348 citations · 1k across the 41 of their papers we have counts for
4 papers · 1 filter
Machine learning and high-throughput robust design of P3HT-CNT composite thin films for high electrical conductivity
Daniil Bash, Yongqiang Cai, Vijila Chellappan +16
Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that ma…
Efficacious symmetry-adapted atomic displacement method for lattice dynamical studies
Chee Kwan Gan, Yun Liu, Tze Chien Sum +1
Small displacement methods have been successfully used to calculate the lattice dynamical properties of crystals. It involves displacing atoms by a small amount in order to calcula…
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Zekun Ren, Siyu Isaac Parker Tian, Juhwan Noh +14
Realizing general inverse design could greatly accelerate the discovery of new materials with user-defined properties. However, state-of-the-art generative models tend to be limite…
Machine-learning assisted cross-domain prediction of ionic conductivity in sodium and lithium-based superionic conductors
Yijie Xu, Yun Zong, Kedar Hippalgaonkar
Solid state lithium- and sodium-ion batteries utilize solid ionicly conducting compounds as electrolytes. However, the ionic conductivity of such materials tends to be lower than t…