| Microstructure generation via generative adversarial network for heterogeneous, topologically complex 3D materials T Hsu, WK Epting, H Kim, HW Abernathy, GA Hackett, AD Rollett, ... Jom 73, 90-102, 2021 | 105 | 2021 |
| Mesoscale characterization of local property distributions in heterogeneous electrodes T Hsu, WK Epting, R Mahbub, NT Nuhfer, S Bhattacharya, Y Lei, ... Journal of Power Sources 386, 1-9, 2018 | 51 | 2018 |
| Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach TW Heo, A Grieder, B Wang, M Wood, T Hsu, SA Akhade, LF Wan, ... npj Computational Materials 7 (1), 214, 2021 | 47 | 2021 |
| An efficient approach for prediction of Warburg-type resistance under working currents T Yang, J Liu, H Finklea, S Lee, WK Epting, R Mahbub, T Hsu, ... International Journal of Hydrogen Energy 43 (32), 15445-15456, 2018 | 34 | 2018 |
| A method for quantitative 3D mesoscale analysis of solid oxide fuel cell microstructures using Xe-plasma focused ion beam (PFIB) coupled with SEM R Mahbub, T Hsu, WK Epting, NT Nuhfer, GA Hackett, H Abernathy, ... ECS Transactions 78 (1), 2159, 2017 | 23 | 2017 |
| Efficient and interpretable graph network representation for angle-dependent properties applied to optical spectroscopy T Hsu, TA Pham, N Keilbart, S Weitzner, J Chapman, P Xiao, SR Qiu, ... npj Computational Materials 8 (1), 151, 2022 | 22 | 2022 |
| Distributions of local electrochemistry in heterogeneous microstructures of solid oxide fuel cells using high-performance computations T Hsu, JH Mason, R Mahbub, WK Epting, HW Abernathy, GA Hackett, ... Electrochimica Acta 345, 136191, 2020 | 18 | 2020 |
| Quantitative analysis of multi-scale heterogeneities in complex electrode microstructures R Mahbub, WK Epting, T Hsu, JH Mason, M Feng, NT Nuhfer, ... Journal of The Electrochemical Society 167 (5), 054506, 2019 | 17 | 2019 |
| Towards quantification of local electrochemical parameters in microstructures of solid oxide fuel cell electrodes using high performance computations T Hsu, R Mahbub, WK Epting, H Abernathy, GA Hackett, AD Rollett, ... ECS Transactions 78 (1), 2711, 2017 | 16 | 2017 |
| Quantifying morphological variability and operating evolution in SOFC anode microstructures R Mahbub, T Hsu, WK Epting, G Nolan, Y Lei, NT Nuhfer, RB Doane, ... Journal of Power Sources 498, 229846, 2021 | 15 | 2021 |
| Harnessing neural networks for elucidating x-ray absorption structure–spectrum relationships in amorphous carbon H Kwon, W Sun, T Hsu, W Jeong, F Aydin, S Sharma, F Meng, ... The Journal of Physical Chemistry C 127 (33), 16473-16484, 2023 | 13 | 2023 |
| Quantifying disorder one atom at a time using an interpretable graph neural network paradigm J Chapman, T Hsu, X Chen, TW Heo, BC Wood Nature Communications 14 (1), 4030, 2023 | 13 | 2023 |
| Metal dissolution from first principles: Potential-dependent kinetics and charge transfer S Sharma, A Zagalskaya, SE Weitzner, L Eggart, S Cho, T Hsu, X Chen, ... Electrochimica Acta 437, 141443, 2023 | 13 | 2023 |
| High performance finite element simulations of infiltrated solid oxide fuel cell cathode microstructures T Hsu, H Kim, JH Mason, R Mahbub, WK Epting, HW Abernathy, ... Journal of Power Sources 541, 231652, 2022 | 13 | 2022 |
| High performance modeling of heterogeneous SOFC electrode microstructures using the MOOSE framework: ERMINE (Electrochemical Reactions in MIcrostructural NEtworks) T Hsu, R Mahbub, JH Mason, WK Epting, HW Abernathy, GA Hackett, ... MethodsX 7, 100822, 2020 | 13 | 2020 |
| Score dynamics: Scaling molecular dynamics with picoseconds time steps via conditional diffusion model T Hsu, B Sadigh, V Bulatov, F Zhou Journal of Chemical Theory and Computation 20 (6), 2335-2348, 2024 | 11 | 2024 |
| Challenges and approaches to privacy preserving post-click conversion prediction C O'Brien, A Thiagarajan, S Das, R Barreto, C Verma, T Hsu, J Neufield, ... arXiv preprint arXiv:2201.12666, 2022 | 11 | 2022 |
| Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models H Kwon, T Hsu, W Sun, W Jeong, F Aydin, J Chapman, X Chen, V Lordi, ... Machine Learning: Science and Technology 5 (4), 045037, 2024 | 6 | 2024 |
| Score-based denoising for atomic structure identification T Hsu, B Sadigh, N Bertin, CW Park, J Chapman, V Bulatov, F Zhou npj Computational Materials 10 (1), 155, 2024 | 5 | 2024 |
| Universal and interpretable classification of atomistic structural transitions via unsupervised graph learning B Aroboto, S Chen, T Hsu, BC Wood, Y Jiao, J Chapman Applied Physics Letters 123 (9), 2023 | 3 | 2023 |
