1.8k citations · 6.6k across the 53 of their papers we have counts for
55 papers
ALIGNN 2.0: A Unified Line-Graph Neural Network Framework for Materials Screening, Force Fields, Inverse Design, Spectroscopy, and Microscopy
Jaehyung Lee, Charles Rhys Campbell, Akshaya Ajith +3
Graph neural networks are central to materials property prediction and machine-learning interatomic potentials, yet their reliance on specialized graph libraries hampers portabilit…
A Unified Understanding of Minimum Lattice Thermal Conductivity
Yi Xia, Dale Gaines, Jiangang He +4
We propose a first-principles model of minimum lattice thermal conductivity () based on a unified theoretical treatment of thermal transport in crystals and gl…
Accelerated Screening of Ternary Chalcogenides for High-Performance Optoelectronic Materials
Chen Shen, Tianshu Li, Yixuan Zhang +7
Chalcogenides, which refer to chalcogen anions, have attracted considerable attention in multiple fields of applications, such as optoelectronics, thermoelectrics, transparent cont…
Testing the rSCAN density functional for the thermodynamic stability of solids with and without a van der Waals correction
Manish Kothakonda, Aaron D. Kaplan, Eric B. Isaacs +6
A central aim of materials discovery is an accurate and numerically reliable description of thermodynamic properties, such as the enthalpies of formation and decomposition. The r$^…
Identification of High-Dielectric Constant Compounds from Statistical Design
Abhijith Gopakumar, Koushik Pal, Chris Wolverton
The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries. Here, we report three previously unexplored materials with v…
Assessing the accuracy of compound formation energies with quantum Monte Carlo
Eric B. Isaacs, Hyeondeok Shin, Abdulgani Annaberdiyev +4
Accurately predicting the formation energy of a compound, which describes its thermodynamic stability, is a key challenge in materials physics. Here, we employ many-body quantum Mo…