Multiscale modeling of the effects of nanoscale load transfer on the effective elastic properties of unfunctionalized carbon nanotube–polyethylene nanocomposites Y Li, GD Seidel Modelling and Simulation in Materials Science and Engineering 22 (2), 025023, 2014 | 78 | 2014 |
Multiscale modeling of the interface effects in CNT-epoxy nanocomposites Y Li, GD Seidel Computational Materials Science 153, 363-381, 2018 | 62 | 2018 |
Multiscale modeling of functionalized interface effects on the effective elastic material properties of CNT–polyethylene nanocomposites Y Li, GD Seidel Computational Materials Science 107, 216-234, 2015 | 47 | 2015 |
Effective design space exploration of gradient nanostructured materials using active learning based surrogate models X Chen, H Zhou, Y Li Materials & Design 183, 108085, 2019 | 32 | 2019 |
Microscale modeling of creep deformation and rupture in Nickel-based superalloy IN 617 at high temperature VT Phan, X Zhang, Y Li, C Oskay Mechanics of Materials 114, 215-227, 2017 | 32 | 2017 |
Uncertainty quantification of artificial neural network based machine learning potentials Y Li, W Xiao, P Wang ASME International Mechanical Engineering Congress and Exposition 52170 …, 2018 | 26 | 2018 |
Physics-informed machine learning assisted uncertainty quantification for the corrosion of dissimilar material joints P Bansal, Z Zheng, C Shao, J Li, M Banu, BE Carlson, Y Li Reliability Engineering & System Safety 227, 108711, 2022 | 21 | 2022 |
Reliable machine learning potentials based on artificial neural network for graphene A Singh, Y Li Computational Materials Science 227, 112272, 2023 | 13 | 2023 |
Numerical modeling on the delamination-induced capacity degradation of silicon anode Z Zheng, Z Liu, P Wang, Y Li Journal of Energy Storage 43, 103190, 2021 | 13 | 2021 |
Atomic Edge-Guided Polyethylene Crystallization on Monolayer Two-Dimensional Materials D Zhou, M Fuentes-Cabrera, A Singh, RR Unocic, JMY Carrillo, K Xiao, ... Macromolecules 55 (2), 559-567, 2022 | 10 | 2022 |
Numerical study on mechanisms of soy protein as a functional modifier for polymer materials Z Zheng, C Xin, Y Li Modelling and Simulation in Materials Science and Engineering 27 (8), 085010, 2019 | 10 | 2019 |
Uncertainty quantification of atomistic materials simulation with machine learning potentials Y Li, P Wang, W Xiao 2018 AIAA Non-Deterministic Approaches Conference, 2166, 2018 | 10 | 2018 |
Analysis of the interface in CNT-polyethylene nanocomposites using a multiscale modeling method Y Li, G Seidel 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials …, 2012 | 10 | 2012 |
A smart coating with integrated physical antimicrobial and strain-mapping functionalities for orthopedic implants Y Zhang, J Cui, KY Chen, SH Kuo, J Sharma, R Bhatta, Z Liu, A Ellis-Mohr, ... Science Advances 9 (18), eadg7397, 2023 | 9 | 2023 |
Corrosion of Al-Fe self-pierce riveting joints with multiphysics-based modeling and experiments P Bansal, Z Zheng, B Pan, Y Meng, W Wen, M Banu, J Li, BE Carlson, ... Journal of Manufacturing Processes 95, 434-445, 2023 | 8 | 2023 |
Machine learning assisted design for active cathode materials S Yong, Z Zheng, P Wang, Y Li ASME International Mechanical Engineering Congress and Exposition 84508 …, 2020 | 8 | 2020 |
Development of artificial neural network potential for graphene A Singh, X Chen, Y Li, S Koric, E Guleryuz AIAA Scitech 2020 Forum, 1861, 2020 | 8 | 2020 |
Adaptive machine learning with physics-based simulations for mean time to failure prediction of engineering systems H Wu, Y Xu, Z Liu, Y Li, P Wang Reliability Engineering & System Safety 240, 109553, 2023 | 7 | 2023 |
Life cycle assessment of hydrometallurgical recycling for cathode active materials Z Liu, JG Sederholm, KW Lan, EJ Cho, MJ Dipto, Y Gurumukhi, KF Rabbi, ... Journal of Power Sources 580, 233345, 2023 | 7 | 2023 |
Uncertainty Quantification on Galvanic Corrosion Based on Adaptive Surrogate Modeling P Bansal, Z Zheng, Y Li ASME International Mechanical Engineering Congress and Exposition 86717 …, 2022 | 7 | 2022 |