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

Research output: Contribution to journalArticlepeer-review

6 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 languageEnglish
Pages (from-to)255-265
Number of pages11
JournalBioresource Technology
Volume177
DOIs
StatePublished - 1 Feb 2015
Externally publishedYes

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

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