8 papers
Machine-Learning-Guided Insights into Solid-Electrolyte Interphase Conductivity: Are Amorphous Lithium Fluorophosphates the Key?
Peichen Zhong, Kristin A. Persson
Despite decades of study, the identity of the dominant \ce{Li+}-conducting phase within the inorganic SEI of Li-ion batteries remains unresolved. While the mosaic model describes L…
MatLLMSearch: Crystal Structure Discovery with Evolution-Guided Large Language Models
Jingru Gan, Peichen Zhong, Yuanqi Du +7
Crystal structure generation is fundamental to materials science, enabling the discovery of novel materials with desired properties. While existing approaches leverage Large Langua…
Crystal structure prediction with host-guided inpainting generation and foundation potentials
Peichen Zhong, Xinzhe Dai, Bowen Deng +2
Unconditional crystal structure generation with diffusion models faces challenges in identifying symmetric crystals as the unit cell size increases. We present the Crystal Host-Gui…
MP-ALOE: An r2SCAN dataset for universal machine learning interatomic potentials
Matthew C. Kuner, Aaron D. Kaplan, Kristin A. Persson +2
We present MP-ALOE, a dataset of nearly 1 million DFT calculations using the accurate r2SCAN meta-generalized gradient approximation. Covering 89 elements, MP-ALOE was created usin…
The Interplay Between Electron Localization, Magnetic Order, and Jahn-Teller Distortion that Dictates LiMnO Phase Stability
Ronald L. Kam, Luca Binci, Aaron D. Kaplan +3
The development of Mn-rich cathodes for Li-ion batteries promises to alleviate supply chain bottlenecks in battery manufacturing. Challenges in Mn-rich cathodes arise from Jahn-Tel…
Cross-functional transferability in universal machine learning interatomic potentials
Xu Huang, Bowen Deng, Peichen Zhong +3
The rapid development of universal machine learning interatomic potentials (uMLIPs) has demonstrated the possibility for generalizable learning of the universal potential energy su…