Selective Sensor Research Articles

Pressure Difference Measuring System for Clean Rooms

This article presents the development and implementation of a pressure difference measuring system tailored for clean rooms, essential in medical facilities to control airflow and reduce nosocomial infections. The study evaluates various pressure sensors, leading to the selection of intelligent sensors that meet specific performance criteria. Key features and operating principles of the system are outlined, including sensor types, measurement techniques, and system architecture. A detailed comparison of sensors such as BMP180 and BMP280 highlights their suitability based on parameters like resolution, power consumption, and communication interfaces. The system’s structure includes dual pressure sensor units connected to a main control unit, enabling real- time pressure monitoring across different room zones. The sensors, equipped with a microcontroller for initial data processing, relay information to the control unit for further analysis and display. Designed with a calibration feature, the system ensures measurement accuracy by allowing recalibration under identical atmospheric conditions. Operating on low voltage, the system provides safe and reliable performance with applications extending to isolation rooms and environments requiring precise pressure regulation. Integrating the measuring system with ventilation systems significantly mitigates the risk of airborne disease transmission, contributing to the maintenance of sterile environments. The article concludes that this cost-effective, intelligent pressure monitoring solution not only enhances safety in healthcare settings but also supports regulatory compliance and improves overall infection control measures in high-risk areas.

A Selective Electrochemical Sensor for Bisphenol A Detection Based on Cadmium (II) (bromophenyl)porphyrin and Gold Nanoparticles

Bisphenol A (BPA) is a commonly synthetic chemical mainly used in producing plastic items. It is an endocrine-disrupting compound that causes irreversible health and environmental damage. Developing a simple method for BPA effective quantitative monitoring is emergently necessary. Herein, a novel electrochemical sensor for BPA detection based on [(5,10,15,20-tetrakis(p-bromophenyl) porphyrinato] cadmium (II) [(CdTBrPP)] and gold nanoparticle (AuNPs)-modified screen-printed carbon electrode (SPCE) was elaborated. CdTBrPP was synthesized and then characterized with Ultraviolet–Visible Spectroscopy (UV/vis), Infrared Spectroscopy (IR), and Proton Nuclear Magnetic Resonance Spectroscopy (1H NMR) to confirm its successful synthesis. After drop-coating AuNPs and CdTBrPP on the SPCE, the sensor performance was evaluated using square wave voltammetry (SWV), a linear response in a concentration range from 10−11 M to 10−2 M, with a low detection limit (LOD) of 9.5 pM. The CdTBrPP/AuNPs/SPCE sensor demonstrates a high selectivity and reproducibility, making it a promising candidate for developing a low-cost water-monitoring system for detecting BPA. Additionally, the proposed sensor effectively detected BPA in both tap and mineral water samples.

Non-enzymatic Electrochemical Sensor Behaviors of Polyaniline: Silicene Nanocomposite- A Study on Sensitive and Selective Sensor Design against Glucose

Abstract This study represents a non-enzymatic electrochemical sensor based on a Polyaniline: Silicene nanocomposite for the detection of glucose. A simple, clean and a low-cost sonication technique was used to prepare silicene nanosheets. XRD, FFT, SAED, HRTEM and FT-IR tecniques were used for characterization and CV for the detection of glucose. Current-voltage measurements were taken at various scanning rates (10-100 mV/s). The active surface areas of PANI and PANI: Silicene nanocomposite based sensors were determined as 0.122 cm2 and 0.179 cm2, respectively. The nanocomposite material presented large peak currents, indicating that the nanocomposite elicited enhanced electrochemical activity with the presence of silicene for glucose detection in the concentration range of 0.75 – 12 mM. At a scan rate of 50 mV/s, PANI-based sensor exhibited a sensitivity of 6.51 μAmM−1 cm−2 with detection limit of 5.52 μM, while the PANI: Silicene nanocomposite-based sensor exhibited a sensitivity of 20.93 μAmM−1 cm−2 with 0.43 μM detection limit. The selectivity of the sensors to measure glucose was also explored by characterizing their electrochemical performances in the presence of fructose and lactose. Due to these enhanced electrochemical performance, PANI: Silicene nanocomposite could be a promising biosensor material for glucose analysis for biomedical applications.

