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Journal Article

Machine learning-supported solvent design for lignin-first biorefineries and lignin upgrading

MPS-Authors
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König-Mattern,  Laura
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Sanchez Medina,  Edgar Ivan
International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

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Linke,  Steffen
International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Rihko-Struckmann,  Liisa
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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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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Citation

König-Mattern, L., Sanchez Medina, E. I., Komarova, A. O., Linke, S., Rihko-Struckmann, L., Luterbacher, J. S., et al. (2024). Machine learning-supported solvent design for lignin-first biorefineries and lignin upgrading. Chemical Engineering Journal, 495: 153524. doi:10.1016/j.cej.2024.153524.


Cite as: https://hdl.handle.net/21.11116/0000-000F-B124-0
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