| Multivariate metal–organic frameworks for dialing-in the binding and programming the release of drug molecules Z Dong, Y Sun, J Chu, X Zhang, H Deng Journal of the American Chemical Society 139 (40), 14209-14216, 2017 | 239 | 2017 |
| Metal-organic frameworks for precise inclusion of single-stranded DNA and transfection in immune cells S Peng, B Bie, Y Sun, M Liu, H Cong, W Zhou, Y Xia, H Tang, H Deng, ... Nature Communications 9 (1), 1293, 2018 | 215 | 2018 |
| Fingerprinting diverse nanoporous materials for optimal hydrogen storage conditions using meta-learning Y Sun, RF DeJaco, Z Li, D Tang, S Glante, DS Sholl, CM Colina, RQ Snurr, ... Science Advances 7 (30), eabg3983, 2021 | 57 | 2021 |
| Deep neural network learning of complex binary sorption equilibria from molecular simulation data Y Sun, RF DeJaco, JI Siepmann Chemical science 10 (16), 4377-4388, 2019 | 51 | 2019 |
| Assessing the quality of molecular simulations for vapor–liquid equilibria: An analysis of the TraPPE database BL Eggimann, Y Sun, RF DeJaco, R Singh, M Ahsan, TR Josephson, ... Journal of Chemical & Engineering Data 65 (3), 1330-1344, 2019 | 43 | 2019 |
| MOFX-DB: An online database of computational adsorption data for nanoporous materials NS Bobbitt, K Shi, BJ Bucior, H Chen, N Tracy-Amoroso, Z Li, Y Sun, ... Journal of Chemical & Engineering Data 68 (2), 483-498, 2023 | 30 | 2023 |
| Multiple linear regression and thermodynamic fluctuations are equivalent for computing thermodynamic derivatives from molecular simulation A Rahbari, TR Josephson, Y Sun, OA Moultos, D Dubbeldam, ... Fluid Phase Equilibria 523, 112785, 2020 | 16 | 2020 |
| Development of a PointNet for detecting morphologies of self-assembled block oligomers in atomistic simulations Z Shen, Y Sun, TP Lodge, JI Siepmann The Journal of Physical Chemistry B 125 (20), 5275-5284, 2021 | 7 | 2021 |
| Large-scale molecular dynamics simulations of bubble collapse in water: Effects of system size, water model, and nitrogen JL Chen, JL Prelesnik, B Liang, Y Sun, M Bhatt, C Knight, K Mahesh, ... The Journal of Chemical Physics 159 (22), 2023 | 4 | 2023 |
| Predicting hydrogen storage in nanoporous materials using meta-learning Y Sun, RF DeJaco, JI Siepmann Machine Learning and the Physical Sciences Workshop, NeurIPS 2019, 2019 | 1 | 2019 |
| Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials Y Sun, JI Siepmann Journal of Chemical Theory and Computation, 2024 | | 2024 |
| Supporting Data for" Development of a PointNet for Detecting Morphologies of Self-Assembled Block Oligomers in Atomistic Simulations" Z Shen, Y Sun, TP Lodge, JI Siepmann | | 2021 |
| Data for Fingerprinting diverse nanoporous materials for optimal hydrogen storage conditions using meta-learning Y Sun, RF DeJaco, Z Li, D Tang, S Glante, DS Sholl, CM Colina, RQ Snurr, ... | | 2021 |
| Predictive Modeling of Adsorption and Transport in Zeolites: From High-Throughput Screening to First Principles Simulations J Siepmann, P Bai, Y Sun, E Fetisov, MS Shah, R DeJaco, T Josephson, ... 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Combining High-Throughput Molecular Simulations and Machine Learning to Optimize Adsorption Processes J Siepmann, Y Sun, T Josephson, R DeJaco 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Interpretable Learning of Complex Multicomponent Adsorption Equilibria from Self-attention Y Sun, TR Josephson, JI Siepmann | | |
