An ultra-sensitive ammonia sensor based on a quartz crystal microbalance using nanofibers overlaid with carboxylic group-functionalized MWCNTs.

Detecting ammonia at low concentrations is crucial in various fields, including environmental monitoring, industrial processes, and healthcare. This study explores the development and performance of an ultra-sensitive ammonia sensor using carboxylic group-functionalized multi-walled carbon nanotubes (f-MWCNTs) overlaid on polyvinyl acetate nanofibers coated on a quartz crystal microbalance (QCM). The sensor demonstrates high responsiveness, with a frequency shift response of over 120 Hz when exposed to 1.5 ppm ammonia, a sensitivity of 23.3 Hz ppm-1 over a concentration range of 1.5-7.5 ppm, and a detection limit of 50 ppb. Additionally, the sensor exhibits a rapid response time of only 14 s, excellent selectivity against other gases, such as acetic acid, formaldehyde, methanol, ethanol, propanol, benzene, toluene, and xylene, and good stability in daily use. These characteristics make the sensor a promising tool for real-time ammonia detection in diverse applications.

Formaldehyde gas sensors based on a quartz crystal microbalance modified with aniline-doped polyvinyl acetate nanofibers.

Real-time detection of formaldehyde in the atmosphere remains challenging. The available gaseous formaldehyde sensing methods offer limited sensitivity, selectivity, and robustness. We modified a quartz crystal microbalance (QCM) system for selective detection of formaldehyde in air. The QCM surface was functionalized with polyvinyl acetate (PVAc) nanofibers and doped with 2, 4, and 6 wt% aniline to improve the selectivity and sensitivity of the sensor. The chemical content and morphological structure of PVAc nanofibers doped with aniline were confirmed by Fourier-transform infrared (FTIR) spectroscopy, energy-dispersive X-ray (EDX) spectroscopy, and scanning electron microscopy (SEM). The results showed that the modified QCM sensor had a sensitivity of 0.056 Hz ppm-1 with a response and recovery times of 200 s and 90 s, respectively. It gave limits of detection (LOD) and limit of quantification (LOQ) of 28 ppm and 96 ppm, respectively. Moreover, the modified QCM was selective towards formaldehyde compared to the other gases. The current workplace exposure limit (WEL) for formaldehyde is 2 ppm, with a time-weighted average over eight hours. Future work will focus on improving the reported QCM sensor to meet the required LOD for formaldehyde detection in the environment and industrial sites.

Polyacrylonitrile Nanofiber-Based Quartz Crystal Microbalance for Sensitive Detection of Safrole.

Safrole is the main precursor for producing the amphetamine-type stimulant (ATS) drug, N-methyl-3,4-methylenedioxyamphetamine (MDMA), also known as ecstasy. We devise a polyacrylonitrile (PAN) nanofiber-based quartz crystal microbalance (QCM) for detecting safrole. The PAN nanofibers were fabricated by direct electrospinning to modify the QCM chips. The PAN nanofiber on the QCM chips has a diameter of 240 ± 10 nm. The sensing of safrole by QCM modified with PAN nanofiber shows good reversibility and an apparent sensitivity of 4.6 Hz·L/mg. The proposed method is simple, inexpensive, and convenient for detecting safrole, and can be an alternative to conventional instrumental analytical methods for general volatile compounds.

Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition.

The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach has been widely used to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, instead of using it alone, clinicians often prefer to diagnose the coronavirus disease 2019 (COVID-19) by utilizing a combination of clinical signs and symptoms, laboratory test, imaging measurement (e.g., chest computed tomography scan), and multivariable clinical prediction models, including the electronic nose. Here, we report on the development and use of a low cost, noninvasive method to rapidly sniff out COVID-19 based on a portable electronic nose (GeNose C19) integrating an array of metal oxide semiconductor gas sensors, optimized feature extraction, and machine learning models. This approach was evaluated in profiling tests involving a total of 615 breath samples composed of 333 positive and 282 negative samples. The samples were obtained from 43 positive and 40 negative COVID-19 patients, respectively, and confirmed with RT-qPCR at two hospitals located in the Special Region of Yogyakarta, Indonesia. Four different machine learning algorithms (i.e., linear discriminant analysis, support vector machine, stacked multilayer perceptron, and deep neural network) were utilized to identify the top-performing pattern recognition methods and to obtain a high system detection accuracy (88-95%), sensitivity (86-94%), and specificity (88-95%) levels from the testing datasets. Our results suggest that GeNose C19 can be considered a highly potential breathalyzer for fast COVID-19 screening.

A highly sensitive safrole sensor based on polyvinyl acetate (PVAc) nanofiber-coated QCM.

A novel, highly sensitive and selective safrole sensor has been developed using quartz crystal microbalance (QCM) coated with polyvinyl acetate (PVAc) nanofibers. The nanofibers were collected on the QCM sensing surface using an electrospinning method with an average diameter ranging from 612 nm to 698 nm and relatively high Q-factors (rigid coating). Scanning electron microscopy (SEM) and atomic force microscopy (AFM) were used to analyze the PVAc nanofiber surface morphology, confirming its high surface area and roughness, which are beneficial in improving the sensor sensitivity compared to its thin-film counterpart. The as-spun PVAc nanofiber sensor could demonstrate a safrole limit of detection (LOD) of down to 0.7 ppm with a response time of 171 s and a sensitivity of 1.866 Hz/ppm. It also showed good reproducibility, rapid response time, and excellent recovery. Moreover, cross-interference of the QCM sensor response to non-target gases was investigated, yielding very low cross-sensitivity and high selectivity of the safrole sensor. Owing to its high robustness and low fabrication cost, this proposed sensing device is expected to be a promising alternative to classical instrumental analytical methods for monitoring safrole-based drug precursors.

Solvent vapor treatment improves mechanical strength of electrospun polyvinyl alcohol nanofibers.

Electrospun nanofibers of polyvinyl alcohol (PVA) have poor mechanical strength. As such their use has often been avoided, particularly in applications that require high mechanical properties. The objective of this study is to increase the mechanical properties of PVA nanofiber mats via physical crosslinking with solvent vapor treatment using organic solvents, dimethyl sulfoxide (DMSO), N, N-dimethyl formamide (DMF), and methanol. The effect of solvent vapor treatment on PVA nanofibers is clearly observed by scanning electron microscope (SEM). The tensile strength increased by over 60%, 90%, and 115% after solvent vapor treatment with DMF at a temperature of 40 °C for 2 h, 4 h, and 8 h, respectively, compared to untreated PVA nanofibers. In addition, Young's modulus of PVA nanofiber mats also increased after DMF treatment. As a comparison, DMSO and methanol were also used in solvent vapor treatment because of differences in their polymer-solvent affinity. Results showed that the highest improvement (100%) in mechanical strength was obtained using DMF. This study shows that solvent vapor treatment offers a simple and inexpensive method that provides excellent results and is a promising alternative treatment for use in increasing the mechanical properties of electrospun nanofibers.