Drawing a materials map with an autoencoder for lithium ionic conductors.

ABSTRACT: Efforts to optimize known materials and enhance their performance are ongoing, driven by the advancements resulting from the discovery of novel functional materials. Traditionally, the search for and optimization of functional materials has relied on the experience and intuition of specialized researchers. However, materials informatics (MI), which integrates materials data and machine learning, has frequently been used to realize systematic and efficient materials exploration without depending on manual tasks. Nonetheless, the discovery of new materials using MI remains challenging. In this study, we propose a method for the discovery of materials outside the scope of existing databases by combining MI with the experience and intuition of researchers. Specifically, we designed a two-dimen

SUBMITTER: Yamaguchi Y 

PROVIDER: S-EPMC10556005 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature