Abstract

BackgroundUnderstanding how the digestibility of lignocellulosic biomass is affected by its morphology is essential to design efficient processes for biomass deconstruction. In this study, we used a model based on a set of partial differential equations describing the evolution of the substrate morphology to investigate the interplay between experimental conditions and the physical characteristics of biomass particles as the reaction proceeds. Our model carefully considers the overall quantity of cellulase present in the hydrolysis mixture and explores its interplay with the available accessible cellulose surface.ResultsExploring the effect of various experimental and structural parameters highlighted the significant role of internal mass transfer as the substrate size increases and/or the enzyme loading decreases. In such cases, diffusion of cellulases to the available cellulose surface limits the rate of glucose release. We notably see that increasing biomass loading, while keeping enzyme loading constant should be favored for both small- (R < 300 mu m) and middle-ranged (300 < R < 1000 mu m) substrates to enhance enzyme diffusion while minimizing the use of enzymes. In such cases, working at enzyme loadings exceeding the full coverage of the cellulose surface (i.e. eI>1) does not bring a significant benefit. For larger particles (R > 1000 mu m), increases in biomass loading do not offset the significant internal mass transfer limitations, but high enzyme loadings improve enzyme penetration by maintaining a high concentration gradient within the particle. We also confirm the well-known importance of cellulose accessibility, which increases with pretreatment.ConclusionsBased on the developed model, we are able to propose several design criteria for deconstruction process. Importantly, we highlight the crucial role of adjusting the enzyme and biomass loading to the wood particle size and accessible cellulose surface to maintain a strong concentration gradient, while avoiding unnecessary excess in cellulase loading. Theory-based approaches that explicitly consider the entire lignocellulose particle structure can be used to clearly identify the relative importance of bottlenecks during the biomass deconstruction process, and serve as a framework to build on more detailed cellulase mechanisms.

Highlights

  • Understanding how the digestibility of lignocellulosic biomass is affected by its morphology is essential to design efficient processes for biomass deconstruction

  • We presented a substrate-focused modeling framework based on pore diffusion and surface reaction for the enzymatic hydrolysis of lignocellulosic biomass to evaluate the relative impact of the substrate properties on its digestibility

  • We demonstrated that the model was robust enough to predict initial glucose release rates for a range of substrates and experimental conditions with a single set of fitted parameters ( Mp = 755 and τ = 2 ), which could be used as a decent first approximation when attempting to predict other substrate–enzyme systems

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Summary

Introduction

Understanding how the digestibility of lignocellulosic biomass is affected by its morphology is essential to design efficient processes for biomass deconstruction. The high-cost of this procedure is related to the resulting yields of monosaccharides, the rate of hydrolysis, and quantity of the enzymes required These factors are always heavily influenced by the physicochemical, structural and compositional properties of the substrate itself, as well as its interactions with enzymes. Two notable phenomena that are well known but poorly understood, at least quantitatively, are the decrease in hydrolysis rates observed as the reaction proceeds [27,28,29,30] and the similar decrease in rates with increased solid loading [31, 32] Given their importance for industrial scale-up, this lack of understanding impedes the implementation of economically viable biomass-to-biofuels pathways. Studying enzymatic hydrolysis is notably complicated (i) by the difficulty of experimentally investigating each factor independently, as targeted modifications of one parameter usually impact the others, and (ii) by the experimental observations being highly dependent on the substrate native structure and treatment history, as well as the composition of the enzyme cocktail that is used

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