Ab initio investigation of the adsorption properties of molecules on MoS2 pristine and with sulfur vacancy

单层 材料科学 化学物理 吸附 空位缺陷 分子 带隙 从头算 密度泛函理论 工作职能 硫黄 纳米技术 计算化学 结晶学 物理化学 化学 有机化学 图层(电子) 光电子学 冶金
作者
Natan M. Regis,Juarez L. F. Da Silva,Matheus P. Lima
出处
期刊:Materials today communications [Elsevier]
卷期号:38: 107710-107710 被引量:10
标识
DOI:10.1016/j.mtcomm.2023.107710
摘要

MoS2 is a key two-dimensional material with a broad range of potential technological applications, which includes flexible nanoelectronics, sensors, support for catalysts, photovoltaics, etc. During device operation, the interactions of gas molecules with the MoS2 surface can significantly affect its performance. In this study, we report a theoretical study based on density functional theory of the impact of sulfur vacancies, a common point defect in MoS2 monolayers, on the adsorption properties of 12 relevant molecules on MoS2 monolayers. Our findings reveal that H2O, N2, CO, O2, NO, and SO2 exhibit the lowest interaction energies when adsorbed in proximity to sulfur vacancies, leading to a modification in their adsorption orientation compared to the pristine surface of MoS2. In contrast, the remaining investigated molecules (H2, NH3, CH4, N2O, CO2, and NO2) preferentially adsorb on pristine regions of MoS2. We attribute these results to differences in charge transfer between the molecules and the surface, with sulfur vacancies inducing more significant charge transfer for the first set of molecules. Notably, the adsorption of NO stands out from the others as it leads to an increase in the work function of MoS2 by 1.25 eV due to the creation of energy levels within the MoS2 band gap. Additionally, NO passivates sulfur vacancies through covalent bonds. Among the remaining 11 molecules, only NO2 and SO2 induce modifications in the electronic structure around the MoS2 bandgap region, showcasing the potential of MoS2 for sensing these molecules, whereas sulfur vacancies enhance only the SO2/monolayer interaction energy, suggesting a promising avenue for selective sensing.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wdy完成签到,获得积分10
1秒前
猪猪侠应助举人烧烤采纳,获得10
1秒前
1秒前
英俊的铭应助dongjingbutaire采纳,获得10
2秒前
HollidayLee完成签到,获得积分10
2秒前
费城青年完成签到,获得积分10
2秒前
3秒前
3秒前
科研通AI6应助ou采纳,获得10
4秒前
张mingyu123发布了新的文献求助10
4秒前
万能图书馆应助pla采纳,获得10
5秒前
Mannose发布了新的文献求助10
5秒前
5秒前
飞翔的鸣发布了新的文献求助10
5秒前
6秒前
桐桐应助gulugulugulug采纳,获得10
6秒前
CipherSage应助苏苏采纳,获得10
7秒前
7秒前
7秒前
举人烧烤完成签到,获得积分10
7秒前
小巧的问旋完成签到,获得积分10
8秒前
Akim应助rortis采纳,获得10
8秒前
打打应助dalunshinidie123采纳,获得10
8秒前
JIA9527完成签到,获得积分10
8秒前
10秒前
10秒前
xx发布了新的文献求助10
11秒前
闫闫完成签到 ,获得积分10
12秒前
su完成签到,获得积分10
12秒前
上好佳完成签到,获得积分10
12秒前
Efficient完成签到 ,获得积分10
13秒前
15秒前
霸霸发布了新的文献求助10
15秒前
孙天天给孙天天的求助进行了留言
15秒前
16秒前
16秒前
顺心的大碗完成签到,获得积分10
16秒前
16秒前
cavendipeng发布了新的文献求助10
16秒前
QDF发布了新的文献求助20
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Exploring Nostalgia 500
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 500
Advanced Memory Technology: Functional Materials and Devices 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5666691
求助须知:如何正确求助?哪些是违规求助? 4882812
关于积分的说明 15117878
捐赠科研通 4825664
什么是DOI,文献DOI怎么找? 2583534
邀请新用户注册赠送积分活动 1537723
关于科研通互助平台的介绍 1495910