| Neural recommender system for the activity coefficient prediction and UNIFAC model extension of ionic liquid‐solute systems G Chen, Z Song, Z Qi, K Sundmacher AIChE Journal 67 (4), e17171, 2021 | 59 | 2021 |
| Transformer-convolutional neural network for surface charge density profile prediction: Enabling high-throughput solvent screening with COSMO-SAC G Chen, Z Song, Z Qi Chemical Engineering Science 246, 117002, 2021 | 37 | 2021 |
| Systematic screening of bifunctional ionic liquid for intensifying esterification of methyl heptanoate in the reactive extraction process R Wang, G Chen, H Qin, H Cheng, L Chen, Z Qi Chemical Engineering Science 246, 116888, 2021 | 26 | 2021 |
| Computer-aided molecular design of ionic liquids as advanced process media: a review from fundamentals to applications Z Song, J Chen, J Cheng, G Chen, Z Qi Chemical Reviews 124 (2), 248-317, 2023 | 18 | 2023 |
| Generalizing property prediction of ionic liquids from limited labeled data: a one-stop framework empowered by transfer learning G Chen, Z Song, Z Qi, K Sundmacher Digital Discovery 2 (3), 591-601, 2023 | 16 | 2023 |
| Prediction of infinite‐dilution activity coefficients with neural collaborative filtering T Tan, H Cheng, G Chen, Z Song, Z Qi AIChE Journal 68 (9), e17789, 2022 | 16 | 2022 |
| A scalable and integrated machine learning framework for molecular properties prediction G Chen, Z Song, Z Qi, K Sundmacher AIChE Journal 69 (10), e18185, 2023 | 4 | 2023 |
| Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models X Chen, G Chen, K Xie, J Cheng, J Chen, Z Song, Z Qi Green Chemical Engineering, 2024 | 2 | 2024 |
| A Transformer-Convolutional Neural Network Based Framework for Predicting Ionic Liquid Properties G Chen, Z Song, Z Qi Authorea Preprints, 2022 | 1 | 2022 |
| A large extension of the modified UNIFAC model for IL–solute systems by combining hybrid activity coefficient databases R Gu, J Chen, J Cheng, G Chen, T Zhou, Z Qi, YA Zhu, Z Song Separation and Purification Technology 355, 129665, 2025 | | 2025 |
| A critical methodological revisit on group-contribution based property prediction of ionic liquids with machine learning P Cao, J Chen, G Chen, Z Qi, Z Song Chemical Engineering Science 298, 120395, 2024 | | 2024 |
| A critical discussion on developing molecular property prediction models: density of ionic liquids as example J CHEN, X YANG, G CHEN, Z SONG, Z QI CIESC Journal 74 (2), 630, 2023 | | 2023 |
| Machine learning boosted eutectic solvent design for CO2 capture with experimental validation X Liu, J Chen, Y Qiu, K Xie, J Cheng, X You, G Chen, Z Song, Z Qi AIChE Journal, e18631, 0 | | |
Kai SundmacherProfessor of Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical在 mpi-magdeburg.mpg.de 的电子邮件经过验证
