A DFT study of the adsorption behavior and sensing properties of CO gas on monolayer MoSe2 in CO2-rich environment.

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2024-07-05 DOI:10.1007/s00894-024-06014-y
V P Vinturaj, Ashish Kumar Yadav, Rohit Singh, Vivek Garg, Ritesh Bhardwaj, K M Ajith, Sushil Kumar Pandey
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Abstract

Context: Carbon monoxide, also known as the "silent killer," is a colorless, odorless, tasteless, and non-irritable gas that, when inhaled, enters the bloodstream and lungs, binds with the hemoglobin, and blocks oxygen from reaching tissues and cells. In this work, the monolayer MoSe2-based CO gas sensors were designed using density functional theory calculation with several dopants including Al, Au, Pd, Ni, Cu, and P. Here, Cu and P were found to be the best dopants, with adsorption energies of -0.67 eV (Cu) and -0.54 eV (P) and recovery times of 1.66 s and 13.8 ms respectively. Cu conductivity for CO adsorption was found to be 2.74 times that of CO2 adsorption in the 1.0-2.26 eV range. P displayed the highest selectivity, followed by Pd and Ni. The dopants, Pd and Ni, were found suitable for building CO gas scavengers due to their high recovery times of 9.76 × 1020 s and 2.47 × 1011 s. Similarly, the adsorption of CO2 on doped monolayer MoSe2 was also investigated. In this study, it is found that monolayer MoSe2 could be employed to create high-performance CO sensors in a CO2-rich environment.

Method: The electrical characteristics of all doped MoSe2 monolayers are obtained using a DFT calculation with the PBE-GGA method from the Quantum ESPRESSO package. The self-consistent field (SCF) computations were performed using a 7 × 7 × 1 k-point grid and a norm-conserving pseudo potential (NCPP) file. To determine electrical conductivity, the semi-classical version of Boltzmann transport theory, implemented in the Boltz Trap code, was used.

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富二氧化碳环境中一氧化碳气体在单层 MoSe2 上的吸附行为和传感特性的 DFT 研究。
背景:一氧化碳又称 "无声杀手",是一种无色、无臭、无味、无刺激性的气体,吸入人体后会进入血液和肺部,与血红蛋白结合,阻碍氧气进入组织和细胞。在这项工作中,利用密度泛函理论计算设计了基于 MoSe2 的单层一氧化碳气体传感器,其中使用了多种掺杂剂,包括 Al、Au、Pd、Ni、Cu 和 P。在此发现,Cu 和 P 是最佳掺杂剂,其吸附能量分别为 -0.67 eV(Cu)和 -0.54 eV(P),恢复时间分别为 1.66 s 和 13.8 ms。在 1.0-2.26 eV 范围内,Cu 对 CO 的吸附电导率是 CO2 吸附电导率的 2.74 倍。P 的选择性最高,其次是 Pd 和 Ni。掺杂剂 Pd 和 Ni 的高回收时间分别为 9.76 × 1020 s 和 2.47 × 1011 s,因此适合用于制造 CO 气体清除剂。本研究发现,单层 MoSe2 可用于在富含二氧化碳的环境中制造高性能的一氧化碳传感器:方法:使用量子 ESPRESSO 软件包中的 PBE-GGA 方法进行 DFT 计算,获得了所有掺杂 MoSe2 单层的电学特性。自洽场(SCF)计算采用 7 × 7 × 1 k 点网格和规范保守伪电势(NCPP)文件。为了确定导电率,使用了半经典版本的波尔兹曼输运理论,该理论在 Boltz Trap 代码中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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