Anti-biofouling NH3 gas sensor based on reentrant thorny ZnO/graphene hybrid nanowalls

Si, O-Codoped Carbonized Polymer Dots with High Chemiresistive Gas Sensing Performance at Room Temperature

A new type of carbonized polymer dot was prepared by the one-step hydrothermal method of triethoxylsilane (TEOS) and citric acid (CA). The sensor made from carbonized polymer dots (CPDs) showed superior gas sensing performance toward ammonia at room temperature. The Si, O-codoped CPDs exhibited superior ammonia sensing performance at room temperature, including a low practical limit of detection (pLOD) of 1 ppm (Ra/Rg: 1.10, 1 ppm), short response/recovery time (30/36 s, 1 ppm), high humidity resistance (less than 5% undulation when changing relative humidity to 80 from 30%), high stability (less than 5% initial response undulation after 120 days), reliable repeatability, and high selectivity against other interferential gases. The gas sensing mechanism was investigated through control experiments and in situ FTIR, indicating that Si, O-codoping essentially improves the electron transfer capability of CPDs and synergistically dominates the superior ammonia sensing properties of the CPDs. This work presents a facile strategy for constructing novel high-performance, single-component carbonized polymer dots for gas sensing.

Detection of methyltransferase activity and inhibitor screening based on rGO-mediated silver enhancement signal amplification strategy

DNA methylation refers to the chemical modification process of obtaining a methyl group by the covalent bonding of a specific base in DNA sequence with S-adenosyl methionine (SAM) as a methyl donor under the catalysis of methyltransferase (MTase), which is related to the occurrence of multiple diseases. Therefore, the detection of MTase activity is of great significance for disease diagnosis and drug screening. Because reduced graphene oxide (rGO) has a unique planar structure and remarkable catalytic performance, it is not clear whether rGO can rapidly catalyze silver deposition as an effective way of signal amplification. However, in this study, we were pleasantly surprised to find that using H₂O₂ as a reducing agent, rGO can rapidly catalyze silver deposition, and its catalytic efficiency of silver deposition is significantly better than that of GO. Therefore, based on further verifying the mechanism of catalytic properties of rGO, we constructed a novel electrochemical biosensor (rGO/silver biosensor) for the detection of dam MTase activity, which has high selectivity and sensitivity to MTase in the range of 0.1 U/mL to 10.0 U/mL, and the detection limit is as low as 0.07 U/mL. Besides, this study also used Gentamicin and 5-Fluorouracil as inhibitor models, confirming that the biosensor has a good application prospect in the high-throughput screening of dam MTase inhibitors.

Deep-learning-based gas identification by time-variant illumination of a single micro-LED-embedded gas sensor

Electronic nose (e-nose) technology for selectively identifying a target gas through chemoresistive sensors has gained much attention for various applications, such as smart factory and personal health monitoring. To overcome the cross-reactivity problem of chemoresistive sensors to various gas species, herein, we propose a novel sensing strategy based on a single micro-LED (μLED)-embedded photoactivated (μLP) gas sensor, utilizing the time-variant illumination for identifying the species and concentrations of various target gases. A fast-changing pseudorandom voltage input is applied to the μLED to generate forced transient sensor responses. A deep neural network is employed to analyze the obtained complex transient signals for gas detection and concentration estimation. The proposed sensor system achieves high classification (~96.99%) and quantification (mean absolute percentage error ~ 31.99%) accuracies for various toxic gases (methanol, ethanol, acetone, and nitrogen dioxide) with a single gas sensor consuming 0.53 mW. The proposed method may significantly improve the efficiency of e-nose technology in terms of cost, space, and power consumption.

Breath VOC analysis and machine learning approaches for disease screening: a review

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

Direct fabrication of high-quality vertical graphene nanowalls on arbitrary substrates without catalysts for tidal power generation

The non-catalytic preparation of high-quality vertical graphene nanowalls (VGN) and graphene-based high output power hydrovoltaic effect power generation devices has always been difficult to achieve. In this work, we successfully prepared VGN with defect density, few layers and submicron domain size on a variety of substrates without catalysts through reasonable adjustment of growth conditions by the hot-wire chemical vapor deposition (HWCVD) method. The Raman test of the VGN prepared under optimal conditions showed that its I_D/I_G value was less than 1, and I_2D/I_G was more than 2.8. The deposition pressure was a key factor affecting the crystallization quality of the VGN. A suitable deposition pressure of 500 Pa could screen the active carbon clusters involved in the growth of nanowalls. The VGN prepared had excellent electrical properties and output of dropping-ion-droplet nano-power generation devices. Because of the larger crystal domain area and smaller contact angle of the VGN, the maximum output power exhibited at 100 Pa was 15.7 μW, which exceeded the value produced by other reported hydrovoltaic energy harvesting devices. All of them confirmed that VGN with improved quality had high application prospects in nano-energy devices.

Highly Sensitive, Selective and Low-Power Consumption Metalloporphyrin−Based Junctions for Nitrogen Monoxide Detection with Excellent Recovery

Research interest in chemical gas detection has been directed towards developing highly selective bio-inspired and eco-friendly materials that allow the integration of sensors in daily human life, such as the...

Synthesis of ZnO Hollow Microspheres and Analysis of Their Gas Sensing Properties for n-Butanol

ZnO hollow microspheres with a diameter of approximately 1.4 μm were successfully synthesized by a facile one-step chemical precipitation method using trisodium citrate dihydrate as a morphology control agent. The ZnO hollow microspheres consisted of nanoplates and had good dispersibility. Control experiments revealed that trisodium citrate dihydrate played an important role in regulating the morphologies of ZnO products. The morphology of the ZnO product evolved from nanowires to hollow microspheres with the addition of trisodium citrate dihydrate. The sensor response of ZnO hollow microspheres toward 100 ppm n-butanol reached 86.6 at the optimum operating temperature of 340 °C, which was approximately three times higher than that of ZnO nanowires. In addition, the ZnO hollow microspheres also displayed good selectivity and long-term work stability toward n-butanol. The excellent gas sensing performance of ZnO hollow microspheres may be ascribed to the unique hollow sphere structure with high exposed polar crystal surface.