Search Results (2,040)

Benzene, as a typical toxic gas and carcinogen, is an important detection object in the field of environmental monitoring. However, it remains challenging for the conventional resistance-type gas sensor to effectively detect low-concentration (ppb-level) benzene gas molecules, owing to their insufficient reaction activation energy, especially when operating at room temperature. Herein, a field-effect transistor (FET)-type gas sensor using carbon nanotubes as a channel material is proposed for the efficient detection of trace benzene, where carbon nanotubes (CNTs) with high semiconductor purity act as the main channel material, and ZnO/WS₂ nanocomposites serve as the gate sensitive material. On the basis of the remarkable amplification effect in CNTs-based FET, the proposed gas sensor manifests desirable sensitive ability with the detection limit as low as 500 ppb for benzene even working at room temperature, and the sensor also exhibits fast response speed (90 s), high consistency with a response deviation of less than 5%, and long-term stability of up to 30 days. Furthermore, utilizing Tenax TA as the screening unit, the as-proposed gas sensor can achieve the feasible selective detection of benzene. These experimental results demonstrate that the strategy proposed here can provide significant guidance for the development of high-performance gas sensors to detect trace benzene gas at room temperature. Full article

Clean hydrogen is a key aspect of carbon neutrality, necessitating robust methods for monitoring hydrogen concentration in critical infrastructures like pipelines or power plants. While semiconducting metal oxides such as In₂O₃ can monitor gas concentrations down to the ppm range, they often exhibit cross-sensitivity to other gases like H₂O. In this study, we investigated whether cyclic optical illumination of a gas-sensitive In₂O₃ layer creates identifiable changes in a gas sensor’s electronic resistance that can be linked to H₂ and H₂O concentrations via machine learning. We exposed nanostructured In₂O₃ with a large surface area of 95 m² g⁻¹ to H₂ concentrations (0–800 ppm) and relative humidity (0–70%) under cyclic activation utilizing blue light. The sensors were tested for 20 classes of gas combinations. A support vector machine achieved classification rates up to 92.0%, with reliable reproducibility (88.2 ± 2.7%) across five individual sensors using 10-fold cross-validation. Our findings suggest that cyclic optical activation can be used as a tool to classify H₂ and H₂O concentrations. Full article

The green extraction of total phenolic compounds, flavonoids, anthocyanins, and tannins from grape marc was optimized using response surface methodology. The extracts were characterized and analyzed using LC-ESI-QTOF-MS/MS, and free radical scavenging capacity was evaluated. An efficient green extraction method is crucial for improving the recovery rates of these high-value phytochemicals and for sustainably reusing wine by-products. Our study optimized parameters for both conventional and ultrasound-assisted extraction methods, including solution pH, extraction temperature, liquid-to-solvent ratio, and ultrasonic amplitude. The optimized conditions for conventional extraction were identified as 60% ethanol with a pH of 2, a solvent-to-solid ratio of 50:1, extraction time of 16 h at a temperature of 49.2 °C. For ultrasound-assisted extraction, the optimized conditions were determined as 60% ethanol with a pH of 2, a solvent-to-solid ratio of 50:1, and an amplitude of 100% for 5.05 min at a temperature of 60 °C. We also demonstrated that lowering the temperature to 49.5 °C improves the energy efficiency of the extraction process with a minor reduction in recovery rates. Considering all factors, ultrasound-assisted extraction is more suitable for efficiently recovering bioactive compounds from grape marc. Full article

Staphylococcus aureus is one of the leading causes of skin and soft tissue infections, and it is even life-threatening if it enters the bloodstream, lung or heart. In the present work, we proposed a novel colorimetric biosensor for the detection of S. aureus through hydrogen peroxide consumption. An onion-like carbon nanozyme with high peroxidase-like activity was prepared, which competed with the endogenous catalase of S. aureus in consuming hydrogen peroxide. This reaction was further characterized by the colorimetric reaction of 3,3′,5,5′-tetramethylbenzidine. The results showed that our approach allowed for the simple and rapid determination of S. aureus, with a linear range of 2 × 10⁴ to 2 × 10⁷ CFU/mL. Moreover, our method displayed good selectivity, with Bacillus subtilis and Escherichia coli showing negligible responses at the concentration of 2 × 10⁵ CFU/mL. The application of the as-prepared biosensor to analyze S. aureus in real water samples yielded recovery rates ranging from 95% to 112%, with relative standard deviations less than 7%. The method demonstrated good accuracy and specificity, which offers a novel approach for the simple and selective detection of S. aureus. Full article

