Search Results for author: Rongzhi Dong

Found 5 papers, 2 papers with code

Materials Transformers Language Models for Generative Materials Design: a benchmark study

no code implementations27 Jun 2022 Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu

We also find that the properties of the generated samples can be tailored by training the models with selected training sets such as high-bandgap materials.

Scalable deeper graph neural networks for high-performance materials property prediction

1 code implementation25 Sep 2021 Sadman Sadeed Omee, Steph-Yves Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu

Machine learning (ML) based materials discovery has emerged as one of the most promising approaches for breakthroughs in materials science.

Band Gap Graph Attention +1

Crystal structure prediction of materials with high symmetry using differential evolution

no code implementations20 Apr 2021 Wenhui Yang, Edirisuriya M. Dilanga Siriwardane, Rongzhi Dong, Yuxin Li, Jianjun Hu

Our experimental results show that our proposed algorithm CMCrystalHS can effectively solve the problem of inconsistent contact map dimensions and predict the crystal structures with high symmetry.

AlphaCrystal: Contact map based crystal structure prediction using deep learning

no code implementations2 Feb 2021 Jianjun Hu, Yong Zhao, Wenhui Yang, Yuqi Song, Edirisuriya MD Siriwardane, Yuxin Li, Rongzhi Dong

To our knowledge, AlphaCrystal is the first neural network based algorithm for crystal structure contact map prediction and the first method for directly reconstructing crystal structures from materials composition, which can be further optimized by DFT calculations.

Protein Structure Prediction Materials Science

MLatticeABC: Generic Lattice Constant Prediction of Crystal Materials using Machine Learning

1 code implementation30 Oct 2020 Yuxin Li, Wenhui Yang, Rongzhi Dong, Jianjun Hu

Lattice constants such as unit cell edge lengths and plane angles are important parameters of the periodic structures of crystal materials.

Materials Science Computational Physics

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