Corn stover semi-mechanistic enzymatic hydrolysis model with tight parameter confidence intervals for model-based process design and optimization

Felipe Scott; Muyang Li; Daniel L. Williams; Raúl Conejeros; David B. Hodge; Germán Aroca

doi:10.1016/j.biortech.2014.11.062

Corn stover semi-mechanistic enzymatic hydrolysis model with tight parameter confidence intervals for model-based process design and optimization

Felipe Scott^*, Muyang Li, Daniel L. Williams, Raúl Conejeros, David B. Hodge, Germán Aroca

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Uncertainty associated to the estimated values of the parameters in a model is a key piece of information for decision makers and model users. However, this information is typically not reported or the confidence intervals are too large to be useful. A semi-mechanistic model for the enzymatic saccharification of dilute acid pretreated corn stover is proposed in this work, the model is a modification of an existing one providing a statistically significant improved fit towards a set of experimental data that includes varying initial solid loadings (10-25% w/w) and the use of the pretreatment liquor and washed solids with or without supplementation of key inhibitors. A subset of 8 out of 17 parameters was identified, showing sufficiently tight confidence intervals to be used in uncertainty propagation and model analysis, without requiring interval truncation via expert judgment.

Original language	English
Pages (from-to)	255-265
Number of pages	11
Journal	Bioresource Technology
Volume	177
DOIs	https://doi.org/10.1016/j.biortech.2014.11.062
State	Published - 1 Feb 2015
Externally published	Yes

Bibliographical note

Funding Information:
Financial support granted to F. Scott by CONICYT’s scholarship program (Comisión Nacional de Investigación Científica y Tecnológica, Chile) is gratefully acknowledged. Muyang Li was supported in part by a grant from the National Science Foundation – United States ( NSF CBET 1336622 ). This work was funded by Innova Chile Project 208-7320 Technological Consortium Bioenercel S.A.

Publisher Copyright:
© 2014 Elsevier Ltd.

Keywords

Biofuels
Enzymatic hydrolysis
High-solids saccharification
Kinetic model
Lignocellulose

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.biortech.2014.11.062

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title = "Corn stover semi-mechanistic enzymatic hydrolysis model with tight parameter confidence intervals for model-based process design and optimization",

abstract = "Uncertainty associated to the estimated values of the parameters in a model is a key piece of information for decision makers and model users. However, this information is typically not reported or the confidence intervals are too large to be useful. A semi-mechanistic model for the enzymatic saccharification of dilute acid pretreated corn stover is proposed in this work, the model is a modification of an existing one providing a statistically significant improved fit towards a set of experimental data that includes varying initial solid loadings (10-25% w/w) and the use of the pretreatment liquor and washed solids with or without supplementation of key inhibitors. A subset of 8 out of 17 parameters was identified, showing sufficiently tight confidence intervals to be used in uncertainty propagation and model analysis, without requiring interval truncation via expert judgment.",

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author = "Felipe Scott and Muyang Li and Williams, {Daniel L.} and Ra{\'u}l Conejeros and Hodge, {David B.} and Germ{\'a}n Aroca",

note = "Funding Information: Financial support granted to F. Scott by CONICYT{\textquoteright}s scholarship program (Comisi{\'o}n Nacional de Investigaci{\'o}n Cient{\'i}fica y Tecnol{\'o}gica, Chile) is gratefully acknowledged. Muyang Li was supported in part by a grant from the National Science Foundation – United States ( NSF CBET 1336622 ). This work was funded by Innova Chile Project 208-7320 Technological Consortium Bioenercel S.A. Publisher Copyright: {\textcopyright} 2014 Elsevier Ltd.",

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doi = "10.1016/j.biortech.2014.11.062",

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AU - Hodge, David B.

AU - Aroca, Germán

N1 - Funding Information: Financial support granted to F. Scott by CONICYT’s scholarship program (Comisión Nacional de Investigación Científica y Tecnológica, Chile) is gratefully acknowledged. Muyang Li was supported in part by a grant from the National Science Foundation – United States ( NSF CBET 1336622 ). This work was funded by Innova Chile Project 208-7320 Technological Consortium Bioenercel S.A. Publisher Copyright: © 2014 Elsevier Ltd.

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AB - Uncertainty associated to the estimated values of the parameters in a model is a key piece of information for decision makers and model users. However, this information is typically not reported or the confidence intervals are too large to be useful. A semi-mechanistic model for the enzymatic saccharification of dilute acid pretreated corn stover is proposed in this work, the model is a modification of an existing one providing a statistically significant improved fit towards a set of experimental data that includes varying initial solid loadings (10-25% w/w) and the use of the pretreatment liquor and washed solids with or without supplementation of key inhibitors. A subset of 8 out of 17 parameters was identified, showing sufficiently tight confidence intervals to be used in uncertainty propagation and model analysis, without requiring interval truncation via expert judgment.

KW - Biofuels

KW - Enzymatic hydrolysis

KW - High-solids saccharification

KW - Kinetic model

KW - Lignocellulose

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Corn stover semi-mechanistic enzymatic hydrolysis model with tight parameter confidence intervals for model-based process design and optimization

Abstract

Bibliographical note

Keywords

UN SDGs

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