| Text mining metal–organic framework papers S Park, B Kim, S Choi, PG Boyd, B Smit, J Kim Journal of chemical information and modeling 58 (2), 244-251, 2018 | 48 | 2018 |
| Efficient models for predicting temperature-dependent henry’s constants and adsorption selectivities for diverse collections of molecules in metal–organic frameworks X Yu, S Choi, D Tang, AJ Medford, DS Sholl The Journal of Physical Chemistry C 125 (32), 18046-18057, 2021 | 27 | 2021 |
| Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal–organic frameworks S Choi, DS Sholl, AJ Medford The Journal of Chemical Physics 156 (21), 2022 | 4 | 2022 |
| The Open DAC 2023 dataset and challenges for sorbent discovery in direct air capture A Sriram, S Choi, X Yu, LM Brabson, A Das, Z Ulissi, M Uyttendaele, ... arXiv preprint arXiv:2311.00341, 2023 | 3 | 2023 |
| Accelerating Development of Porous Sorbents for Direct Air Capture Using High Throughput Computing and Machine Learning X Yu, L Brabson, S Choi, A Medford, D Sholl, A Sriram 2023 AIChE Annual Meeting, 2023 | | 2023 |
| An Efficient Featurization Scheme for Machine-Learning Predictions of Diverse Molecules in Metal-Organic Frameworks S Choi, X Yu, D Sholl, A Medford 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Efficiently Exploring the Adsorption Space of Molecules in MOFs Combining the Use of Molecular Simulations, Machine Learning, and IAST X Yu, S Choi, A Medford, D Sholl 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Online Graduate Certificate in Data Science for the Chemical Industry A Medford, F Boukouvala, M Grover, D Sholl, C Meredith, P Cheng, ... Chemical Engineering Education, 249-259, 2022 | | 2022 |
Andrew J. MedfordAssistant Professor, School of Chemical & Biomolecular Engineering, Georgia Institute of TechnologyEmail verificata su chbe.gatech.edu
