical material (CuPy) using low-temperature plasma and subsequent modification for the detection of CA 125. Introduction: Plasma consists of a mixture of fully and partially ionized gas. It comprises diverse, highly energized species of atoms, ions, electrons, excited molecules, and charged species. These energized species are used to create new materials, for surface modifications, and in medical applications. Plasma can create a controlled environment for the creation of novel materials. Using low-temperature plasma, it will be possible to have precise control of the chemical composition and structure due to the creation of excited molecules, ions, and free radicals. Method: The CuPy material was synthesized using radio-frequency-assisted low-temperature plasma. Prior to synthesis, the plasma chamber was cleaned using radio frequency (RF) plasma without any reagents or gases. RF plasma was used for the synthesis of CuPy for 10 min and subsequent hydrogen plasma (50 sccm) for another 10 min. Two types of products were extracted from the chamber (one in water and another in methanol). These two products were analyzed using UV–visible absorbance spectroscopy, fluorescence spectroscopy, X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy (FTIR). The methanol extracted samples were further modified with CA 125 antibody. Zeta potential measurements were performed to confirm the binding of the CA 125 antibody to the sensor. The sensing efficacy of the sensor towards CA 125 antigen was monitored using fluorescence spectroscopy. Results: The absorbance spectrum of methanol extracted CuPy shows absorbances around 251 nm, 282 nm, and 339 nm. The extracted product exhibited a red edge excitation emission in the visible region. The elemental composition and oxidation state of the sample were evaluated using XPS. CA 125 antibody conjugation with CuPy was confirmed using UV–visible absorbance spectroscopy, fluorescence spectroscopy, and FTIR spectroscopy. The antibody binding resulted in the fluorescence shifts towards higher wavelengths with an increase in the emission intensity compared with CuPy. Zeta potential measurements also confirmed the binding of the CA 125 antibody to the sensor. Different concentrations of CA 125 antigen resulted in the quenching of fluorescence. This change in the fluorescence intensity was used for the detection of CA 125. Conclusions: A copper-based optical material was developed using low-temperature plasma, and it was found to be effective for the detection of CA 125 ovarian cancer marker. Full article

Rapid room-temperature identification of gases and volatile organic compounds remains challenging for compact sensing platforms, particularly when chemically related analytes must be discriminated using accessible sensing materials. In this work, we evaluate whether magneto-optical surface plasmon resonance (MOSPR), combined with multi-spot sensing and conventional SPR readout from the same chip, can provide complementary response features for improved gas/VOC discrimination. The sensing spots are made from accessible chemicals and nanoparticles with plasmonic and magnetic properties. The sensor chip consists of a multilayer structure of metallic materials with both plasmonic and magnetic properties featuring enhanced sensitivity and stability. Measurements are made using a custom-built MOSPR instrument at relevant analyte concentrations. Analyte-specific sensor channels were selected for concentration-dependent calibration while the complete multivariate data were first explored using principal component analysis for supervised analyte classification. The combined 16-feature MOSPR/SPR model achieved an overall accuracy of 88.3% and a balanced accuracy of 87.6% under leave-one-concentration-block-out cross-validation compared with 66.2% and 65.7%, respectively, for the SPR measurement alone. These results show that MOSPR provides response information that encompasses and extends that obtained from conventional SPR measurements, thereby improving analyte discrimination. The proposed approach may provide a basis for future environmental monitoring and industrial process control, including real-time monitoring of harmful gaseous emissions pending further validation under application-specific conditions. Full article

Hydrogen is a clean energy carrier essential for carbon neutrality, but its invisible and odorless nature poses significant safety risks, particularly during low-concentration leaks. Although metal oxide semiconductor (MOS) sensors offer fast response and high sensitivity, their ability to detect ppb-level hydrogen remains limited. In this work, we present a high-performance hydrogen gas sensor based on nickel-doped tin dioxide (Ni-SnO₂) nanorods, directly grown on planar electrodes via aerosol-assisted chemical vapor deposition (AACVD). By optimizing the Ni doping ratio and nanorod morphology, the 3 wt% Ni-SnO₂ sensor achieves a low detection limit of 100 ppb for H₂, demonstrating promising potential for low-concentration hydrogen detection. Moreover, the sensor exhibits outstanding selectivity, with a response to 100 ppm H₂ nearly six times higher than that to the next most responsive interfering gas (NH₃). Comprehensive XPS and Raman analyses reveal that Ni doping introduces abundant oxygen vacancies and lattice defects, which are the key origins of the enhanced sensing performance. Notably, the 3 wt% Ni-SnO₂ sensor strikes an optimal balance between lattice defects and structural stability, delivering both high sensitivity and good moisture resistance with minimal baseline drift over weeks of operation. This work establishes a facile and scalable AACVD strategy for engineering defect-rich SnO₂ nanostructures, enabling sub-ppm hydrogen detection with high selectivity and long-term stability—addressing a critical gap in practical hydrogen safety monitoring. Full article

