Showing results (1-10 of 174) with videos related to
Sort By:
Pageof 18
ACS Central Science|August 8, 2026
Replacing Quantum Chemistry With Machine-Learned Interatomic Potentials: Revolution or Evolution?Andrew J Medford, David S ShollThe Journal of Chemical Physics|June 8, 2022
Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal-organic frameworksSihoon Choi, David S Sholl, Andrew J MedfordThe Journal of Physical Chemistry. C, Nanomaterials and Interfaces|September 24, 2025
Comparing Classical and Machine Learning Force Fields for Modeling Deformation of Metal-Organic Frameworks Relevant for Direct Air CaptureLogan M Brabson, Andrew J Medford, David S ShollACS Central Science|May 27, 2024
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air CaptureAnuroop Sriram, Sihoon Choi, Xiaohan Yu, et al.Accounts of Chemical Research|June 21, 2006
Understanding macroscopic diffusion of adsorbed molecules in crystalline nanoporous materials via atomistic simulationsDavid S ShollLangmuir : the ACS Journal of Surfaces and Colloids|April 6, 2006
Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneityDavid S ShollThe Journal of Physical Chemistry. C, Nanomaterials and Interfaces|February 4, 2026
Examination of Replicate Syntheses of Metal Organic Frameworks as a Window into Reproducibility in Materials ChemistryDavid S ShollThe Journal of Physical Chemistry Letters|August 18, 2022
A Universal Framework for Featurization of Atomistic SystemsXiangyun Lei, Andrew J MedfordThe Journal of Chemical Physics|August 6, 2020
Classification of biomass reactions and predictions of reaction energies through machine learningChaoyi Chang, Andrew J MedfordLangmuir : the ACS Journal of Surfaces and Colloids|January 13, 2006
Efficient simulation of binary adsorption isotherms using transition matrix Monte CarloHaibin Chen, David S ShollPageof 18