| An architecture of deep learning in QSPR modeling for the prediction of critical properties using molecular signatures Y Su, Z Wang, S Jin, W Shen, J Ren, MR Eden AIChE Journal 65 (9), e16678, 2019 | 84 | 2019 |
| Predictive deep learning models for environmental properties: the direct calculation of octanol–water partition coefficients from molecular graphs Z Wang, Y Su, W Shen, S Jin, JH Clark, J Ren, X Zhang Green Chemistry 21 (16), 4555-4565, 2019 | 71 | 2019 |
| A novel unambiguous strategy of molecular feature extraction in machine learning assisted predictive models for environmental properties Z Wang, Y Su, S Jin, W Shen, J Ren, X Zhang, JH Clark Green Chemistry 22 (12), 3867-3876, 2020 | 34 | 2020 |
| Machine learning for ionic liquid toxicity prediction Z Wang, Z Song, T Zhou Processes 9 (1), 65, 2020 | 32 | 2020 |
| A systematic modeling methodology of deep neural network‐based structure‐property relationship for rapid and reliable prediction on flashpoints H Wen, Y Su, Z Wang, S Jin, J Ren, W Shen, M Eden AIChE Journal 68 (1), e17402, 2022 | 31 | 2022 |
| Interpretable machine learning for accelerating the discovery of metal-organic frameworks for ethane/ethylene separation Z Wang, T Zhou, K Sundmacher Chemical Engineering Journal 444, 136651, 2022 | 30 | 2022 |
| Insights into ensemble learning-based data-driven model for safety-related property of chemical substances Z Wang, H Wen, Y Su, W Shen, J Ren, Y Ma, J Li Chemical Engineering Science 248, 117219, 2022 | 21 | 2022 |
| Energy Applications of Ionic Liquids: Recent Developments and Future Prospects T Zhou, C Gui, L Sun, Y Hu, H Lyu, Z Wang, Z Song, G Yu Chemical Reviews 123 (21), 12170-12253, 2023 | 16 | 2023 |
| Identification of optimal metal-organic frameworks by machine learning: Structure decomposition, feature integration, and predictive modeling Z Wang, Y Zhou, T Zhou, K Sundmacher Computers & Chemical Engineering 160, 107739, 2022 | 16 | 2022 |
| Comprehensive Evaluation of COSMO-RS for Predicting Ternary and Binary Ionic Liquid-Containing Vapor–Liquid Equilibria H Qin, Z Wang, T Zhou, Z Song Industrial & Engineering Chemistry Research 60 (48), 17761-17777, 2021 | 14 | 2021 |
| A multi-task deep learning neural network for predicting flammability-related properties from molecular structures A Yang, Y Su, Z Wang, S Jin, J Ren, X Zhang, W Shen, JH Clark Green Chemistry 23 (12), 4451-4465, 2021 | 10 | 2021 |
| A neural recommender system for efficient adsorbent screening X Zhang, S Sethi, Z Wang, T Zhou, Z Qi, K Sundmacher Chemical Engineering Science 259, 117801, 2022 | 5 | 2022 |
| High-Throughput Computational Screening of Ionic Liquids for Butadiene and Butene Separation H Qin, Z Wang, Z Song, X Zhang, T Zhou Processes 10 (1), 165, 2022 | 3 | 2022 |
| Data‐driven integrated design of solvents and extractive distillation processes Z Wang, T Zhou, K Sundmacher AIChE Journal 69 (12), e18236, 2023 | | 2023 |
| Molecular Property Targeting for Optimal Solvent Design in Extractive Distillation Processes Z Wang, T Zhou, K Sundmacher Computer Aided Chemical Engineering 52, 1247-1252, 2023 | | 2023 |
| A Novel Machine Learning-Based Optimization Approach for the Molecular Design of Solvents Z Wang, T Zhou, K Sundmacher Computer Aided Chemical Engineering 51, 1477-1482, 2022 | | 2022 |
| A New Machine Learning Framework for Efficient MOF Discovery: Application to Hydrogen Storage T Zhou, Z Wang, K Sundmacher Computer Aided Chemical Engineering 49, 1807-1812, 2022 | | 2022 |
Teng ZhouThe Hong Kong University of Science and Technology (Guangzhou)Dirección de correo verificada de mpi-magdeburg.mpg.de
