Kristin A. Persson
- A foundation model for atomistic materials chemistry
2023/12/29 by Ilyes Batatia, Philipp Benner, Batatia, Ilyes +182 · 5 voices · 138 citations
Materials Science · Decision Sciences · #physics.chem-ph #cond-mat.mtrl-sci
- An autonomous laboratory for the accelerated synthesis of inorganic materials
2023/11/29 by Nathan J. Szymanski, Bernardus Rendy, Yuxing Fei +13 · 47 citations
Materials Science · #Electronic and Structural Properties of Oxides #Machine Learning in Materials Science #X-ray Diffraction in Crystallography
- Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions
2023/08/28 by Janosh Riebesell, Rhys E. A. Goodall, Riebesell, Janosh +13 · 14 citations
Computer Science · Materials Science · #Computational Drug Discovery Methods #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #X-ray Diffraction in Crystallography
- Promises and Challenges of Next-Generation “Beyond Li-ion” Batteries for Electric Vehicles and Grid Decarbonization
2020/12/24 by Yaosen Tian, Guobo Zeng, Ann Rutt +11 · 6 citations
Engineering · #Advanced Battery Materials and Technologies #Advanced Battery Technologies Research #Advancements in Battery Materials
- A Foundational Potential Energy Surface Dataset for Materials
2025/03/06 by Aaron D. Kaplan, Kaplan, Aaron D., Runze Liu +15 · 18 citations
Materials Science · Physics and Astronomy · Chemistry · #Machine Learning in Materials Science #Quantum many-body systems #Advanced Physical and Chemical Molecular Interactions
- Atomate2: modular workflows for materials science
2025/01/01 by Alex M. Ganose, Hrushikesh Sahasrabuddhe, Mark Asta +53 · 2 voices · 8 citations
Chemical Engineering · Decision Sciences · Materials Science · #Catalysis and Oxidation Reactions #Machine Learning in Materials Science #Scientific Computing and Data Management
- Overcoming systematic softening in universal machine learning interatomic potentials by fine-tuning
2024/05/11 by Bowen Deng, Deng, Bowen, Yunyoung Choi +15 · 6 citations
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Materials Science (cond-mat.mtrl-sci) #Neural Networks and Applications
- Designing transparent conductors using forbidden optical transitions
2023/03/29 by Rachel Woods‐Robinson, Yihuang Xiong, Woods-Robinson, Rachel +15 · 3 citations
Materials Science · Physics and Astronomy · #Electronic and Structural Properties of Oxides #ZnO doping and properties #Advanced Condensed Matter Physics
- Machine Learned Potential for High-Throughput Phonon Calculations of Metal-Organic Frameworks
2024/12/03 by Alin M. Elena, Alin Marin Elena, Elena, Alin Marin +12 · 1 voice · 3 citations
Chemistry · Materials Science · Physics and Astronomy · #Chemical Physics (physics.chem-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Metal-Organic Frameworks: Synthesis and Applications #X-ray Diffraction in Crystallography #cond-mat.mtrl-sci #physics.chem-ph
- Incorporating electronic information into Machine Learning potential energy surfaces via approaching the ground-state electronic energy as a function of atom-based electronic populations
2020/03/04 by Xiaowei Xie, Xie, Xiaowei, Kristin A. Persson +3 · 1 citation
Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Advanced Chemical Physics Studies #X-ray Diffraction in Crystallography
- Full spectrum optical constant interface to the Materials Project
2021/08/24 by J. J. Kas, Fernando D. Vila, Kas, J. J. +11 · 1 citation
Chemical Engineering · Materials Science · #Catalysis and Oxidation Reactions #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #X-ray Diffraction in Crystallography
- High-throughput optical absorption spectra for inorganic semiconductors
2022/09/07 by Ruoxi Yang, Yang, Ruo Xi, Matthew K. Horton +5 · 1 citation
Chemical Engineering · Chemistry · #Analytical Chemistry and Sensors #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Spectroscopy and Chemometric Analyses #Spectroscopy and Laser Applications
- A Critical Analysis of Chemical and Electrochemical Oxidation Mechanisms in Li-Ion Batteries
2024/01/04 by Evan Walter Clark Spotte‐Smith, Sudarshan Vijay, Thea Bee Petrocelli +3 · 1 voice · 1 citation
Engineering · #Advancements in Battery Materials #Advanced Battery Materials and Technologies #Advanced battery technologies research
- RNMC: kinetic Monte Carlo implementations for complex reaction networks
2024/12/17 by Laura Zichi, Daniel Barter, Eric Sivonxay +5 · 1 voice · 1 citation
Chemical Engineering · Engineering · Materials Science · #Advanced Memory and Neural Computing #Catalysis and Oxidation Reactions #Machine Learning in Materials Science
- Structured information extraction from complex scientific text with fine-tuned large language models
2022/12/10 by Alexander Dunn, John Dagdelen, Dunn, Alexander +13 · 1 citation
Materials Science · Computer Science · #Machine Learning in Materials Science #Topic Modeling
- A database of molecular properties integrated in the Materials Project
2023/01/01 by Evan Walter Clark Spotte‐Smith, Orion Cohen, Samuel M. Blau +9 · 1 voice · 1 citation
Materials Science · Computer Science · #Machine Learning in Materials Science #X-ray Diffraction in Crystallography #Computational Drug Discovery Methods
- Data-driven Design of Metal-Organic Frameworks with Tunable Negative Thermal Expansion
2026/07/21 by Prathami Divakar Kamath, Francesco Tavani, Alin Marin Elena +6 · 1 voice
#cond-mat.mtrl-sci