Publications of Teng Zhou

Qin, H.; Wang, Z.; Song, Z.; Zhang, X.; Zhou, T.: High-Throughput Computational Screening of Ionic Liquids for Butadiene and Butene Separation. Processes 10 (1), 165 (2022)

Wang, Z.; Zhou, Y.; Zhou, T.; Sundmacher, K.: Identification of Optimal Metal-Organic Frameworks by Machine Learning: Structure Decomposition, Feature Integration, and Predictive Modeling. Computers & Chemical Engineering 160, 107739 (2022)

Zhang, X.; Zhou, T.; Sundmacher, K.: Integrated metal–organic framework and pressure/vacuum swing adsorption process design: Descriptor optimization. AIChE Journal 68 (2), e17524 (2022)

Zhang, X.; Zhou, T.; Sundmacher, K.: Integrated metal‐organic framework (MOF) and pressure/vacuum swing adsorption process design:MOFmatching. AIChE Journal 68 (9), e17788 (2022)

Zhou, Y.; Zhang, X.; Zhou, T.; Sundmacher, K.: Computational Screening of Metal-Organic Frameworks for Ethylene Purification from Ethane/Ethylene/Acetylene Mixture. Nanomaterials 12 (5), 869 (2022)

Shi, H.; Zhang, X.; Sundmacher, K.; Zhou, T.: Model-Based Optimal Design of Phase Change Ionic Liquids for Efficient Thermal Energy Storage. Green Energy & Environment 6 (3), pp. 392 - 404 (2021)

Shi, H.; Zhou, T.: Computational design of heterogeneous catalysts and gas separation materials for advanced chemical processing. Frontiers of Chemical Science and Engineering 15, pp. 49 - 59 (2021)

Wang, Z.; Song, Z.; Zhou, T.: Machine Learning for Ionic Liquid Toxicity Prediction. Processes 9 (1), 65 (2021)

Zhang, X.; Ding, X.; Song, Z.; Zhou, T.; Sundmacher, K.: Integrated Ionic Liquid and Rate‐Based Absorption Process Design for Gas Separation: Global Optimization Using Hybrid Models. AIChE Journal 67 (10), 17340 (2021)

Zhou, T.; Gani, R.; Sundmacher, K.: Hybrid data-driven and mechanistic modeling approaches for multiscale material and process design. Engineering 7 (9), pp. 1231 - 1238 (2021)

Zhang, C.; Song, Z.; Jin, C.; Nijhuis, J.; Zhou, T.; Noël, T.; Gröger, H.; Sundmacher, K.; van Hest, J.; Hessel, V.: Screening of functional solvent system for automatic aldehyde and ketone separation in aldol reaction: A combined COSMO-RS and experimental approach. Chemical Engineering Journal 385, 123399 (2020)

Zhang, X.; Song, Z.; Gani, R.; Zhou, T.: Comparative Economic Analysis of Physical, Chemical, and Hybrid Absorption Processes for Carbon Capture. Industrial & Engineering Chemistry Research 59, pp. 2005 - 2012 (2020)

Zhou, T.; McBride, K.; Linke, S.; Song, Z.; Sundmacher, K.: Computer-aided solvent selection and design for efficient chemical processes. Current Opinion in Chemical Engineering 27, pp. 35 - 44 (2020)

Song, Z.; Zhou, Y.; Zhou, T.; Qi, Z.; Sundmacher, K.: Rational design of double salt ionic liquids as extraction solvents: Separation of thiophene/n‐octane as example. AIChE-Journal 65 (8), e16625 (2019)

Zhou, T.; Song, Z.; Sundmacher, K.: Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design. Engineering 5 (6), pp. 1017 - 1026 (2019)

Zhou, T.; Song, Z.; Zheng, X.; Gani, R.; Sundmacher, K.: Optimal Solvent Design for Extractive Distillation Processes: A Multiobjective Optimization-Based Hierarchical Framework. Industrial and Engineering Chemistry Research 58 (15), pp. 5777 - 5786 (2019)

Zhang, X.; Song, Z.; Zhou, T.: Rigorous design of reaction-separation processes using disjunctive programming models. Computers and Chemical Engineering 111, pp. 16 - 26 (2018)

Zhou, T.; Jhamb, S.; Liang, X.; Sundmacher, K.; Gani, R.: Prediction of acid dissociation constants of organic compounds using group contribution methods. Chemical Engineering Science 183, pp. 95 - 105 (2018)

Zhou, T.; Zhou, Y.; Sundmacher, K.: A hybrid stochastic-deterministic optimization approach for integrated solvent and process design. Chemical Engineering Science 159, pp. 207 - 2016 (2017)