Title: | Single-Atom Tailoring of Two-Dimensional Atomic Crystals Enables Highly Efficient Detection and Pattern Recognition of Chemical Vapors |
Author(s): | Liu B; Zhu Q; Pan Y; Huang F; Tang L; Liu C; Cheng Z; Wang P; Ma J; Ding M; |
Address: | "Key Laboratory of Mesoscopic Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, People's Republic of China. Institute of Theoretical and Computational Chemistry, Nanjing University, Nanjing 210023, People's Republic of China. College of Engineering and Applied Sciences, Nanjing University, Nanjing 210023, People's Republic of China" |
DOI: | 10.1021/acssensors.2c00356 |
ISSN/ISBN: | 2379-3694 (Electronic) 2379-3694 (Linking) |
Abstract: | "Low-dimensional semiconductor materials, such as single-walled carbon nanotubes, two-dimensional (2D) atomic crystals, and organic frameworks, have been widely adapted as ideal platforms to construct various chemo/biosensors with satisfying sensitivity. However, the general drawbacks in chemiresistive devices, including high operation temperatures, low response to low-polarity molecules, and poor selectivity, have limited their real-world applications. In this study, 2D materials (graphene, MoS(2), and WSe(2)) were systematically functionalized with series of monodispersed single atomic sites (Pt, Co, and Ru) through a facile approach to construct single-atom sensors (SASs) for the detection of VOCs at room temperature. The structural and catalytic characteristics of SAs successfully translated into enhanced gas-sensing performance, with a 1-2 orders of magnitude increase in relative response to ethanol (@5 ppm) and acetone (@20 ppm) vapors (in all M-2D SASs as compared to pristine substrates), high selectivity to VOCs against relative humidity (M-WSe(2) SASs), and fast response/recovery time (11/58 s for Pt-Graphene and 22/48 s for Pt-MoS(2) to 50 ppm ethanol, 9/57 s for Pt-Graphene and 15/75 s for Pt-MoS(2) to 200 ppm acetone) that are several times faster than the pristine 2D materials. Density functional theory (DFT) calculations revealed the signaling mechanism in SASs, and the data were further trained to build machine learning (ML) models for predicting the adsorption energies and sensing performance using the features of adsorption heights, metal charge, and charge transfer between the adsorbed VOCs and SASs sites. Finally, the rich combination of the metal single atoms and 2D atomic crystal supports were converted to cross-sensitive SA sensor array that allows for detection and identification of different VOCs" |
Keywords: | 2D materials chemiresistior gas detection single atom sensor volatile organic compounds; |
Notes: | "PubMed-not-MEDLINELiu, Bingqian Zhu, Qin Pan, Yanghang Huang, Futao Tang, Lingyu Liu, Cheng Cheng, Zheng Wang, Peng Ma, Jing Ding, Mengning eng 2022/05/14 ACS Sens. 2022 May 27; 7(5):1533-1543. doi: 10.1021/acssensors.2c00356. Epub 2022 May 11" |