This work reports on the development of an analyte sampling strategy on a plasmonic substrate to amplify the detection capability of a dual analytical system, paper spray ionization–mass spectrometry (PSI-MS) and surface-enhanced Raman spectroscopy (SERS). While simply applying only an analyte solution to the plasmonic paper results in a limited degree of SERS enhancement, the introduction of plasmonic gold nanoparticles (AuNPs) greatly improves the SERS signals without sacrificing PSI-MS sensitivity. It is initially revealed that the concentration of AuNPs and the type of analytes highly influence the SERS signals and their variations due to the “coffee ring effect” flow mechanism induced during sampling and the degree of the interfacial interactions (e.g., van der Waals, electrostatic, covalent) between the plasmonic substrate and analyte. Subsequent PSI treatment at high voltage conditions further impacts the overall SERS responses, where the signal sensitivity and homogeneity significantly increase throughout the entire substrate, suggesting the ready migration of adsorbed analytes regardless of their interfacial attractive forces. The PSI-induced notable SERS enhancements are presumably associated with creating unique conditions for local aggregation of the AuNPs to induce effective plasmonic couplings and hot spots (i.e., electromagnetic effect) and for repositioning analytes in close proximity to a plasmonic surface to increase polarizability (i.e., chemical effect). The optimized sampling and PSI conditions are also applicable to multi-analyte analysis by SERS and MS, with greatly enhanced detection capability and signal uniformity. Full article

The integration of advanced diagnostic technologies in healthcare is crucial for enhancing the accuracy and efficiency of disease detection and management. This paper presents an innovative approach combining machine learning-assisted 3D flexible fiber-based organic transistor (FOT) sensors for high-accuracy metabolite analysis and potential diagnostic applications. Machine learning algorithms further enhance the analytical capabilities of FOT sensors by effectively processing complex data, identifying patterns, and predicting diagnostic outcomes with 100% high accuracy. We explore the fabrication and operational mechanisms of these transistors, the role of machine learning in metabolite analysis, and their potential clinical applications by analyzing practical human blood samples for hypernatremia syndrome. This synergy not only improves diagnostic precision but also holds potential for the development of personalized diagnostics, tailoring treatments for individual metabolic profiles. Full article

This paper reports the use of nanoparticles (NPs)-modified voltammetric sensors for the rapid determination of glycerol in the presence of ethanol and methanol, which are used in the transesterification reaction of biodiesel production. Two different modified electrodes have been prepared to form the electronic tongue (ET): copper hexacyanoferrate NPs obtained by chemical synthesis and mixed into graphite/epoxy (GEC) electrode, and nickel hydroxide NPs electrodeposited in reduced graphene oxide onto a GEC electrode. The response characteristics of these electrodes were first evaluated by building the respective calibration against glycerol, ethanol, and methanol. The electrodes demonstrated good stability during their analytical characterization, while principal component analysis confirmed the differentiated response against the different alcohols. Finally, the quantification of mixtures of these substances was achieved by a genetic algorithm-artificial neural networks (GA-ANNs) model, showing satisfactory agreement between expected and obtained values. Full article

