Developing structure-oriented models for enzymatic hydrolysis of lignocellulosic biomass

With the unsustainable use of fossil fuels increasing strains on human institutions and ecosystems, the development of a renewable energy alternative is of paramount importance. Second generation biorefineries, based on the production of fuels and chemicals from lignocellulosic biomass, appear as attractive alternative to their non-renewable counterparts. Within the multiplicity of existing valorisation routes, enzymatic hydrolysis of lignocellulosic biomass into its constituent sugars has generated considerable interest, notably in the context of biofuels production. However, major hurdles stemming from the intricate structure of the lignocellulosic feedstocks still impede large-scale deployment of this process.

The multiplicity of highly intertwined spatiotemporal factors impacting the enzymatic hydrolysis of lignocellulosic biomass represents a challenge to rationally design efficient hydrolysis process. Here, we propose a theory-based modelling framework relying on pore-diffusion and surface reaction to explore the effects of recognised bottlenecks on the enzymatic hydrolysis of lignocellulosic substrates. The model is 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. The overall quantity of cellulase present in the hydrolysis mixture is carefully considered to investigate its interplay with the available accessible cellulose surface. Also, non-uniformity in terms of cellulose accessibility and cellulose digestibility are introduced in the model to weight their influence on observed hydrolysis rates. Finally, deactivation mechanisms are considered through unproductive adsorption of cellulases on both cellulose and lignin fractions, with the existence of such phenomena alleged to be critical in the efficiency of the hydrolysis process.

Based on predictions of our model, we were able to confirm the critical role of cellulose accessibility, as defined by the combination of particle size, porosity and accessible cellulose surface, in dictating early reaction rates for a range of pretreated beech wood substrates. While high biomass loading should be favoured to improve enzyme penetration in the substrates, high enzyme loadings going beyond the initial number of cellulose adsorption appeared beneficial in notably two cases: (i) to promote internal diffusion in large particles and (ii) counteract undesired enzyme adsorption on lignin. For the latter, a relatively low increase in enzyme loading was sufficient to offset the resulting slowdown. We also showed that the existence of structural heterogeneities, and in particular non-uniform pore volume distribution within the lignocellulosic samples, contribute to the rate slowdown observed at later stage of the hydrolysis, while not explaining it in its entirety. Unproductive adsorption to cellulose, coupled to decrease in the cellulase efficiency at the cellulose surface, appeared as major contributor to the rate slowdown. Overall, we show how the use of a theory-based model can help decouple and evaluate the effects of key factors in the enzymatic hydrolysis of lignocellulosic biomass. As such, our model can help pave the way towards efficient integrated rational design strategies for enzyme process engineering for biomass conversion.