Density Functional Theory (DFT) calculations were applied at the B3LYP/6-311G+(d,p) level to examine how nitrogen (N) and boron (B) and combined nitrogen/boron doping (N/B) affected the electronic properties and chemical behavior of graphene oxide (GrO). The work aimed to measure how global reactivity descriptors, including ionization potential, chemical hardness, and electrophilicity, changed when dopants entered the system while evaluating their prediction accuracy for gas sensing performance against NH₃ and H₂O and CO₂. The results show that undoped GrO exhibits a HOMO/LUMO gap value of 2.9059 eV while the introduction of dopants increases reactivity through gap reduction because N-doping decreased the gap to 1.3622 eV, B-doping reduced it to 1.3388 eV, and co-doping (GrO-NB) led to a gap of 1.9897 eV. The TDM analysis and the gas interaction energy gap results show that GrO-NB-H₂O exhibits the strongest interaction which results in chemical reactivity through its lowest ΔE of 1.9565 eV, establishing itself as a highly sensitive water vapor sensor when compared with NH₃ and CO₂. With adsorption energies of −0.1986, −0.1742, and −0.0735 eV for NH₃, H₂O, and CO₂, respectively, the N/B co-doped graphene oxide demonstrated favorable and reversible physisorption, underscoring its potential for gas sensing applications. The results offer an essential understanding of how N/B co-doping influences the electronic and adsorption characteristics of graphene oxide, thereby supporting its potential use in graphene-based sensing technologies. Full article

This study evaluated the use of an E-nose using a piercing-assisted volatile extraction as a practical and non-destructive tool for distinguishing between three muscle types (biceps femoris—BF; semitendinosus—ST; and semimebranosus—SM) in 30-month ripened dry-cured Bísaro hams (n = 23). The muscles were analyzed for volatile organic compounds (VOC) using gas chromatography-mass spectrometry (GC-MS) and for signal profiles obtained from an E-nose system composed of metal oxide (SnO₂) sensors. Sensor signals were standardized using Z-score normalization prior to chemometric modeling. Linear discriminant analysis (LDA) was used to evaluate the capability of the MOS-based E-nose to differentiate the VOC profiles of Bísaro ham across its main muscle types. The model trained on Z-score-standardized sensor signals achieved classification accuracies of 94.3% and 80.0% for the training and external test sets, respectively, demonstrating good predictive performance and robustness. When compared with the VOC-based LDA model (94.4% and 78.6% for the training and test sets, respectively), the E-nose showed comparable classification performance and slightly higher predictive capability in the external validation set. The first two discriminant functions explained 88.01% and 11.99% of the discriminant variance, respectively, indicating that most of the discrimination occurred along a single dominant axis. To chemically interpret the sensor-based discrimination, multiple linear regression models were established between the LDA scores and VOC concentrations. The first discriminant function was significantly associated with compounds related to lipid oxidation and aroma development, particularly 2-pentylfuran, butanoic acid, hexanoic acid, hexanal, and benzaldehyde (R² = 0.617; p < 0.001), whereas the second discriminant function showed a weaker but significant relationship with hexanal, 3-methylbutanal, butanoic acid, and hexanoic acid (R² = 0.202; p = 0.006). These findings demonstrate that the E-nose is capable of capturing meaningful chemical information associated with muscle-specific volatile profiles and can provide a rapid, non-destructive, and cost-effective alternative for the characterization and classification of dry-cured Bísaro ham. Full article