Underwater methane (CH₄) detection technology is of great significance to the leakage monitoring and location of marine natural gas transportation pipelines, the exploration of submarine hydrothermal activity, and the monitoring of submarine volcanic activity. In order to improve the safety of underwater CH₄ detection mission, it is necessary to study the effect of hydrogen sulfide (H₂S) in leaking CH₄ gas on sensor performance and harmful influence, so as to evaluate the health status and life prediction of underwater CH₄ sensor arrays. In the process of detecting CH₄, the accuracy decreases when H₂S is found in the ocean water. In this study, we proposed an explainable sorted-sparse (ESS) transformer model for concentration interval detection under industrial conditions. The time complexity was decreased to O (n log_n) using an explainable sorted-sparse block. Additionally, we proposed the Ocean X generative pre-trained transformer (GPT) model to achieve the online monitoring of the health of the sensors. The ESS transformer model was embedded in the Ocean X GPT model. When the program satisfied the special instructions, it would jump between models, and the online-monitoring question-answering session would be completed. The accuracy of the online monitoring of system health is equal to that of the ESS transformer model. This Ocean-X-generated model can provide a lot of expert information about sensor array failures and electronic noses by text and speech alone. This model had an accuracy of 0.99, which was superior to related models, including transformer encoder (0.98) and convolutional neural networks (CNN) + support vector machine (SVM) (0.97). The Ocean X GPT model for offline question-and-answer tasks had a high mean accuracy (0.99), which was superior to the related models, including long short-term memory–auto encoder (LSTM–AE) (0.96) and GPT decoder (0.98). Full article

The formation of scale in hot springs and geothermal brines can be detected quickly and easily using optical fiber-based scale sensors. This paper describes the development of a portable sensor for the in situ detection of scale in geothermal water. This sensor was used to detect the formation of calcium carbonate and silica scale and to assess the effectiveness of their inhibitors. The performance of the sensor was evaluated using calcium carbonate scale. In laboratory experiments using both the newly developed sensor and a conventional nonportable sensor, the strength of the transmitted signal was found to decrease significantly as the amount of scale increased. It was considered that this sensor can accurately evaluate only scale formation without being affected by turbidity. The scale that was deposited on each material (optical fiber core, glass plate, polyvinyl chloride (PVC), and SUS304) was observed using a shape analysis laser microscope. Based on these observations, we concluded that this sensor could be used to predict the amount of scale deposited in real time. In situ evaluation of the sensor was conducted at a blowout carbonated hot spring on Rishiri Island, which is located off the coast of Hokkaido, Japan. The results obtained from experiments using hot spring water showed a similar sensor response within a comparable time range as those obtained from the laboratory experiments. The results of this study thus demonstrate that this novel portable scale sensor is suitable for use in geothermal power plants and investigating effectiveness of inhibiters under different conditions. Full article

Recently, a technical modification of a Reflectance Anisotropy Spectroscopy (RAS) spectrometer has been proposed to investigate the circular dichroism (CD) of samples instead of the normally studied linear dichroism. CD-RAS measures the anisotropy of the optical properties of a sample under right-handed and left-handed circularly polarized light. Here, we present the application of CD-RAS to measure the circular dichroism of a twisted bilayer of graphene, purposely prepared as a possible substrate for the adsorption of thin molecular layers, in air, in liquid or in a vacuum. This result demonstrates the performance of the apparatus and shows interesting perspectives for the investigation of chiral organic assemblies deposited in solid film. Full article

Ammonia (NH₃) sensing is crucial for environmental safety, necessitating the development of efficient NH₃ sensors. In this study, an efficient NH₃ sensor based on CdS quantum dots (QDs) decorated with ZnO (CdS/ZnO) covering optical fiber was successfully fabricated. The CdS/ZnO was first synthesized by a hydrothermal method, featuring an n-n heterojunction in the composite material. The optimal sensor with 10 wt% CdS QDs exhibits efficient performance, with a response sensitivity of 0.9 × 10⁻³ dB/ppm and R² = 0.9858. Additionally, it demonstrates excellent selectivity and repeatability. Mechanistic insights for the NH₃ sensor were elucidated through X-ray photoelectron spectroscopy, energy-dispersive X-ray spectroscopy, scanning electron microscopy, and transmission electron microscopy. These results confirm that the enhancement in NH₃ sensing performance is attributed to the formation of well-defined n-n heterojunctions. This study contributes to the advancement of gas-sensing technology, particularly in the detection of harmful gases, such as NH₃. Full article

