Seed project: Development of machine-learning interatomic potentials for two-dimensional antiferromagnetic MnX and Janux XMnY (X, Y=S, Se, Te)
We plan to develop machine-learning (ML) models on large datasets of atomic configurations of two-dimensional (2D) antiferromagnetic MnX and Janus XMnY (X, Y=S, Se, Te). Once trained and benchmarked, these models can accurately predict thermal, mechanical, and spintronic properties of complex charge/spin configurations.
Seed project information
Project manager
Shahid Sattar
Other project members
Carlo M. Canali, Welf Löwe, Morgan Ericsson, Linnaeus University, Daniel Hedman, IBS, Korea
Participating organisations
Linnaeus University, IBS, Korea
Financier
Linnaeus University Centre for Data Intensive Sciences and Applications (DISA), VR 2021-04622
Timetable
Aug 2024-Oct 2024
Subject
Computer Science (Department of Computer Science and Media Technology, Faculty of Technology)
Research Groups
Condensed Matter Physics, Linnaeus University Centre for Data Intensive Sciences and Applications (DISA)
Knowledge Environment
Linnaeus Knowledge Environment: Advanced materials
More about the project
The use of machine-learning (ML) methods in materials sciences is exponentially increasing owing to their success in predicting material properties. To leverage capabilities of ML models and expedite and foster innovation in this realm, we plan to develop new ML techniques using large datasets of atomic configurations of 2D antiferromagnetic crystals. Aiming to reduce computational costs and maintaining accuracy close to that of ab-initio methods, we predict material properties (such as thermal conductivities) and their possible technological applications.
What is a seed project?
A seed project is a minor project funded by a knowledge environment or a research group at the university. The aim is to launch and promote excellent research. Depending on the financier, a seed project may be to idenfify new or deepen existing collaborations, preferably cross-disciplinary ones, to explore possible research issues in a feasibility study, to collect empirical material, or to write an application for external funding.
DISA's seed projects
Learn more about the seed project concept and DISA's other seed projects.
