| Artificial intelligence and machine learning in design of mechanical materials K Guo, Z Yang, CH Yu, MJ Buehler Materials Horizons 8 (4), 1153-1172, 2021 | 450 | 2021 |
| End-to-end deep learning method to predict complete strain and stress tensors for complex hierarchical composite microstructures Z Yang, CH Yu, K Guo, MJ Buehler Journal of the Mechanics and Physics of Solids 154, 104506, 2021 | 105 | 2021 |
| Failure progression in the solid electrolyte interphase (SEI) on silicon electrodes K Guo, R Kumar, X Xiao, BW Sheldon, H Gao Nano Energy 68, 104257, 2020 | 102 | 2020 |
| A semi-supervised approach to architected materials design using graph neural networks K Guo, MJ Buehler Extreme Mechanics Letters 41, 101029, 2020 | 73 | 2020 |
| Stress evolution in lithium metal electrodes JH Cho, X Xiao, K Guo, Y Liu, H Gao, BW Sheldon Energy Storage Materials 24, 281-290, 2020 | 49 | 2020 |
| Wrinkling and ratcheting of a thin film on cyclically deforming plastic substrate: Mechanical instability of the solid-electrolyte interphase in Li–ion batteries Y Liu, K Guo, C Wang, H Gao Journal of the Mechanics and Physics of Solids 123, 103-118, 2019 | 47 | 2019 |
| End-to-end deep learning model to predict and design secondary structure content of structural proteins CH Yu, W Chen, YH Chiang, K Guo, Z Martin Moldes, DL Kaplan, ... ACS biomaterials science & engineering 8 (3), 1156-1165, 2022 | 38 | 2022 |
| Deformation and chemomechanical degradation at solid electrolyte–electrode interfaces X Su, K Guo, T Ma, PA Tamirisa, H Ye, H Gao, BW Sheldon ACS Energy Letters 2 (8), 1729-1733, 2017 | 33 | 2017 |
| Rapid prediction of protein natural frequencies using graph neural networks K Guo, MJ Buehler Digital Discovery 1, 277-285, 2022 | 25 | 2022 |
| Concentration dependent properties and plastic deformation facilitate instability of the solid-electrolyte interphase in Li-ion batteries Y Liu, K Guo, C Wang, J Han, H Gao International Journal of Solids and Structures 198, 99-109, 2020 | 23 | 2020 |
| Optimum particle size in silicon electrodes dictated by chemomechanical deformation of the SEI MY Jin, K Guo, X Xiao, MW Verbrugge, H Gao, BW Sheldon Advanced Functional Materials 31 (19), 2010640, 2021 | 19 | 2021 |
| In situ three-dimensional spider web construction and mechanics I Su, N Narayanan, MA Logrono, K Guo, A Bisshop, R Mühlethaler, ... Proceedings of the National Academy of Sciences 118 (33), e2101296118, 2021 | 18 | 2021 |
| Nature’s way: hierarchical strengthening through weakness K Guo, MJ Buehler Matter 1 (2), 302-303, 2019 | 18 | 2019 |
| Pop-up delamination of electrodes in solid-state batteries K Guo, PA Tamirisa, BW Sheldon, X Xiao, H Gao Journal of the Electrochemical Society 165 (3), A618, 2018 | 18 | 2018 |
| Concentration dependent properties lead to plastic ratcheting in thin island electrodes on substrate under cyclic charging and discharging K Guo, W Zhang, BW Sheldon, H Gao Acta Materialia 164, 261-271, 2019 | 16 | 2019 |
| Biomimicry for natural and synthetic composites and use of machine learning in hierarchical design M Milazzo, F Libonati, S Zhou, K Guo, MJ Buehler Biomimicry for Materials, Design and Habitats, 141-182, 2022 | 5 | 2022 |
| Tuning crack-inclusion interaction with an applied T-stress K Guo*, B Ni*, (equal contribution), H Gao International Journal of Fracture 222, 13–23, 2020 | 5 | 2020 |
| Energy release rate for steady-state fiber debonding in structural battery composites K Guo, N Sridhar, CC Foo, BM Srinivasan Composites Science and Technology 247, 110416, 2024 | 3 | 2024 |
| Multiphysics modelling of structural battery composites CC Foo, K Guo, BM Srinivasan, N Sridhar, K Joshi, Z Su, G Zhang, ... Composites Science and Technology 242, 110178, 2023 | 1 | 2023 |
| Protein structure prediction using machine learning PY Chen, S Huo, T Ma, L Wu, K Guo, F Rigoldi, B Marelli, MJ Buehler US Patent App. 17/842,839, 2023 | | 2023 |
Markus J. BuehlerMassachusetts Institute of TechnologyMIT.EDU의 이메일 확인됨