1 citations · 1 across the 1 of their papers we have counts for
9 papers · 1 filter
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…
Modeling phase transformations in Mn-rich disordered rocksalt cathodes with machine learning interatomic potentials
Peichen Zhong, Bowen Deng, Shashwat Anand +2
Mn-rich disordered rocksalt (DRX) cathode materials exhibit a phase transformation from a disordered to a partially disordered spinel-like structure (-phase) during electrochemi…
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…
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…
Origin of Enhanced Performance when Mn-Rich Rocksalt Cathodes transform to -DRX
Shashwat Anand, Tara P. Mishra, Peichen Zhong +4
Most Mn-rich cathodes are known to undergo phase transformation into structures resembling spinel-like ordering upon electrochemical cycling. Recently, the irreversible transformat…
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…