Publications (7)
A fingerprint based metric for measuring similarities of crystalline structures
Li Zhu, Maximilian Amsler, Tobias Fuhrer +8
Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordi…
Inverse Design of Ultralow Lattice Thermal Conductivity Materials Via Lone Pair Cation Coordination Environment
Eric B. Isaacs, Grace M. Lu, Christopher Wolverton
The presence of lone pair (LP) electrons is strongly associated with the disruption of lattice heat transport, which is a critical component of strategies to achieve efficient ther…
Tailored ordering enables high-capacity cathode materials
Tzu-chen Liu, Adolfo Salgado-Casanova, So Yubuchi +7
Newly designed Li-ion battery cathode materials with high capacity and greater flexibility in chemical composition will be critical for the growing electric vehicles market. Cathod…
A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials
Logan Ward, Ankit Agrawal, Alok Choudhary +1
A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior example…
Accelerating Discovery of Extreme Lattice Thermal Conductivity by Crystal Attention Graph Neural Network (CATGNN) Using Chemical Bonding Intuitive Descriptors
Mohammed Al-Fahdi, Riccardo Rurali, Jianjun Hu +2
Designing materials with targeted lattice thermal conductivity (LTC) demands electronic-level insight into chemical bonding. We introduce two bonding descriptors, namely normalized…
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery
Dipendra Jha, Logan Ward, Zijiang Yang +5
Materials discovery is crucial for making scientific advances in many domains. Collections of data from experiments and first-principle computations have spurred interest in applyi…