| Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics W Ji, W Qiu, Z Shi, S Pan, S Deng The Journal of Physical Chemistry A 125 (36), 8098–8106, 2021 | 165 | 2021 |
| Stiff neural ordinary differential equations S Kim, W Ji, S Deng, Y Ma, C Rackauckas Chaos: An Interdisciplinary Journal of Nonlinear Science 31, 2021 | 128 | 2021 |
| Machine learning for combustion L Zhou, Y Song, W Ji, H Wei Energy and AI 7, 100128, 2022 | 116 | 2022 |
| First-stage ignition delay in the negative temperature coefficient behavior: Experiment and simulation P Zhang, W Ji, T He, X He, Z Wang, B Yang, CK Law Combustion and Flame 167, 14-23, 2016 | 101 | 2016 |
| Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network W Ji, S Deng The Journal of Physical Chemistry A 125 (4), 1082–1092, 2021 | 98 | 2021 |
| Machine learning model to project the impact of COVID-19 on US motor gasoline demand S Ou, X He, W Ji, W Chen, L Sui, Y Gan, Z Lu, Z Lin, S Deng, ... Nature Energy 5 (9), 666-673, 2020 | 82 | 2020 |
| Ignition delay measurements of light naphtha: A fully blended low octane fuel T Javed, EF Nasir, A Ahmed, J Badra, K Djebbi, M Beshir, W Ji, ... Proceedings of the Combustion Institute 36 (1), 315-322, 2017 | 60 | 2017 |
| Shared low-dimensional subspaces for propagating kinetic uncertainty to multiple outputs W Ji, J Wang, O Zahm, YM Marzouk, B Yang, Z Ren, CK Law Combustion and Flame 190, 146-157, 2018 | 55 | 2018 |
| Quantifying kinetic uncertainty in turbulent combustion simulations using active subspaces W Ji, Z Ren, Y Marzouk, CK Law Proceedings of the Combustion Institute 37 (2), 2175-2182, 2019 | 53 | 2019 |
| Evolution of sensitivity directions during autoignition W Ji, Z Ren, CK Law Proceedings of the Combustion Institute 37 (1), 807-815, 2019 | 50 | 2019 |
| On the controlling mechanism of the upper turnover states in the NTC regime W Ji, P Zhao, T He, X He, A Farooq, CK Law Combustion and Flame 164, 294-302, 2016 | 49 | 2016 |
| Autonomous Kinetic Modeling of Biomass Pyrolysis using Chemical Reaction Neural Networks W Ji, F Richter, MJ Gollner, S Deng Combustion and Flame 240, 2022 | 45 | 2022 |
| Intermediate species measurement during iso-butanol auto-ignition W Ji, P Zhang, T He, Z Wang, L Tao, X He, CK Law Combustion and Flame 162 (10), 3541-3553, 2015 | 43 | 2015 |
| On the crossover temperature and lower turnover state in the NTC regime W Ji, P Zhao, P Zhang, Z Ren, X He, CK Law Proceedings of the Combustion Institute 36 (1), 343-353, 2017 | 35 | 2017 |
| Measurement of reaction rate constants using RCM: A case study of decomposition of dimethyl carbonate to dimethyl ether P Zhang, S Li, Y Wang, W Ji, W Sun, B Yang, X He, Z Wang, CK Law, ... Combustion and Flame 183, 30-38, 2017 | 26 | 2017 |
| KiNet: A deep neural network representation of chemical kinetics W Ji, S Deng arXiv preprint arXiv:2108.00455, 2021 | 14 | 2021 |
| Uncertainty analysis in mechanism reduction via active subspace and transition state analyses X Su, W Ji, Z Ren Combustion and Flame 227, 135-146, 2021 | 13 | 2021 |
| Dependence of kinetic sensitivity direction in premixed flames W Ji, T Yang, Z Ren, S Deng Combustion and Flame 220, 16-22, 2020 | 10 | 2020 |
| SGD-based optimization in modeling combustion kinetics: Case studies in tuning mechanistic and hybrid kinetic models W Ji, X Su, B Pang, Y Li, Z Ren, S Deng Fuel 324, 124560, 2022 | 9 | 2022 |
| Arrhenius. jl: A Differentiable Combustion Simulation Package W Ji, X Su, B Pang, SJ Cassady, AM Ferris, Y Li, Z Ren, R Hanson, ... arXiv preprint arXiv:2107.06172, 2021 | 9 | 2021 |
Sili DengAssistant Professor at Massachusetts Institute of Technology在 mit.edu 的电子邮件经过验证
