material

Predicting the Hydrogen Release Ability of LiBH4-based Mixtures by Ensemble Machine Learning

The prediction of hydrogen release ability is indispensable to evaluating hydrogen storage performance of LiBH 4 -based mixtures before experimentation. In order to achieve this goal, ensemble machine learning is employed to automatically infer the …

Unsupervised Discovery of Solid-State Lithium Ion Conductors

Apply hierarchical clustering technique for characterizing Solid-State Lithium Ion conductors

Materials Application by Deep Learning

[ Collaborated with Toyota Research, Illinois Tech ] Material development heavily relies on domain knowledge and professional’s intuitive, which hinders the discovery of new material. We are collaborating with material experts and propose generative models for boosting material discovery.

LiBH4 for hydrogen storage - New perspectives

Hydrogen energy has been recognized as “Ultimate Power Source” in the 21st century. It is a boon in these days of energy crunches and concerns about climate change because of the characterized advantages, such as high energy density, large calorific …