000201582 001__ 201582
000201582 005__ 20181203023609.0
000201582 0247_ $$2doi$$a10.1002/bit.24614
000201582 022__ $$a0006-3592
000201582 037__ $$aARTICLE
000201582 245__ $$aA pore-hindered diffusion and reaction model can help explain the importance of pore size distribution in enzymatic hydrolysis of biomass
000201582 260__ $$bWiley-Blackwell$$c2012
000201582 269__ $$a2012
000201582 336__ $$aJournal Articles
000201582 520__ $$aUntil now, most efforts to improve monosaccharide production from biomass through pretreatment and enzymatic hydrolysis have used empirical optimization rather than employing a rational design process guided by a theory-based modeling framework. For such an approach to be successful a modeling framework that captures the key mechanisms governing the relationship between pretreatment and enzymatic hydrolysis must be developed. In this study, we propose a pore-hindered diffusion and kinetic model for enzymatic hydrolysis of biomass. When compared to data available in the literature, this model accurately predicts the well-known dependence of initial cellulose hydrolysis rates on surface area available to a cellulase-size molecule. Modeling results suggest that, for particles smaller than 5 × 10−3 cm, a key rate-limiting step is the exposure of previously unexposed cellulose occurring after cellulose on the surface has hydrolyzed, rather than binding or diffusion. However, for larger particles, according to the model, diffusion plays a more significant role. Therefore, the proposed model can be used to design experiments that produce results that are either affected or unaffected by diffusion. Finally, by using pore size distribution data to predict the biomass fraction that is accessible to degradation, this model can be used to predict cellulose hydrolysis with time using only pore size distribution and initial composition data
000201582 700__ $$0248339$$g154408$$aLuterbacher, Jeremy S.
000201582 700__ $$aParlange, Jean-Yves
000201582 700__ $$aWalker, Larry P.
000201582 773__ $$j110$$tBiotechnology and Bioengineering$$k1$$q127-136
000201582 909C0 $$xU12907$$0252511$$pLPDC
000201582 909CO $$pSB$$particle$$ooai:infoscience.tind.io:201582
000201582 917Z8 $$x242569
000201582 917Z8 $$x242569
000201582 937__ $$aEPFL-ARTICLE-201582
000201582 973__ $$rREVIEWED$$sPUBLISHED$$aOTHER
000201582 980__ $$aARTICLE