Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning YD Wang, Q Meyer, K Tang, JE McClure, RT White, ST Kelly, ... Nature Communications 14 (1), 745, 2023 | 57 | 2023 |
Generalizable framework of unpaired domain transfer and deep learning for the processing of real-time synchrotron-based x-ray microcomputed tomography images of complex structures K Tang, Y Da Wang, J McClure, C Chen, P Mostaghimi, RT Armstrong Physical Review Applied 17 (3), 034048, 2022 | 20 | 2022 |
Deep learning for full-feature X-ray microcomputed tomography segmentation of proton electron membrane fuel cells K Tang, Q Meyer, R White, RT Armstrong, P Mostaghimi, Y Da Wang, ... Computers & Chemical Engineering 161, 107768, 2022 | 19 | 2022 |
Deep convolutional neural network for 3D mineral identification and liberation analysis Kunning Tang,Ying Da Wang,Peyman Mostaghimi,Mark Knackstedt, Chad Hargrave ... Minerals Engineering 183, 107592, 2022 | 17 | 2022 |
Harnessing the power of water: A review of hydroelectric nanogenerators H Su, A Nilghaz, D Liu, L Dai, J Tian, JM Razal, K Tang, J Li Nano Energy, 108819, 2023 | 12 | 2023 |
Particle classification of iron ore sinter green bed mixtures by 3D X-ray microcomputed tomography and machine learning K Tang, Y Da Wang, Y Niu, TA Honeyands, D O’Dea, P Mostaghimi, ... Powder Technology 415, 118151, 2023 | 10 | 2023 |
A pore-scale model for electrokinetic in situ recovery of copper: the influence of mineral occurrence, zeta potential, and electric potential K Tang, Z Li, Y Da Wang, J McClure, H Su, P Mostaghimi, RT Armstrong Transport in Porous Media 150 (3), 601-626, 2023 | 6 | 2023 |
Dendrite-free zinc deposition enabled by MXene/nylon scaffold and polydopamine solid-electrolyte interphase for flexible zinc-ion batteries Z Wang, P Zhang, J Zhang, K Tang, J Cao, Z Yang, S Qin, JM Razal, ... Energy Storage Materials 67, 103298, 2024 | 5 | 2024 |
Dynamic X-ray micotomography of microfibrous cellulose liquid foams using deep learning SR Muin, PT Spicer, K Tang, Y Niu, M Hosseini, P Mostaghimi, ... Chemical Engineering Science 248, 117173, 2022 | 5 | 2022 |
Multi-scale modelling of multi-physics flow in coal seams Z Lanetc, A Zhuravljov, K Tang, RT Armstrong, P Mostaghimi Gas Science and Engineering 118, 205081, 2023 | 4 | 2023 |
In situ characterization of heterogeneous surface wetting in porous materials Y Da Wang, L Kearney, MJ Blunt, C Sun, K Tang, P Mostaghimi, ... Advances in Colloid and Interface Science, 103122, 2024 | 3 | 2024 |
Efficient energy generation from a sweat-powered, wearable, MXene-based hydroelectric nanogenerator H Su, KAS Usman, A Nilghaz, Y Bu, K Tang, L Dai, D Liu, JM Razal, W Lei, ... Device 2 (5), 2024 | 2 | 2024 |
From Surface to Volume: Deep Learning-Driven 3D Realisation of Super-Large 2D SEM Images for Material Characterisation K Tang, Y Da Wang, M Regaieg, G Borisochev, I Jolivet, R Armstrong, ... Available at SSRN 4939600, 2024 | | 2024 |
Bayesian linear regression with Gaussian mixture likelihood for outlier detection of metal grades in Porphyry Cu deposit Y NIU, M Lindsay, R Scalzo, L Zhang, K Tang Authorea Preprints, 2024 | | 2024 |
Controlled ion transport in the subsurface: A coupled advection–diffusion–electromigration system K Tang, Z Bo, Z Li, Y Da Wang, J McClure, H Su, P Mostaghimi, ... Physics of Fluids 36 (6), 2024 | | 2024 |
Scaling Deep Learning for Material Imaging: A Pseudo-3d Model for Tera-Scale 3d Domain Transfer K Tang, R Armstrong, P Mostaghimi, Y Niu, Q Meyer, C Zhao, D Finegan, ... Available at SSRN 4808378, 2024 | | 2024 |
Insights into hydroelectric nanogenerators: numerical simulation and experimental verification H Su, A Nilghaz, K Tang, D Liu, S Zhao, J Tian, Y Bu, J Li Journal of Materials Chemistry A 12 (36), 24409-24416, 2024 | | 2024 |
Applications of Deep Convolutional Neural Networks for Energy-based Materials Characterization on Digital Images K Tang UNSW Sydney, 2023 | | 2023 |