Highly Sensitive and Selective SnO2-Gr Sensor Photoactivated for Detection of Low NO2 Concentrations at Room Temperature

Chemical nanosensors based on nanoparticles of tin dioxide and graphene-decorated tin dioxide were developed and characterized to detect low NO2 concentrations. Sensitive layers were prepared by the drop casting method. SEM/EDX analyses have been used to investigate the surface morphology and the elemental composition of the sensors. Photoactivation of the sensors allowed for detecting ultra-low NO2 concentrations (100 ppb) at room temperature. The sensors showed very good sensitivity and selectivity to NO2 with low cross-responses to the other pollutant gases tested (CO and CH4). The effect of humidity and the presence of graphene on sensor response were studied. Comparative studies revealed that graphene incorporation improved sensor performance. Detections in complex atmosphere (CO + NO2 or CH4 + NO2, in humid air) confirmed the high selectivity of the graphene sensor in near-real conditions. Thus, the responses were of 600%, 657% and 540% to NO2 (0.5 ppm), NO2 (0.5 ppm) + CO (5 ppm) and NO2 (0.5 ppm) + CH4 (10 ppm), respectively. In addition, the detection mechanisms were discussed and the possible redox equations that can change the sensor conductance were also considered.

Wearable Resistive-Type Stretchable Strain Sensors: Materials and Applications.

The rapid advancement of wearable electronics over recent decades has led to the development of stretchable strain sensors, which are essential for accurately detecting and monitoring mechanical deformations. These sensors have widespread applications, including movement detection, structural health monitoring, and human-machine interfaces. Resistive-type sensors have gained significant attention due to their simple design, ease of fabrication, and adaptability to different materials. Their performance, evaluated by metrics like stretchability and sensitivity, is influenced by the choice of strain-sensitive materials. This review offers a comprehensive comparison and evaluation of different materials used in resistive strain sensors, including metal and semiconductor films, low-dimensional materials, intrinsically conductive polymers, and gels. The review also highlights the latest applications of resistive strain sensors in motion detection, healthcare monitoring, and human-machine interfaces by examining device physics and material characteristics. This comparative analysis aims to support the selection, application, and development of resistive strain sensors tailored to specific applications.

Health Monitoring Technology for Hydraulic Engineering Gates Based on Multi-Sensor Data Fusion

An essential part of the hydraulic engineering systems, hydraulic gates regulate water flow in dams and other structures. To avoid structural problems, they must ensured to be consistent. Multi-sensor data fusion has become a key tool for health monitoring with advances in machine learning (ML) and sensor technologies. This study aims to provide a novel multi-sensor data fusion health monitoring system for hydraulic engineering gates. To provide more effective and precise real-time monitoring of hydraulic engineering gates, a unique Dynamic Satin Bowerbird search-driven Bidirectional Long Short-Term Memory (DSB-BiLSTM) model were proposed. The hydraulic monitoring dataset was collected from Kaggle website, comprising information and some attributes obtained from hydraulic engineering gates. To improve data quality, noise reduction, and data normalization are used. Time-series analysis techniques extract important information such as vibration patterns and pressure variations. The DSB-BiLSTM model leverages bidirectional LSTM to progress time-dependent data, and the Satin Bowerbird search optimizes sensor selection. The method shows better accuracy and efficiency in identifying potential faults compared to traditional models. When compared to four attributes such as pump, cooling, valve and accumulator with the metrics outcomes of 0.9901, 0.9925, 0.9950, and 0.9890 in accuracy, 0.9930, 0.9960, 0.9902, and 0.9889 in precision, 0.9920, 0.9960, 0.9911, and 0.9890 in recall, and 0.9915, 0.9955, 0.9905, and 0.9889 in F1-score, the DSB-BiLSTM model performs better than all other approaches that were examined. This suggests better overall hydraulic engineering gate health monitoring performance. The proposed DSB-BiLSTM model is a show potential solution for real-time health monitoring of hydraulic gates, provided that it enhances accuracy and reduces computational complexity.

