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The impact of humidity on the efficiency of gas sensors has become highlighted in the realm of gas detection. Due to the complex relationship between humidity and gas sensor performance, the development of gas sensors has recently focused on minimizing humidity-related interference. This research aims to address humidity-related challenges in zinc oxide (ZnO) gas sensors designed to detect triethylamine. The ZnO nanostructures (NSs) were synthesized using thermal decomposition methods at varying temperatures (380 °C, 480 °C, and 580 °C) and annealing times (3 h, 7 h, 12 h, and 21 h). X-ray diffraction (XRD) confirmed the formation of a wurtzite hexagonal close-packed structure in ZnO NSs. Scanning electron microscopy (SEM) images provided insights into the morphologies of ZnO NSs at different annealing temperatures, while energy dispersive spectroscopy (EDS) demonstrated the elemental distribution. Subsequently, gold (Au) nanoparticles were uniformly sputtered onto ZnO sensors with thickness variations (0.1 nm, 0.6 nm, 1 nm, 5 nm, and 10 nm). XPS was employed to analyse the elemental composition and oxygen vacancies of the synthesized sensing materials. The effectiveness of 0.6 nm-thick Au nanoparticles in mitigating humidity effects was observed in ZnO sensors synthesized at 380 °C. The results indicated that ZnO sensors coated with 0.6 nm-thick Au nanoparticles exhibited highly stable responses to ethanol and triethylamine at different humidity levels from 50 % to 90 %. Notably, these sensors demonstrated promising selectivity towards triethylamine (with a response of 17.57) compared to various gas targets at room temperature. The sensor exhibited rapid response and recovery times of 9.8 s and 4.4 s, respectively, toward triethylamine with excellent stability in variable humid environments. The sensor maintained a consistent response over 24 days, demonstrating good stability at high humidity.

Abstract Respiration stands as a vital process reflecting physiological and pathological human health status. Exhaled breath analysis offers a facile, non-invasive, swift, and cost-effective approach for diagnosing and monitoring diseases by detecting concentration changes of specific biomarkers. In this study, we employed Polyethylene oxide/copper (I) oxide composite nanofibers (PCNFs), synthesized via the electrospinning method as the sensing material to measure ethanol levels (1–200 ppm) in an exhaled breath simulator environment. The integrated contact-separation triboelectric nanogenerator was utilized to power the self-powered PCNFs exhaled breath sensor. The PCNFs-based gas sensor demonstrates promising results with values of 0.9 and 3.2 for detecting 5 ppm and 200 ppm ethanol, respectively, in the presence of interfering gas at 90% relative humidity (RH). Notably, the sensor displayed remarkable ethanol selectivity, with ratios of 10:1 to methanol and 25:1 to acetone. Response and recovery times for 200 ppm ethanol at 90 RH% were rapid, at 2.7 s and 5.8 s, respectively. The PCNFs-based exhaled breath sensor demonstrated consistent and stable performance in practical conditions, showcasing its potential for integration into wearable devices. This self-powered breath sensor enabling continuous monitoring of lung cancer symptoms and facilitating compliance checks with legal alcohol consumption limits.

The utilization of gas sensors has the potential to enhance worker safety, mitigate environmental issues, and enable early diagnosis of chronic diseases. However, traditional sensors designed for such applications are often bulky, expensive, difficult to operate, and require large sample volumes. By employing microfluidic technology to miniaturize gas sensors, we can address these challenges and usher in a new era of gas sensors suitable for point-of-care and point-of-use applications. In this review paper, we systematically categorize microfluidic gas sensors according to their applications in safety, biomedical, and environmental contexts. Furthermore, we delve into the integration of various types of gas sensors, such as optical, chemical, and physical sensors, within microfluidic platforms, highlighting the resultant enhancements in performance within these domains.

Objective Substantial effort has been put into designing DNA-based biosensors, which are commonly used to detect presence of known sequences including the quantification of gene expression. Porous silicon (PSi), as a nanostructured base, has been commonly used in the fabrication of optimally transducing biosensors. Given that the function of any PSi-based biosensor is highly dependent on its nanomorphology, we systematically optimized a PSi biosensor based on reflectometric interference spectroscopy (RIS) detecting the high penetrance breast cancer susceptibility gene, BRCA1. Materials And Methods In this experimental study, PSi pore sizes on the PSi surface were controlled for optimum filling with DNA oligonucleotides and surface roughness was optimized for obtaining higher resolution RIS patterns. In addition, the influence of two different organic electrolyte mixtures on the formation and morphology of the pores, based on various current densities and etching times on doped p-type silicon, were examined. Moreover, we introduce two cleaning processes which can efficiently remove the undesirable outer parasitic layer created during PSi formation. Results of all the optimization steps were observed by field emission scanning electron microscopy (FE-SEM). Results DNA sensing reached its optimum when PSi was formed in a two-step process in the ethanol electrolyte accompanied by removal of the parasitic layer in NaOH solution. These optimal conditions, which result in pore sizes of approximately 20 nm as well as a low surface roughness, provide a considerable RIS shift upon complementary sequence hybridization, suggesting efficient detectability. Conclusion We demonstrate that the optimal conditions identified here makes PSi an attractive solid-phase DNA-based biosensing method and may be used to not only detect full complementary DNA sequences, but it may also be used for detecting point mutations such as single nucleotide substitutions and indels.

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

Room temperature gas sensing behavior of arrayed one-dimensional (1D) nickel nanowires (Ni NWs) are investigated using impedance spectroscopy. Ni nanowires synthesized via electrochemical deposition method based on anodic aluminum oxide (AAO) templates. Their structural characterization verified by scanning electron microscopy (SEM), x-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR) analysis. Impedance spectroscopy as an essential technique utilized to understand the mechanism of gas interaction with the wires through the changes in their electronic behavior. Bode and Nyquist plots with the real and imaginary impedances are plotted versus frequency range of 500 Hz to 2 MHz at different relative humidity values (varying from 30% to 70%) and ethanol vapor concentrations (varying from 2 to 18 ppm). The equivalent circuits are proposed and simulated for impedance responses to both humidity and ethanol vapors. The impedance plots indicate the increase in resistance of the aligned nanowires at low frequencies by the adsorption of water and ethanol molecules.

This paper reports on hydrogen sensing based graphene oxide hybrid with Co-based metal organic frameworks (Co-MOFs@GO) prepared by the hydrothermal process. The texture and morphology of the hybrid were characterized by powder x-ray diffraction, scanning electron microscopy and Brunauer–Emmett–Teller analysis. Porous flower like structures assembled from Co-MOFs and GO flakes with sufficient specific surface area are obtained, which are ideal for gas molecules diffusion and interactions. Sensing performance of Co-MOFs@GO were tested and also improved by sputtering platinum (Pt) as a catalyst. The Pt-sputtered Co-MOFs@GO show outstanding hydrogen resistive-sensing with response and recovery times below 12 s at 15 °C. Also, they show stable, repeatable and selective responses to the target gas which make it suitable for the development of a high performance hydrogen sensor. [ABSTRACT FROM AUTHOR]