1 citations · 1 across the 3 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2022
DeepXRD, a Deep Learning Model for Predicting of XRD spectrum from Materials Composition
Rongzhi Dong, Yong Zhao, Yuqi Song +6
One of the long-standing problems in materials science is how to predict a material's structure and then its properties given only its composition. Experimental characterization of…
cond-mat.mtrl-sci2021★ 1 cited
Scalable deeper graph neural networks for high-performance materials property prediction
Sadman Sadeed Omee, Steph-Yves Louis, Nihang Fu +5
Machine learning (ML) based materials discovery has emerged as one of the most promising approaches for breakthroughs in materials science. While heuristic knowledge based descript…
physics.app-ph2021
Modeling and Optimizing Laser-Induced Graphene
Lars Kotthoff, Sourin Dey, Vivek Jain +3
A lot of technological advances depend on next-generation materials, such as graphene, which enables a raft of new applications, for example better electronics. Manufacturing such…