Antenna effect on Zn(II) porphyrin-based molecular ensembles for the detection of 2,4-dinitrophenol through energy and electron transfer process.

Twomodular systems were synthesizedcomposed of triphenylamine (ZnTPAP) and pyrene (ZnPyP) covalently linked at meso position of the Zn(II) porphyrins. Both compounds behaved as energy transfer antenna and orthogonal units to enhance the electron donating ability of Zn(II) porphyrins. Detailed photophysical and aggregation studies reveal that an appreciable electronic interaction exists between peripheral units to the porphyrin π-system so that they behave like strong donor materials. The electrochemical and computational studies demonstrate delocalization of the frontier highest occupied molecular orbital (-5.08eV) over the triphenylamine entities (ZnTPAP) in addition to the porphyrin macrocycle. Fluorescence experiments withZnTPAP and ZnPyP in the presence ofdifferent nitro analytes at various concentrations show turn-off fluorescence behaviour and exhibit superior selectivity towards 2,4-dinitrophenol (DNP) with limit of detection (LOD) of ~ 2.3 and 9.2ppm for ZnTPAP and ZnPyP. Photoinduced electron transfer process is involvedin the static and dynamicfluorescence quenching process. A Stern-Volmer quenching association constant (Ksv) determination revealed that ZnTPAP is more sensitive than the ZnPyP. This is attributed to thestrong donating behaviour of TPA unitscaused by intermolecular interaction through metal center and strong π-π interactions with nitro analytes. The present study provides new insights into the ability to tune the affinity and selectivity of porphyrin-based sensors utilising electronic factors associated with the central Zn(II) ion. Furthermore, a smartphone-interfaced portable fluorimetric method by recognising colour variations in RGB and the luminance (L) values facilitate sensitive and real-time sensing at low concentration levels will have a significant impact on development of a new class of chemosensors.

Facile formation of nanoporous reduced graphene oxide via epoxy-based negative photoresist laser irradiation for highly sensitive and selective gas detection

This study aims to advance gas sensor technology, particularly focusing on chemiresistive gas sensors known for their simplicity and cost-effectiveness. SU-8, an epoxy-based negative photoresist characterized by the presence of eight epoxy groups, is employed as a precursor to laser-induced graphene. Under CO2 laser irradiation, SU-8 rapidly dissociates, forming a porous graphite-like surface and transforming into reduced graphene oxide (rGO). This rGO exhibits exceptional sensitivity, detecting 20 ppb of NO2 at room temperature (25℃), representing a significant achievement for singular materials. Furthermore, the study demonstrates the scalability of rGO not only as a sensing material but also as a framework through a straightforward deposition process. The deposition of SnO2 on rGO shows remarkable selectivity and sensitivity toward NO2 gas, achieving an ultra-low limit of detection of 26.2 ppt. Subsequent Pd deposition enhances the gas sensor's selectivity for hydrogen gas, highlighting its scalability as a framework for diverse gas sensors beyond NO2. In summary, this study showcases the capability of carbonized SU-8 to detect low-concentration NO2 using a singular material. It underscores the material's potential as a versatile framework for gas sensors, demonstrating its adaptability across various gas sensing applications.

Computational Investigation of Pristine, Al-, and Ga-Doped Zn12O12 nanoclusters as Detection Platforms for Methadone in gas and solvent phases

