Knowledge-Reuse Transfer Learning Methods in Molecular and Material Science

arXiv:2403.12982v1 Announce Type: cross
Abstract: Molecules and materials are the foundation for the development of modern advanced industries such as energy storage systems and semiconductor devices. However, traditional trial-and-error methods or theoretical calculations are highly resource-intensive, and extremely long R&D (Research and Development) periods cannot meet the urgent need for molecules/materials in industrial development. Machine learning (ML) methods based on big data are expected to break this dilemma. However, the difficulty in constructing large-scale datasets of new molecules/materials due to …

abstract advanced arxiv cond-mat.mtrl-sci cs.lg development devices energy energy storage error foundation however industries knowledge material materials modern molecules physics.chem-ph research research and development science semiconductor storage systems transfer transfer learning type