Efficient exploration of transition-metal decorated MXene for carbon monoxide sensing using integrated active learning and density functional theory

Abstract

The urgent demand for chemical safety necessitates the real-time detection of carbon monoxide (CO), a highly toxic gas. MXene, a 2D material, has shown potential for gas sensing applications (e.g.,...

Multi-atomic loaded C2N1 catalysts for CO2 reduction to CO or formic acid

“…Finally, in order to explore the conductivity of the catalyst, the height of the DOS curve at the Fermi level for the TM-C 2 N 1 monolayer represents the conductivity of the catalyst. 2,57–62 DOSs were calculated as the key parameters of catalyst conductivity. As shown in Fig.…”

Expanding the Applicability Domain of Machine Learning Model for Advancements in Electrochemical Material Discovery

“…For material screening, we recently used an incremental AL pipeline to conduct high-throughput screening of carbon monoxide sensors on transition-metal decorated MXene search space. [56] The recovery time of sensor material was optimized with the aid of the CGCNN model and K-center sampler. We could identify that the Y and Sc decorated on Zr 3 C 2 O 2 are the best candidates by calculating 110 structures out of 450.…”

Metal-modified C3N1 monolayer sensors for battery instability monitoring

“…Theoretical calculations, employing density functional theory (DFT), have played a pivotal role in accurately predicting the sensing efficiency of two-dimensional (2D) monolayers and elucidating their micro-sensing mechanisms. [9][10][11][12][13][14][15][16][17] For instance, Sun et al 18 utilized DFT calculations to analyze the adsorption behavior of six gases on an indium nitride monolayer, demonstrating its potential in detecting SO 2 and NO 2 molecules. Additionally, rst-principles calculations were employed to explore the structural and electronic properties of group III nitrides and phosphides in gas adsorption.…”