| cemff: A force field database for cementitious materials including validations, applications and opportunities RK Mishra, AK Mohamed, D Geissbühler, H Manzano, T Jamil, ... Cement and concrete research 102, 68-89, 2017 | 180 | 2017 |
| Benchmarking Machine Learning Models for Polymer Informatics: An Example of Glass Transition Temperature L Tao, V Varshney, Y Li Journal of Chemical Information and Modeling 61 (11), 5395-5413, 2021 | 84 | 2021 |
| Machine learning enables interpretable discovery of innovative polymers for gas separation membranes J Yang, L Tao, J He, JR McCutcheon, Y Li Science advances 8 (29), eabn9545, 2022 | 76 | 2022 |
| Machine learning discovery of high-temperature polymers L Tao, G Chen, Y Li Patterns 2 (4), 100225, 2021 | 67 | 2021 |
| Predicting Polymers’ Glass Transition Temperature by a Chemical Language Processing Model G Chen, L Tao, Y Li Polymers 13 (11), 1898, 2021 | 49 | 2021 |
| Diffusive, displacive deformations and local phase transformation govern the mechanics of layered crystals: The case study of tobermorite L Tao, R Shahsavari Scientific reports 7 (1), 5907, 2017 | 37 | 2017 |
| Edge dislocations in dicalcium silicates: Experimental observations and atomistic analysis R Shahsavari, L Chen, L Tao Cement and Concrete Research 90, 80-88, 2016 | 32 | 2016 |
| Interlaced, nanostructured interface with graphene buffer layer reduces thermal boundary resistance in nano/microelectronic systems L Tao, S Theruvakkattil Sreenivasan, R Shahsavari ACS applied materials & interfaces 9 (1), 989-998, 2017 | 29 | 2017 |
| Integration of Machine Learning and Coarse-grained Molecular Simulations for Polymer Materials: physical understandings and molecular design DT Nguyen, L Tao, Y Li Frontiers in Chemistry, 1280, 2021 | 28 | 2021 |
| Structure, energetics, and impact of screw dislocations in tricalcium silicates R Shahsavari, L Tao, L Chen Journal of the American Ceramic Society 99 (7), 2512-2520, 2016 | 23 | 2016 |
| Machine Learning Strategies for the Structure-Property Relationship of Copolymers L Tao, J Byrnes, V Varshney, Y Li iScience, 2022 | 20 | 2022 |
| Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning L Tao, J He, NE Munyaneza, V Varshney, W Chen, G Liu, Y Li Chemical Engineering Journal 465, 142949, 2023 | 15 | 2023 |
| Machine learning prediction on the fractional free volume of polymer membranes L Tao, J He, T Arbaugh, JR McCutcheon, Y Li Journal of Membrane Science 665, 121131, 2023 | 14 | 2023 |
| High-Throughput Screening and Prediction of High Modulus of Resilience Polymers Using Explainable Machine Learning T Yue, J He, L Tao, Y Li Journal of Chemical Theory and Computation, 2023 | 3 | 2023 |
| Machine learning-based prediction for single-cell mechanics D Nguyen, L Tao, H Ye, Y Li Mechanics of Materials 180, 104631, 2023 | 3 | 2023 |
| Interfacial modification to anomalously facilitate thermal transport through cathode-separator composite in lithium-ion batteries J He, W Xian, L Tao, P Corrigan, Y Li Applied Surface Science 606, 155010, 2022 | 3 | 2022 |
| Unified machine learning protocol for copolymer structure-property predictions L Tao, T Arbaugh, J Byrnes, V Varshney, Y Li STAR Protocols 3 (4), 101875, 2022 | 3 | 2022 |
| Molecular self-assembled monolayers anomalously enhance thermal conductance across polymer–semiconductor interfaces J He, L Tao, W Xian, T Arbaugh, Y Li Nanoscale 14 (47), 17681-17693, 2022 | 3 | 2022 |
| Mechanistic Data Science for Modeling and Design of Aerospace Composite Materials S Mojumder, L Tao, Y Li, WK Liu arXiv preprint arXiv:2112.00968, 2021 | 2 | 2021 |
| Inverse Hall–Petch effect in nanocrystalline ice predicted by machine-learned coarse-grained molecular simulations G Chen, L Tao, M Kröger, Y Li Journal of Micromechanics and Molecular Physics, 1-10, 2022 | 1 | 2022 |
Ying LiUniversity of Wisconsin-MadisonVerified email at wisc.edu
