Machine learning prediction of biochar yield and carbon contents in biochar based on biomass characteristics and pyrolysis conditions X Zhu, Y Li, X Wang Bioresource technology 288, 121527, 2019 | 326 | 2019 |
The application of machine learning methods for prediction of metal sorption onto biochars X Zhu, X Wang, YS Ok Journal of hazardous materials 378, 120727, 2019 | 287 | 2019 |
Machine learning for the selection of carbon-based materials for tetracycline and sulfamethoxazole adsorption X Zhu, Z Wan, DCW Tsang, M He, D Hou, Z Su, J Shang Chemical Engineering Journal 406, 126782, 2021 | 196 | 2021 |
Online prediction of mechanical properties of hot rolled steel plate using machine learning Q Xie, M Suvarna, J Li, X Zhu, J Cai, X Wang Materials & Design 197, 109201, 2021 | 164 | 2021 |
Multi-task prediction and optimization of hydrochar properties from high-moisture municipal solid waste: Application of machine learning on waste-to-resource J Li, X Zhu, Y Li, YW Tong, YS Ok, X Wang Journal of Cleaner Production 278, 123928, 2021 | 155 | 2021 |
Insights into the adsorption of pharmaceuticals and personal care products (PPCPs) on biochar and activated carbon with the aid of machine learning X Zhu, M He, Y Sun, Z Xu, Z Wan, D Hou, DS Alessi, DCW Tsang Journal of Hazardous Materials 423, 127060, 2022 | 148 | 2022 |
Machine learning exploration of the critical factors for CO2 adsorption capacity on porous carbon materials at different pressures X Zhu, DCW Tsang, L Wang, Z Su, D Hou, L Li, J Shang Journal of Cleaner Production 273, 122915, 2020 | 144 | 2020 |
Molecular modeling of interactions between heavy crude oil and the soil organic matter coated quartz surface G Wu, X Zhu, H Ji, D Chen Chemosphere 119, 242-249, 2015 | 96 | 2015 |
Machine learning exploration of the direct and indirect roles of Fe impregnation on Cr (VI) removal by engineered biochar X Zhu, Z Xu, S You, M Komárek, DS Alessi, X Yuan, KN Palansooriya, ... Chemical Engineering Journal 428, 131967, 2022 | 79 | 2022 |
Application of life cycle assessment and machine learning for high-throughput screening of green chemical substitutes X Zhu, CH Ho, X Wang ACS Sustainable Chemistry & Engineering 8 (30), 11141-11151, 2020 | 66 | 2020 |
Molecular dynamic simulation of asphaltene co-aggregation with humic acid during oil spill X Zhu, D Chen, G Wu Chemosphere 138, 412-421, 2015 | 59 | 2015 |
Modeling the adsorption of PAH mixture in silica nanopores by molecular dynamic simulation combined with machine learning H Sui, L Li, X Zhu, D Chen, G Wu Chemosphere 144, 1950-1959, 2016 | 50 | 2016 |
Molten salt shielded pyrolysis of biomass waste: Development of hierarchical biochar, salt recovery, CO2 adsorption X Zhu, M Sun, X Zhu, W Guo, Z Luo, W Cai, X Zhu Fuel 334, 126565, 2023 | 39 | 2023 |
Machine learning-assisted exploration for carbon neutrality potential of municipal sludge recycling via hydrothermal carbonization X Zhu, B Liu, L Sun, R Li, H Deng, X Zhu, DCW Tsang Bioresource Technology 369, 128454, 2023 | 34 | 2023 |
Correlating asphaltene dimerization with its molecular structure by potential of mean force calculation and data mining X Zhu, G Wu, F Coulon, L Wu, D Chen Energy & fuels 32 (5), 5779-5788, 2018 | 30 | 2018 |
Reutilization of biomass pyrolysis waste: Tailoring dual-doped biochar from refining residue of bio-oil through one-step self-assembly X Zhu, Z Luo, W Guo, W Cai, X Zhu Journal of Cleaner Production 343, 131046, 2022 | 28 | 2022 |
Insights into the oil adsorption and cyclodextrin extraction process on rough silica surface by molecular dynamics simulation X Zhu, D Chen, Y Zhang, G Wu The Journal of Physical Chemistry C 122 (5), 2997-3005, 2018 | 28 | 2018 |
Molecular dynamics simulation of cyclodextrin aggregation and extraction of Anthracene from non-aqueous liquid phase X Zhu, G Wu, D Chen Journal of hazardous materials 320, 169-175, 2016 | 24 | 2016 |
Insights into asphaltene aggregation in the Na-montmorillonite interlayer X Zhu, D Chen, G Wu Chemosphere 160, 62-70, 2016 | 20 | 2016 |
Deep learning-assisted automated sewage pipe defect detection for urban water environment management L Sun, J Zhu, J Tan, X Li, R Li, H Deng, X Zhang, B Liu, X Zhu Science of The Total Environment 882, 163562, 2023 | 16 | 2023 |