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Gallifuoco A, Papa AA, Taglieri L. Modeling biomass hydrothermal carbonization by the maximum information entropy criterion. REACT CHEM ENG 2021. [DOI: 10.1039/d1re00002k] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The kinetics of biomass hydrothermal carbonization is modeled by the MaxEnt principle, without assuming a reaction network. Modeling is in good accordance with the experimental data concerning a broad range of biomass and reaction conditions.
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Affiliation(s)
- Alberto Gallifuoco
- University of L'Aquila
- Department of Industrial and Information Engineering & Economics
- Italy
| | | | - Luca Taglieri
- University of L'Aquila
- Department of Industrial and Information Engineering & Economics
- Italy
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Olkiewicz M, Tylkowski B, Montornés JM, Garcia-Valls R, Gulaczyk I. Modelling of enzyme kinetics: cellulose enzymatic hydrolysis case. PHYSICAL SCIENCES REVIEWS 2020. [DOI: 10.1515/psr-2020-0039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
Enzymes as industrial biocatalysts offer numerous advantages over traditional chemical processes resulting on improvements in process economy and environmental sustainability. Because enzymes are extensively used in different industrial areas, the enzyme kinetics is an important factor for industry as it is able to estimate the extent of substrate conversion under known conditions and evaluate reactor performance. Furthermore, kinetic modelling is useful in the analysis, prediction, and optimization of an enzymatic process. Thus, kinetic modelling is a powerful tool for biochemical reaction engineering. In addition to the aforementioned, in the industrial technology, modelling together with simulation play a key role because they help to understand how a system behaves under specific conditions, and thus they allow saving on costs and lead times. Enzymatic conversion of renewable cellulosic biomass into biofuels is at the heart of advanced bioethanol production. In the production of bioethanol from cellulosic biomass, enzymatic hydrolysis of cellulose to fermentable sugars accounts for a large portion (∼30%) of the total production costs. Therefore, a thorough understanding of enzymatic hydrolysis is necessary to create a robust model which helps designing optimal conditions and economical system. Nevertheless, it is a challenging task because cellulose is a highly complex substrate and its enzymatic hydrolysis is heterogeneous in nature, and thus the whole process of cellulose conversion to glucose involves more steps than classical enzyme kinetics. This chapter describes the bases of enzyme kinetic modelling, focussing on Michaelis-Menten kinetics, and presents the models classification based on the fundamental approach and methodology used. Furthermore, the modelling of cellulose enzymatic hydrolysis is described, also reviewing some model examples developed for cellulose hydrolysis over the years. Finally, the application of enzyme kinetics modelling in food, pharmaceutical and bioethanol industry is presented.
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Affiliation(s)
- Magdalena Olkiewicz
- Eurecat Technology Centre of Catalonia , Chemical Technology Unit , C/ Marcel·lí Domingo 2 , 43007 Tarragona , Spain
| | - Bartosz Tylkowski
- Eurecat Technology Centre of Catalonia , Chemical Technology Unit , C/ Marcel·lí Domingo 2 , 43007 Tarragona , Spain
| | - Josep M. Montornés
- Eurecat Technology Centre of Catalonia , Chemical Technology Unit , C/ Marcel·lí Domingo 2 , 43007 Tarragona , Spain
| | - Ricard Garcia-Valls
- Eurecat Technology Centre of Catalonia , Chemical Technology Unit , C/ Marcel·lí Domingo 2 , 43007 Tarragona , Spain
- Universitat Rovira i Virgili , Department of Chemical Engineering , Av. Països Catalans 26 , 43007 Tarragona , Spain
| | - Iwona Gulaczyk
- Faculty of Chemistry , Adam Mickiewicz University in Poznan , ul. Uniwersytetu Poznańskiego 8 , 61-614 Poznań , Poland
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Multi-objective reactor design under uncertainty: A decomposition approach based on cubature rules. Chem Eng Sci 2020. [DOI: 10.1016/j.ces.2019.115304] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Freund H, Maußner J, Kaiser M, Xie M. Process intensification by model-based design of tailor-made reactors. Curr Opin Chem Eng 2019. [DOI: 10.1016/j.coche.2019.08.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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