Gas-insulated switchgears (GISs) and gas-insulated transmission lines (GILs) are essential for large-capacity power transmission in demanding environments, such as high drops, large spans, and heavy pollution. As the core components providing both electrical insulation and mechanical support, ultra-high voltage (UHV) epoxy-based insulators often suffer from high internal residual stress. This issue, compounded by a lack of reliable detection methods, frequently results in equipment being commissioned with hidden defects. To address this, this review first examines the formation mechanisms of curing deformation and residual stress in oversized insulators based on cure kinetics and thermo-chemical coupling models. Subsequently, it provides a comprehensive summary of current residual stress measurement techniques, comparing the applicability and limitations of embedded sensors, direct mechanical measurements, and indirect non-destructive testing (NDT) methods. Finally, by coupling residual stress with filler sedimentation, the stress distribution patterns and mechanical reliability of epoxy-based insulators across different life-cycle stages are analyzed. These insights offer valuable theoretical references for the structural design, process optimization, and performance evaluation of oversized epoxy-based insulators, ultimately contributing to the intrinsic safety of UHV power equipment. Full article

Atractylodis Rhizoma is an important traditional Chinese medicinal material derived from two botanical origins, Maocangzhu (MCZ) and Beicangzhu (BCZ), which are difficult to distinguish by conventional morphological identification because of their similar appearance. However, differences in botanical origin may lead to variations in odor, taste, volatile constituents, and non-volatile metabolites, thereby affecting quality evaluation and clinical application. This study aimed to systematically characterize the sensory and chemical differences between MCZ and BCZ and to identify potential markers for their discrimination. A multi-dimensional analytical strategy combining electronic nose, electronic tongue, headspace gas chromatography–ion mobility spectrometry (HS-GC-IMS), and ultra-high-performance liquid chromatography–Orbitrap high-resolution mass spectrometry (UPLC-Orbitrap MS) was established. Electronic nose and electronic tongue were used to digitize odor and taste characteristics, HS-GC-IMS was employed to profile volatile organic compounds, and UPLC-Orbitrap MS was applied to characterize non-volatile metabolites. Principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), variable importance in projection (VIP) screening, permutation tests, and correlation analysis were further used to evaluate discrimination performance and screen characteristic markers. The electronic nose results showed that MCZ and BCZ exhibited distinct odor profiles, with W5S, W1W, and W1S identified as the main differential sensors, suggesting that nitrogen oxides, terpenoids, inorganic sulfides, and short-chain alkanes contributed to the odor differences between the two origins. Electronic tongue analysis further demonstrated clear taste discrimination, with sourness and richness identified as the key taste indicators. HS-GC-IMS detected 108 volatile organic compounds, and 24 volatile markers with VIP > 1.2 were screened as important contributors to the differentiation of MCZ and BCZ. Among them, propionic acid and 5-methyl-2-furancarboxaldehyde were mainly distributed in MCZ, whereas (E)-caryophyllene was present only or at higher levels in BCZ, indicating its potential as a characteristic volatile marker of BCZ. UPLC-Orbitrap MS detected 78 non-volatile constituents, and OPLS-DA screened 17 key non-volatile differential metabolites with VIP > 1.2. These results indicated that MCZ and BCZ could be clearly separated not only by sensory signals but also by volatile and non-volatile chemical profiles. This study revealed that the differences between MCZ and BCZ are mainly reflected in odor-active volatile compounds, key taste indicators, and non-volatile differential metabolites. The integration of electronic nose, electronic tongue, HS-GC-IMS, and UPLC-Orbitrap MS provides a comprehensive and reliable strategy for distinguishing the two botanical origins of Atractylodis Rhizoma. These findings provide valuable insights into the material basis underlying the sensory and chemical differences between MCZ and BCZ and offer scientific support for accurate authentication, quality evaluation, and rational clinical application of Atractylodis Rhizoma. Full article

