Comprehensive Study of Lithium Adsorptionand Diffusion on Janus Mo/WXY (X, Y= S,Se, Te) using First Principles and MachineLearning Approaches
Gracie Chaney, Akram Ibrahim, Fatih Ersan, Deniz \c{C}ak{\i}r, and Can, Ataca

TL;DR
This study investigates lithium adsorption and diffusion on Janus transition metal dichalcogenides using first principles and machine learning, revealing promising properties for battery electrode applications.
Contribution
It introduces a machine learning model with a universal descriptor for predicting Li adsorption energies on 2D TMDs, including Janus structures, and analyzes their potential as battery anodes.
Findings
Li atoms migrate easily between transition metal top sites.
Many Janus materials outperform graphene and regular TMDs as electrodes.
Janus structures show promise for Li-ion battery applications.
Abstract
The structural asymmetry of two-dimensional (2D) Janus transition metal dichalcogenides (TMDs) produces internal dipole moments that result in interesting electronic properties. These properties differ from the regular (symmetric) TMD structures that the Janus structures are derived from. In this study, we, at first, examine adsorption and diffusion of a single Li atom on regular MX2and Janus MXY (M = Mo, W; XY =S, Se, Te) TMD structures at various concentrations using first principles calculations within density functional theory. To gain more physical insight and prepare for future investigations of regular TMD and Janus materials, we applied a supervised machine learning (ML) model that uses cluster-wise linear regression to predict the adsorption energies of Li on top of 2D TMDs. We developed a universal representation with few descriptors that take into account the intrinsic dipole…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
Topics2D Materials and Applications · Machine Learning in Materials Science · Advanced Photocatalysis Techniques
