Process Systems Engineering (PSE): Synthesis and analysis of chemical, biological and energy conversion systems from the molecular up to the plant scale

Magdeburg, Germany
Joined June 2020
Representing the PSE group at #AIChE! Great discussions, inspiring talks, and lots of progress in #ChemicalEngineering. Excited to bring back new ideas! 🌍🔬
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Congratulations to our PhD student, Zihao Wang, who has been granted the "2023 Chinese Government Award for Outstanding Self-financed Student Abroad" by the China Scholarship Council, in recognition of his academic excellence during his PhD studies.
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Unser Doktorand der PSE-Gruppe Alexander Klimek erhielt den VDI-Förderpreis für seine Masterarbeit bezüglich des optimalen Designs und Betriebes nachhaltiger Ammoniakanlagen und der Identifizierung maßgeblicher technischer und wirtschaftlicher Einflussfaktoren. Gratulation!
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New paper out: 'Challenges in data-based reactor modeling: A critical analysis of purely data-driven and hybrid models for a CSTR case study'. Surprisingly, hybrid models didn't always outperform purely data-driven models. Curious? Check it out here: doi.org/10.1016/j.compchemen…
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Complex, Simplicius, Simplicissimus. This is the path we have followed in our new exploratory study into the design of “simple” Power-to-Methanol processes to help streamline their deployment across locations with different renewable energy conditions authors.elsevier.com/sd/arti…
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Big congrats to our doctoral researchers! 🌟 Alexander Klimek named Best Overall Master's Graduate by the Faculty of Process and Systems Engineering, and Christoph Griehl awarded Best Master's Graduate in Process Engineering by @Dow_de. 🏆 Both studied at @OVGUpresse.
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🎉 Check out our new article on using GNNs for predicting activity coefficients of #Polymer solutions. Available code and data on GitHub! doi.org/10.1021/acs.jpca.3c0… 🧪🔍 #MachineLearning #GNNs #OpenAccess
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Multi-objective superstructure optimization at its best: We designed an optimal biorefinery considering sustainability and economy for the wet extraction of EPA, laminarin and fucoxanthin from Phaeodactylum tricornutum.  Read more here: doi.org/10.1002/bbb.2540
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♻️ Chemical recycling of Nylon 6 In our new paper, we provide the first comprehensive overview and techno-economic comparison of the chemical recycling pathways of Nylon 6 to its monomer caprolactam. 🔓 Open access paper in @Chem_Eng_J: doi.org/10.1016/j.cej.2023.1…
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How to extend the flexibility of a power-to-X process by different buffering strategies? Read our brand new article in @chemengsci: sciencedirect.com/science/ar…
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A scalable and integrated machine learning framework for molecular property prediction! Enjoy our new article published in the AIChE Journal: aiche.onlinelibrary.wiley.co…
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Congratulations to Karsten Rätze for his very successful doctoral examination @OVGUpresse. Outstanding contributions to computer-aided model development, process design and dynamic operating strategies for multiphase reaction systems.
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Many thanks go to Christof Hamel, Sebastian Engell, and Michael Doherty for serving in the examination committee.
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Exciting results on data-driven integrated design of solvents and extractive distillation processes just published in the AIChE Journal. Check out more details here:  aiche.onlinelibrary.wiley.co…
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Extending the UNIFAC models for discovering novel eutectic solvents. Enjoy reading our recent article in Chemical Engineering Science: sciencedirect.com/science/ar…
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We are excited about the start of our new @ DFG funded Research Unit FOR 5538: Integrated Molecular, Material and Process Design for the Production of Fine Chemicals. Read more in German here: idw-online.de/de/news818846
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Mit Algen statt Erdöl und mit Kreislauf-Energie statt fossilen Brennstoffen: Nele Eckhardt und Johannes Kopton haben VDI-Preise für ihre ausgezeichneten Masterarbeiten erhalten. Dabei wurden sie von der PSE-Gruppe sehr gut betreut. Gratulation an unsere AbsolventInnen!
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📢 GNNs + simple thermodynamics Check out our work on predicting limiting activity coefficients with the Gibbs-Helmholtz Graph Neural Network (GH-GNN)! 🌡️🔬 🚀Transfer learning for accurate predictions doi.org/10.1039/D2DD00142J 🔓🔗Open-source model! #MachineLearning #ChemEng
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