Medford, Andrew J.

1. The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture
   2023/11/01 by Anuroop Sriram, Sriram, Anuroop, Sihoon Choi +14 · 8 citations
   Chemistry · Engineering · Materials Science · #Metal-Organic Frameworks: Synthesis and Applications #Carbon Dioxide Capture Technologies #Machine Learning in Materials Science
2. Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials
   2022/08/17 by Yuge Hu, Joseph Musielewicz, Hu, Yuge +5 · 4 citations
   Computer Science · Materials Science · Physics and Astronomy · #Advanced Neural Network Applications #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Model Reduction and Neural Networks
3. SPARC: Simulation Package for Ab-initio Real-space Calculations
   2020/05/21 by Qimen Xu, Xu, Qimen, Abhiraj Sharma +13 · 4 citations
   Chemistry · Materials Science · Physics and Astronomy · #Advanced Chemical Physics Studies #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Zeolite Catalysis and Synthesis
4. The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture
   2025/08/05 by Anuroop Sriram, Logan M. Brabson, Sriram, Anuroop +27 · 2 voices · 7 citations
   #cond-mat.mtrl-sci #cs.LG #physics.chem-ph
5. Analysis of Photocatalytic Nitrogen Fixation on Rutile TiO₂(110)
   2017/07/10 by Benjamin M. Comer, Andrew J. Medford, Comer, Benjamin M. +1 · 1 citation
   Chemical Engineering · Energy · Materials Science · #Advanced Photocatalysis Techniques #Ammonia Synthesis and Nitrogen Reduction #Catalytic Processes in Materials Science #Chemical Physics (physics.chem-ph) #FOS: Physical sciences
6. Soft and transferable pseudopotentials from multi-objective optimization
   2022/09/20 by Shojaei, Mostafa Faghih, Pask, John E., Medford, Andrew J. +1 · 2 citations
   #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences
7. Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems
   2023/04/12 by Gabriel S. Gusmão, Andrew J. Medford, Gusmão, Gabriel S. +1 · 1 citation
   Computer Science · Materials Science · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning in Materials Science #Model Reduction and Neural Networks #Neural Networks and Applications #Numerical Analysis (math.NA)
8. MLFF_GMP
   2024/04/11 by Lucas R. Timmerman, Timmerman, Lucas R., Shashikant Kumar +5 · 1 citation
   Biochemistry, Genetics and Molecular Biology · Materials Science · Physics and Astronomy · #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Protein Structure and Dynamics #Spectroscopy and Quantum Chemical Studies
9. Kohn-Sham accuracy from orbital-free density functional theory via Δ-machine learning
   2023/10/10 by Shashikant Kumar, Xin Jing, Kumar, Shashikant +7 · 1 citation
   Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Advanced Chemical Physics Studies #Electron and X-Ray Spectroscopy Techniques
10. Spectral scheme for atomic structure calculations in density functional theory
    2024/06/01 by Sayan Bhowmik, Bhowmik, Sayan, John E. Pask +5 · 2 citations
    Chemical Engineering · Chemistry · #Catalysis and Oxidation Reactions #Chemical Thermodynamics and Molecular Structure #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Inorganic Fluorides and Related Compounds #Materials Science (cond-mat.mtrl-sci)