Integration of Computational Chemistry and Artificial Intelligence for Multi-scale Modeling of Bioprocesses

Nima Nazemzadeh, Laura Wind Sillesen, Rasmus Fjordbak Nielsen, Mark Nicholas Jones, Krist V. Gernaey, Martin Andersson, Seyed Soheil Mansouri*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Bio-based manufacturing is playing an increasingly important role. Flocculation is an important step in bio-manufacturing, and in water, wastewater treatment and the food industry. Flocculation is a multi-scale process with phenomena that span from the nanoscale all the way beyond the microscale. The control and monitoring of such a process is a difficult task due to the lack of knowledge towards modeling the process across the scales. The intention of this work is to develop a hybrid systematic model-based framework, which integrates the computational methods in chemistry and stochastic modeling approaches for monitoring and control of the flocculation process above microscale. The framework therefore utilizes a hybrid model structure. Since industry resorts to either manual control or no control at all for flocculation, it is aimed to reduce the time required for manual control and to avoid unnecessary product losses and unwanted process variations during the operation.
Original languageEnglish
Title of host publicationProceedings of the 30th European Symposium on Computer Aided Process Engineering (ESCAPE30)
EditorsSauro Pierucci, Flavio Manenti, Giulia Bozzano, Davide Manca
PublisherElsevier
Publication date2020
Pages295-300
ISBN (Electronic)9780128233771
DOIs
Publication statusPublished - 2020
Event 30th European Symposium on Computer Aided Process Engineering (ESCAPE 30) - Virtual symposium, Milano, Italy
Duration: 31 Aug 20202 Sept 2020

Conference

Conference 30th European Symposium on Computer Aided Process Engineering (ESCAPE 30)
LocationVirtual symposium
Country/TerritoryItaly
CityMilano
Period31/08/202002/09/2020

Keywords

  • Flocculation
  • Hybrid Modeling
  • Computational Chemistry
  • Artificial Intelligence

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