Imperial College London
Portrait Picture

Professor Cleo Kontoravdi

Faculty of Engineering, Department of Chemical Engineering

Professor of Biological Systems Engineering
 
 
 
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Contact

 

+44 (0)20 7594 6655cleo.kontoravdi98 Website

 
 
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Location

 

310ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Niu:2015:10.1016/j.bej.2015.10.017,
author = {Niu, H and Shah, N and Kontoravdi, C},
doi = {10.1016/j.bej.2015.10.017},
journal = {Biochemical Engineering Journal},
pages = {455--472},
title = {Modelling of Amorphous Cellulose Depolymerisation by Cellulases, Parametric Studies and Optimisation},
url = {http://dx.doi.org/10.1016/j.bej.2015.10.017},
volume = {105},
year = {2015}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Improved understanding of heterogeneous cellulose hydrolysis by cellulases is the basis for optimising enzymatic catalysis-based cellulosic biorefineries. A detailed mechanistic model is developed to describe the dynamic adsorption/desorption and synergistic chain-end scissions of cellulases (endoglucanase, exoglucanase, and β-glucosidase) upon amorphous cellulose. The model can predict evolutions of the chain lengths of insoluble cellulose polymers and production of soluble sugars during hydrolysis. Simultaneously, a modelling framework for uncertainty analysis is built based on a quasi-Monte-Carlo method and global sensitivity analysis, which can systematically identify key parameters, help refine the model and improve its identifiability. The model, initially comprising 27 parameters, is found to be over-parameterized with structural and practical identification problems under usual operating conditions (low enzyme loadings). The parameter estimation problem is therefore mathematically ill posed. The framework allows us, on the one hand, to identify a subset of 13 crucial parameters, of which more accurate confidence intervals are estimated using a given experimental dataset, and, on the other hand, to overcome the identification problems. The model’s predictive capability is checked against an independent set of experimental data. Finally, the optimal composition of cellulases cocktail is obtained by model-based optimisation both for enzymatic hydrolysis and for the process of simultaneous saccharification and fermentation.
AU  - Niu,H
AU  - Shah,N
AU  - Kontoravdi,C
DO  - 10.1016/j.bej.2015.10.017
EP  - 472
PY  - 2015///
SN  - 1873-295X
SP  - 455
TI  - Modelling of Amorphous Cellulose Depolymerisation by Cellulases, Parametric Studies and Optimisation
T2  - Biochemical Engineering Journal
UR  - http://dx.doi.org/10.1016/j.bej.2015.10.017
UR  - http://hdl.handle.net/10044/1/27471
VL  - 105
ER  -
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