| Predicting effective diffusivity of porous media from images by deep learning H Wu, WZ Fang, Q Kang, WQ Tao, R Qiao Scientific reports 9 (1), 20387, 2019 | 131 | 2019 |
| The ionized graphene oxide membranes for water-ethanol separation C Fang, H Wu, SY Lee, RL Mahajan, R Qiao Carbon 136, 262-269, 2018 | 55 | 2018 |
| Phase transitions in three-lane TASEPs with weak coupling YQ Wang, R Jiang, QS Wu, HY Wu Modern Physics Letters B 28 (15), 1450123, 2014 | 39 | 2014 |
| Phase transitions in coupled exclusion processes constituted by TASEP and two-lane SEPs YQ Wang, R Jiang, QS Wu, HY Wu Modern Physics Letters B 28 (08), 1450064, 2014 | 37 | 2014 |
| Recovery of multicomponent shale gas from single nanopores H Wu, Y He, R Qiao Energy & Fuels 31 (8), 7932-7940, 2017 | 36 | 2017 |
| Physics-constrained deep learning for data assimilation of subsurface transport H Wu, R Qiao Energy and AI 3, 100044, 2021 | 22 | 2021 |
| A kinetic model for multicomponent gas transport in shale gas reservoirs and its applications S Wang, Y Zhang, H Wu, SH Lee, R Qiao, XH Wen Physics of Fluids 34 (8), 2022 | 16 | 2022 |
| Drying of porous media by concurrent drainage and evaporation: a pore network modeling study H Wu, C Fang, R Wu, R Qiao International Journal of Heat and Mass Transfer 152, 118718, 2020 | 16 | 2020 |
| Deep learning-based reconstruction of the structure of heterogeneous composites from their temperature fields H Wu, H Zhang, G Hu, R Qiao AIP Advances 10 (4), 2020 | 13 | 2020 |
| Real-space charge density profiling of electrode–electrolyte interfaces with angstrom depth resolution LKS Bonagiri, KS Panse, S Zhou, H Wu, NR Aluru, Y Zhang ACS nano 16 (11), 19594-19604, 2022 | 10 | 2022 |
| Electrical double layers near charged nanorods in mixture electrolytes Z Yu, H Wu, R Qiao The Journal of Physical Chemistry C 121 (17), 9454-9461, 2017 | 8 | 2017 |
| Superdiffusive gas recovery from nanopores H Wu, Y He, R Qiao Physical Review Fluids 1 (7), 074101, 2016 | 8 | 2016 |
| Note: A top-view optical approach for observing the coalescence of liquid drops L Wang, G Zhang, H Wu, J Yang, Y Zhu Review of Scientific Instruments 87 (2), 2016 | 8 | 2016 |
| Innermost Ion Association Configuration Is a Key Structural Descriptor of Ionic Liquids at Electrified Interfaces KS Panse, H Wu, S Zhou, F Zhao, NR Aluru, Y Zhang The Journal of Physical Chemistry Letters 13 (40), 9464-9472, 2022 | 4 | 2022 |
| Deep learning-based quasi-continuum theory for structure of confined fluids H Wu, NR Aluru The Journal of Chemical Physics 157 (8), 2022 | 4 | 2022 |
| Harness the power of atomistic modeling and deep learning in biofuel separation D Zhang, H Wu, B Smith, VA Glezakou Pacific Northwest National Laboratory (PNNL), Richland, WA (United States …, 2023 | | 2023 |
| From ab initio to continuum: Linking multiple scales using deep-learned forces H Wu, C Liang, J Jeong, NR Aluru The Journal of Chemical Physics 159 (18), 2023 | | 2023 |
| Data-Driven Approach to Coarse-Graining Simple Liquids in Confinement I Nadkarni, H Wu, NR Aluru Journal of Chemical Theory and Computation 19 (20), 7358-7370, 2023 | | 2023 |
| Unraveling Spatial Charge Density Distributions at Electrode-Electrolyte Interfaces LKS Bonagiri, KS Panse, S Zhou, H Wu, NR Aluru, Y Zhang Electrochemical Society Meeting Abstracts 243, 2384-2384, 2023 | | 2023 |
| Deep learning based quasi-continuum theory for structural prediction of water and Lennard-Jones fluid in confined environments H Wu, N Aluru, HW Team, NRA Team APS March Meeting Abstracts 2022, A32. 004, 2022 | | 2022 |
Rui Qiao 乔锐Professor of Mechanical Engineering, Virginia TechVerified email at vt.edu