pH regulation in human biofluids is a crucial step for disease diagnosis and health monitoring. Traditional pH sensors are limited by their bulky size in wearable systems, and fragile glass tips require frequent calibration, thus limiting their use in continuous monitoring. Flexible sensors, particularly those utilizing microwires and thread-based substrates, present advantages for small sample analysis, including natural breathability and suitability for bandage or textile integration. This study examines iridium oxide and silver–silver chloride coated on thin gold wires, fabricated using sol–gel and dip-coating processes known for their simplicity. The flexible microwires demonstrated promising pH performance from a study of their pH characteristics, sensitivity, hysteresis, and potential drift. Electrodes tested in microwells allowed for small sample volumes and localized pH measurement in a controlled environment. Additional integration into fabrics for sweat sensing in wearables highlighted their potential for continuous, real-time health monitoring applications. Full article

As a significant biomarker during the apoptosis process, cytochrome c (Cyt c) is considered as a critical component in the inherent apoptotic pathway, but the simple and portable detection still remains challengeable. In this work, a portable and visual sensing platform for Cyt c was developed based upon the fluorescence quenching of graphene quantum dots (GQDs), which could be finished within a few seconds. Herein, the absorption spectrum of Cyt c matched the emission spectrum of GQDs well, which could cause the fluorescence quenching of GQDs via the inner filter effect (IFE) in the range of 1–50 μg/mL with the limit of detection as low as 0.1 μg/mL. Furthermore, the intracellular Cyt c was imaged to observe the apoptosis process of cancer cells induced by staurosporine. To achieve the portable and visual detection of Cyt c, GQDs were deposited on the filter paper to form the solid platform, which displayed a gradual fluorescence quenching when different concentrations of Cyt c were present. Compared to the conventional methods, the proposed assay is low-cost, fast, portable, and visual, which will be useful for the investigation of mitochondrial dysfunction and apoptotic cell death. Full article

Luminescent Ag nanoclusters (Ag NCs) are a promising probe material for sensing and bioimaging applications. However, the intrinsic obstacle of poor water stability and photostability greatly restrict their practical application in biological systems. Herein, we report the intracellular hypochlorite (ClO⁻) detection with amphiphilic copolymer-modified luminescent Ag NCs with good biocompatibility and photostability. The Ag NCs were synthesized by using chemically inert hydrophobic ligands and then modified with an amphiphilic (1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(poly(ethylene glycol))-2000]) (DSPE-PEG-2000) and sodium dodecyl sulfonate (SDS) for phase transfer. It was found that the approach of the removal of organic solvents during the phase transfer has remarkable influences on the properties of the Ag NCs, including their size, luminescence property, and aqueous stability. Furthermore, the silver core of Ag NCs could be oxidatively damaged by ClO⁻, thereby causing photoluminescence (PL) quenching. The ClO⁻-induced PL quenching was specific over the other common reactive oxygen species (ROS) as well as some common interferences. Finally, they have been successfully applied as a fluorescent nanoprobe for detecting exogenous and endogenous ClO⁻ in living cells. Full article

In the field of quality analysis of food and flavoring products, gas chromatography–quadrupole mass spectrometry–ion mobility spectrometry (GC-QMS-IMS) is a powerful technique for the simultaneous detection of volatile organic compounds (VOCs) by both QMS and IMS. GC is an established technique for the separation of complex VOC-rich food products. While subsequent detection by IMS features soft ionization of fragile compounds (e.g., terpenes) with characteristic drift times, MS provides analytes’ m/z values for database substance identification. A limitation of the prominently used static-headspace-based GC-QMS-IMS systems is the substantially higher sensitivity of IMS in comparison to full-scan QMS. The present study describes a new prototypic trapped-headspace (THS)-GC-QMS-IMS setup using mango purees. This approach ultimately allows the combination of soft ionization with m/z values obtained from database-searchable electron ionization (EI) spectra. The new setup features aligned retention times for IMS and MS and sufficient signal intensities for QMS and IMS. The results demonstrate that THS-GC-QMS-IMS allows for the classification of mango purees from different cultivars and that it could be a promising alternative method for authenticity control of food, flavors, and beverages. Full article