Electrochemical sensors are emerging as promising tools for point-of-care diagnostic medical devices, benefiting from advancements in nanomaterials. These nanomaterials enable the development of smaller, more sensitive, and selective sensors while reducing fabrication and maintenance costs. This work presents a comprehensive theoretical investigation of the potential application of pristine, Ga- and Al-doped Zn12O12 nanoclusters for detecting methadone, a critical analyte in various medical and law enforcement applications. Employing density functional theory (DFT) calculations at the B3LYP-D level with the 6-311G (d, p) basis set, we have elucidated the interactions between these nanoclusters and methadone. The results reveal that methadone exhibits intense adsorption energies of -41.02, -39.79, and -59.77 kcal/mol on the pristine Zn12O12, GaZn11O12, and AlZn11O12 nanoclusters, respectively, in their most stable configurations. The doped nanoclusters, GaZn11O12 and AlZn11O12, displayed significant gap energies (Eg) changes upon methadone adsorption, indicating enhanced sensitivity towards this analyte. The UV-Vis spectroscopic analysis showed that methadone adsorption on the GaZn11O12 and AlZn11O12 nanoclusters led to distinct spectral shifts and oscillator strength variations compared to the Zn12O12 nanocluster. The transition theory calculations highlighted the GaZn11O12 nanocluster's short recovery time of 0.44 seconds, a crucial attribute for practical applications. Solvent effect studies demonstrated the stability of the methadone/GaZn11O12 complex in water and revealed its heightened polarization, as evidenced by the increased dipole moment. These findings suggest that the GaZn11O12 nanocluster is a promising candidate for detecting methadone in gas and liquid phases, with favorable attributes such as high sensitivity, rapid reversibility, and stability in gas and aqueous environments. Thus, this nanocluster can be used in sensor devices.

Construction and application of an electrochemical sensor based on MIL-101-NH2(Fe)-derived Fe-C porous materials doped with reduced graphene oxide for baicalin detection

Baicalin (Bn), a natural flavonoid compound, possesses high pharmacological effects. Here, an electrochemical sensor has been proposed based on an MIL-101-NH2(Fe)-derived Fe porous carbon composite (Fe-C) doped with reduced graphene oxide (rGO) for detecting Bn, designated as Fe-C/rGO. Fabricated through a straightforward physical doping process, Fe-C/rGO exhibits remarkable electrochemical activity. This superiority stems primarily from two key factors. Firstly, the porous structure of Fe-C efficiently concentrates Bn, facilitating its capture and recognition. Secondly, graphene oxide, serving as a substrate for anchoring metal–organic frameworks (MOFs), boosts the electrochemical performance of the composite due to its distinctive two-dimensional structure, abundant active sites, and unparalleled stability. The synergistic interaction between Fe-C and rGO maximizes their respective advantages, leading to a significant enhancement in the sensitivity and selectivity of the electrochemical sensor. Boasting a low detection limit of 7.5 nM and a broad detection range spanning from 30 to 180 nM, this sensor holds immense potential in clinical applications and drug monitoring, offering a reliable and efficient method for Bn detection.

Competitive Binding Strategy for Reliable Signal-off Surface Enhanced Raman Scattering Sensing in Protecting Apples from Patulin without External Interference

Patulin is a toxin that can be found in damaged or moldy fruits, especially apples. Very high detection sensitivity can be achieved using the SERS (Surface Enhanced Raman Scattering) technique, which provides information about molecular vibrations. However, unexpected desorption of target toxins from the surface of the SERS substrate and interference from other substances pose a major challenge. Here we investigate a competitive binding strategy for reliable SERS analysis of PAT. Core-Raman molecule-shell (CMS) structures and programmable, specific DNA interactions are utilized to regulate Raman signal intensity without affecting the embedded Raman molecules. Specfically, aptamer-functionalized CMS structures are combined with metal-organic scaffold nanoparticles that possess complementary DNA sequences. In the presence of PAT, binding of the aptamer to the toxin leads to degradation of the hybrid nano assembly, which can be measured by a change in the SERS signal. This SERS strategy enables turn-off sensing in apple juice over a wide range (10pg/mL to 1μg/mL), with a detection limit as low as 0.02ng/mL. Analysis of real samples gives results consistent with high-performance liquid chromatography (HPLC) test. The excellent selectivity and sensitivity of the SERS sensor demonstrate its potential for a wide range of SERS sensor applications.