To address prevalent industrial challenges, including the high cost of fabricating microstructures via photolithography and 3D printing, impurity residues easily generated by conventional physical/chemical pore-forming techniques, and the limited sensitivity of regular capacitive sensors, this paper innovatively proposes an integrated low-temperature in situ gas foaming strategy using ammonium bicarbonate for the fabrication of porous TPU-based ionic gels. Relying on the complete gaseous decomposition property of ammonium bicarbonate upon heating, a three-dimensionally interconnected continuous porous network is spontaneously constructed inside the polymer matrix. Thermoplastic polyurethane (TPU) is selected as the continuous polymer phase, and [EMIM][TFSI] imidazolium ionic liquid is blended as the ion source to synthesize composite ionic gel substrates. A PDMS composite slurry filled with graphene is employed to prepare flexible substrates, followed by low-temperature oxygen plasma surface modification to introduce polar functional groups such as hydroxyl and carboxyl onto electrode surfaces. A standard sandwich-structured ionic pressure sensor with the configuration of “top modified electrode—porous ionic gel dielectric layer—bottom modified electrode” is finally assembled. The porous framework and modified electrodes constitute a dual synergistic enhancement system: the porous structure markedly reduces the equivalent elastic modulus of the gel and improves its compressive deformation capacity; polar-modified electrodes optimize the interfacial compatibility between electrodes and gels, shorten ion migration paths and lower interfacial contact resistance. Systematic calibration of multiple batches of parallel samples reveals that the as-fabricated sensor achieves a high sensitivity of 25.3 kPa⁻¹ across the full measuring range from 0 to 1000 kPa with a linear fitting coefficient R² = 0.992. The loading response time and unloading recovery time of the device are 60 ms and 80 ms respectively, with a performance degradation of less than 3% after 1000 consecutive loading–unloading cycles, featuring low hysteresis error and excellent signal repeatability. Multi-scenario in vivo wearable tests on human subjects verify that the device can precisely capture subtle fluctuations of radial artery pulse and periodic laryngeal deformation during swallowing, distinguish characteristic waveform patterns of various English words according to differences in vocal cord vibration, and accurately detect bending motions when attached to finger joints. The entire fabrication process adopts common chemical raw materials and standard laboratory equipment without expensive micro-nano processing facilities, featuring convenient raw material procurement and high process fault tolerance, which enables large-area coating-based mass production. This work delivers a novel technical route for the low-cost large-scale production of high-performance ionic flexible sensors and bears significant industrialization reference value for applications in wearable medical monitoring, bionic robotic electronic skin, flexible human–machine interactive touch panels and other related fields. Full article

Conventional chemical analysis relies on costly laboratory instrumentation, while current e-nose systems are expensive for widespread deployment. New opportunities for low-cost, accessible e-nose applications are emerging for diverse fields due to the rapid evolution of inexpensive sensor technologies. We developed a framework that enables rapid integration of newly available low-cost gas sensors into functional e-nose systems, continuously evaluating them as they become commercially available. By characterizing their performance in multi-sensor arrays that mimic biological olfaction, the framework demonstrates effective odor discrimination in a low-cost e-nose system through coordinated behavior of a heterogeneous sensor array. Our testing approach includes sensor sensitivity, selectivity, and stability, which are to be combined with appropriate pattern recognition and AI algorithms in the future for effective chemical discrimination. This work provides a pathway for continuously updating e-nose technology with the latest available sensors in a cost-effective manner, thereby making advanced chemical sensing accessible for resource-limited settings and enabling large-scale deployment in real-world applications with future potential applications such as food quality monitoring, environmental sensing, smart agriculture, etc. Full article

High-entropy alloys (HEAs), composed of five or more principal elements in near-equimolar ratios, have emerged as a groundbreaking class of materials for next-generation flexible electronics. This review systematically examines the unique potential of HEAs as sensing materials, moving beyond their traditional role as structural components. We first elucidate the fundamental mechanisms—core effects including lattice distortion, sluggish diffusion, and the cocktail effect—that endow HEAs with an exceptional synergy of high strength, good ductility, tunable electrical resistivity, and superior electrocatalytic activity. Subsequently, we critically analyze the state-of-the-art strategies for processing HEA-based micro/nano structures, including mechanical alloying, wet-chemical synthesis, and non-equilibrium deposition techniques, with an emphasis on their compatibility with flexible substrates. The core of the review categorizes and discusses the latest advances in HEA-based flexible sensors for strain/stress, gas, and electrochemical (e.g., glucose, biomarkers, heavy metals) detection, highlighting the structure–property–performance relationships. Representative studies have demonstrated that HEA flexible strain sensors achieve a temperature coefficient of resistance as low as 45.59 ppm/K with no signal drift over 6000 stretching cycles; room-temperature hydrogen sensors reach a detection limit down to 31 ppb with a response time of 19 s; and non-enzymatic glucose sensors deliver a sensitivity up to 3043 μA·mM⁻¹·cm⁻². Finally, we summarize the key challenges—such as manufacturing scalability, long-term stability under dynamic deformation, and cost-effectiveness—and provide a forward-looking perspective on promising research directions, including high-throughput compositional screening, multi-functional sensor arrays, and the integration of machine learning for rational material design. Full article