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Conference Paper

A Novel Machine Learning-Based Optimization Approach for the Molecular Design of Solvents

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Wang,  Zihao
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Zhou,  Teng
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

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Sundmacher,  Kai
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

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Wang, Z., Zhou, T., & Sundmacher, K. (2022). A Novel Machine Learning-Based Optimization Approach for the Molecular Design of Solvents. In 32nd European Symposium on Computer Aided Process Engineering (pp. 1477-1482). Elsevier.


Cite as: https://hdl.handle.net/21.11116/0000-000B-3D56-1
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