Highly responsive and selective gas sensors utilizing ZIF-8/porous rGO/ZnO composites

Highly responsive and selective gas sensors utilizing ZIF-8/porous rGO/ZnO composites

Real-time Neurochemical Sensing of Hydrogen Peroxide Production in Brain Tissue using Advanced Nanostructured Au Microelectrodes Functionalized with Ruthenium Purple Film

Real-time monitoring of H2O2 is essential for understanding its role in neurological physio(path)ology. In this study, we developed an advanced electrochemical sensor utilizing nanostructured gold wire microelectrodes functionalized with a Ruthenium Purple (RP) film, a polynuclear transition metal hexacyanoferrate analog of the prototypical Prussian blue (PB). The RP film exhibits enhanced stability in neutral buffer solutions and reduced interference from biologically relevant cations such as Na+, Mg2+, and Ca2+. By integrating gold nanoparticles onto a nanoporous gold surface, we significantly increased the electroactive surface area of the microwire (ρ=26.1 ± 10.2). The electrodeposition of a thin RP film (4.23 ± 1.2 nm) resulted in a highly selective H2O2 sensor, operating at an optimal potential of -0.05 V vs. Ag/AgCl, with a linear detection range of 0.5-500 µM, sensitivity of 1.18 ± 0.37 µA µM-1 cm-2, and a low limit of detection (LOD) of 66.6 ± 34.9 nM. Adding a Nafion® layer enhanced the sensor's operational stability, maintaining optimal performance over three hours under physiological conditions of pH and ion concentration. We validated the sensor's capability to monitor transient changes in H2O2 concentration in brain tissue by assessing its response to exogenously applied H2O2. Furthermore, we demonstrated that glutamate receptor activation in hippocampal slices induces a rapid and transient increase in extracellular H2O2 levels, underscoring the sensor's potential for studying oxidative stress in neurobiological contexts.

Insights into Selective Sensitivity of In2O3-CuO Heterojunction Nanocrystals to CH4 over CO and H2: Experiments and First-Principles Calculations.

Metal oxide semiconductor gas sensors have demonstrated exceptional potential in gas detection due to their high sensitivity, rapid response time, and impressive selectivity for identifying various sorts of gases. However, selectively distinguishing CH4 from those of CO and H2 remains a significant challenge. This difficulty primarily stems from the weakly reducing nature of CH4, which results in a low adsorption response and makes it prone to interference from stronger reducing gases in the surroundings. Herein, we synthesized In2O3-xCuO nanocomposites using a hydrothermal method to explore their gas sensing properties toward CH4, CO, and H2. Characterization tests confirmed the successful preparation of In2O3-xCuO nanocomposites with different In:Cu molar ratios and the formation of a p-n heterojunction. The gas sensing test results indicated that the In2O3-2.1CuO nanocomposites calcined at 500 °C and measured at 350 °C displayed a p-type response for CH4 and an n-type response for CO and H2, allowing for accurate differentiation of CH4 from CO and H2. Moreover, the In2O3-2.1CuO sensor also showed excellent stability and reproducibility across all three gases. First-principles calculations revealed distinct changes in the electronic structure of the In2O3-CuO heterojunction upon adsorption of CH4, CO, and H2, a finding that aligns with empirical evidence. The gas selectivity mechanism was effectively explained by variations in the energy band gap, driven by electrical behavior during the adsorption process. This work suggests a promising approach for developing selective gas sensors capable of detecting weakly reducing gases.

The Effective Sorting Technologies for Reducing Aflatoxins in Nuts and Dried Figs in Turkey

