Theoretical prediction of disulfide defects (S22−) in molybdenum disulfide monolayers

IF 2.1 4区化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2025-02-10 DOI:10.1007/s00894-025-06306-x

Maxim R. Ryzhikov, Svetlana G. Kozlova

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Abstract

Context

Defects have a noticeable influence on many properties of two-dimensional materials. The controlled formation of defects can be used for fine-tuning the electronic and chemical properties of transition metal dichalcogenide monolayers. The formation of a new type of displacement defect on the molybdenum disulfide (MoS₂) monolayer surface has been studied using density functional theory. In the defect structure, two sulfur atoms form a disulfide bridge between the Mo atoms. The sulfur-sulfur bond is confirmed by interatomic distances, atomic charges, and Electron Localization Function analysis.

Methods

The PBEsol density functional in the BAND2017 and VASP software packages was used for structural relaxation and NEB pathway calculations for the MoS₂ monolayers. The Slater-type orbital basis set TZP and PAW pseudopotential were used in the BAND2017 and VASP 6.2.0 codes, respectively. Additionally, single-point calculations with SCAN and HSE06 density functionals were performed. QTAIM charges and ELF distributions were calculated using the BAND2017 package.

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来源期刊

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.