Background: RASFF notifications serve to determine the hazards responsible for food and feed. In case of determining risks to human health, the information provided to member countries via the rapid alarm system at the same time warned us to take the necessary measures. Objectives: In this research, the RASFF portal alerts over the last three years related to aflatoxins in hazelnut, fig, and peanut products were examined. The impact of image processing technologies on lowering the danger of aflatoxins in shelled hazelnuts and dried figs was also investigated, as well as Critical Control Points (CCPs) on aflatoxin hazard. Methods: The RASFF database was used in the RASFF Window portal and analyzed for aflatoxin alerts. ISO 22000:2018 was used for hazard and risk analysis for raw hazelnut, peanut, and fig products. Aflatoxin analyses were performed according to the AOAC 2000/991.31 method. Prior to and after hazelnut sorting methods, levels of aflatoxin were measured. Besides, aflatoxin contamination in peanuts harvesting in 2023 years from three local producers in Turkey was studied. Results: The number of RASFF notifications for hazelnuts, peanuts/groundnuts, dried figs, and their products for the period of 03/01/2020 to 01/06/2023 were 84, 283 and 173, respectively. As a result of HACCP implementation, especially for aflatoxin hazard management, optical-laser-manual sorting and aflatoxin detection using UV light stages are accepted as CCPs. When nuts were sorted using optical and laser systems were detected decreasing total aflatoxin levels. The mean value of Aflatoxin B1(AFB1) and total aflatoxins were reduced from 7.80±1.08 and 13.56±1.06 to 3.63±0.39 and 7.21±0.71, respectively. 79.16% of all sorted samples were found to comply with legal limits. Investigated peanut samples for aflatoxin B1 contents were found between 5.63 and 27.75 µg kg-1 in 19.5%. Conclusion: The alerts based on aflatoxin contamination above legal limits have been carried on for nuts and dried figs. The physical sorting methods using optical selection and high-resolution laser sensor systems aflatoxin-contaminated nuts from healthy nuts applied for in-shell Turkish nut sorting were able to assess the quality of the batch studied, and the systems were assigned significantly effective to reduce aflatoxin contents. Food business operators in Turkey, which is among the countries exporting agricultural and food products to the European Union (EU), have tended to prefer the most advanced technologies. Efficacies of reduction of aflatoxin by different physical and other (such as imaging, X-ray and acoustic, audio signals and hyperspectral images of moldy natural nuts etc.) methods will be developed in the near future.

A technical survey on practical applications and guidelines for IoT sensors in precision agriculture and viticulture

Climate change pose significant challenges to modern agriculture management systems, threatening food production and security. Therefore, tackling its effects has never been so imperative to attain sustainable food access and nutrition worldwide. In the case of viticulture, besides jeopardizing grape production, climate change has severe impact in quality, which has becoming more challenging to manage, due to the increasingly frequent fungal contamination, with consequences for relevant quality parameters such as the aromatic profiles of grapes and wines and their phenolic compounds. This has been leading to a reconfiguration of the wine industry geostrategic landscape and economy dynamics, particularly in Southern Europe. To address these and other emerging challenges, in-field deployable proximity-based precision technologies have been enabling real-time monitoring of crops ecosystems, including climate, soil and plants, by performing relevant data gathering and storage, paving the way for advanced decision support under the Internet of Things (IoT) paradigm. This paper explores the integration of agronomic and technological knowledge, emphasizing the proper selection of IoT-capable sensors for viticulture, while considering more general ones from agriculture to fill gaps when specialized options are unavailable. Moreover, advisable practices for sensor installation are provided, according to respective types, data acquisition capabilities and applicability.

Highly robust and efficient metal-free water cup solid–liquid triboelectric nanogenerator for water wave energy harvesting and ethanol detection

Recently, low-frequency mechanical energy harvesters based on solid–liquid contact electrification have garnered widespread attention for their unique advantages in wear resistance, high charge transfer efficiency, and novel insights into electron–ion interactions at the solid–liquid interface, particularly in material identification. Hence, we designed an robust and efficient water cup triboelectric nanogenerator (WC-TENG) that only uses ordinary drinking water and plastic water cups as primary materials, achieving high-efficiency power output while eliminating the need for metal electrodes and effectively addressing the issue of corrosion in generator components. Experimental results indicate that, at an operating frequency of 2 Hz, the WC-TENG generates an open-circuit voltage (Voc) of 249.71 V, a short-circuit current (Isc) of 4.21 µA, and a transferred charge (Qsc) of 188.85 nC. The WC-TENG is capable of harvesting water wave energy with low frequency and low vibration amplitude. Furthermore, the introduction of ethanol disrupts the potential balance at the solid–liquid interface by impeding electron transfer and reducing the WC-TENG’s electrical output, but as the ethanol volatilizes, the device gradually returns to its original potential state, demonstrating its potential as a selective ethanol sensor. This design not only advances the development of corrosion-resistant, high-performance energy harvesters but also opens up new possibilities for low-cost, sustainable, and environmentally adaptable sensing technologies.

Flexible 3D nanofiber-based SERS biosensor for detection of miRNA-223-3p in early Laryngeal Cancer diagnosis

MicroRNAs (miRNAs) are small non-coding RNAs (18–22 nucleotides) that regulate gene expression and are associated with various diseases, including Laryngeal Cancer (LCa), which has a high mortality rate due to late diagnosis. Traditional methods for miRNA detection present several drawbacks (time-consuming steps, high cost and high false positive rate). Early-stage diagnosis and selective detection of miRNAs remain challenging.This study proposes a 3D flexible biosensor that combines nanofibers (NFs), gold nanoparticles (AuNPs), and an inverse molecular sentinel (iMS) for enzyme-free, SERS-based detection of miRNA-223-3p, evaluated as a potential LCa biomarker. The electrospun flexible nanofibers decorated with AuNPs enhance Raman signal. Selective detection of miRNA-223-3p is achieved by immobilizing an iMS-DNA probe labeled with a Raman reporter (Cyanine 3) on the AuNPs. The iMS distinctive stem-and-loop structure undergoes a conformational change upon interaction with the miRNA-223-3p, producing an “on to off” SERS signal. The proposed sensor demonstrated a linear detection range from 10 to 250 fM, with a limit of detection (LOD) of 19.50 ± 0.05 fM. The sensor selectivity was confirmed by analyzing the SERS signal behaviour in the presence of both Non-complementary miRNA and miRNA with three mismatched base pairs. This easily fabricable sensor requires no amplification and offers key advantages, including sensitivity, flexibility, and cost-effectiveness.

Gas Adsorption on the Co2Te3 Monolayer: Density Functional Theory Study.

We report a numerical investigation of the chemical adsorption of acetone and carbon dioxide gases by a cobalt telluride (III) 2D layer. Calculations were performed using first principles calculations within the density functional theory to evaluate the adsorbed gas impact on the material's conductivity. The adsorption of carbon dioxide was found to significantly affect the Co2Te3 monolayer electronic structure and its electrical conductivity, which is not observed in the case of acetone. This letter demonstrates that the calculated bond formation energy for carbon dioxide is approximately 2 times higher than that for the acetone. It proved that the quasi-2D cobalt telluride (III) could be introduced as a selective electrochemical sensor for carbon dioxide in quick medical diagnoses and other technological applications.

Covalent Organic Framework as Selective Fluorescence Sensors for Cancer Inducing Volatile Organic Compounds.

Certain volatile organic compounds (VOCs), such as formaldehyde, acetone, and ethanol, are overexpressed in some terminal diseases like cancer, diabetes, Alzheimer's, etc. Therefore, high-precision detection and quantification of VOCs is imperative for early diagnosis of such detrimental diseases. Non-invasive and accurate fluorescence-based detection of such analytes has garnered widespread attention. The inherent luminescent properties of covalent organic frameworks (COFs), resulting from their extensive π-conjugation, have made them suitable for sensing applications. Structural tunability and strong covalent linkers facilitate sensing by COFs. Appropriate choices of linker and skeletal units of the COF can help detect various biologically important analytes selectively. The most common linkers used in this regard is the imine linker, which can undergo excellent hydrogen bonding with different protic VOCs e. g., ethanol, methanol, etc. Besides imine detection, hydrogen bonding also proved useful for detection of aldehydes. Suitable combinations of donors and acceptors enable the COFs to have specific charge transfer interactions with many electron-rich and electron-poor VOCs. In this review, we have highlighted the syntheses of selective COFs incorporating linkers designed for sensing cancer-inducing VOCs. A detailed discussion of the interaction mechanisms between COFs and these VOCs is provided, along with examples from recent literature in this field.