A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract

BackgroundEnzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system.ResultsA phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed.ConclusionsAlthough the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

Different pre-treatments and kinetic models for bioethanol production from lignocellulosic biomass: A review

“…However, using them is time-consuming, labour-intensive, and harmful to the environment. Theoretical models were thus developed and are frequently used to reduce the workload and further give insights into the reaction process [ 26 , 27 ]. These models help in understanding the reaction mechanisms more thoroughly thus making the reactor design process easier.…”

A Simple Techno-Economic Assessment for Scaling-Up the Enzymatic Hydrolysis of MSW Pulp

“…A sudden decrease in glucose concentrations is observed when switching from batch to continuous, taking several hours to reach steady state. More recently, Lischeske and Stickel (2019) reported that final glucose concentrations of 5 and 7.5%TS acid-pretreated corn stover were significantly higher in batch than in continuous mode, 22.5 to 12.5 g L −1 and 40 to 22 g L −1 , respectively. Ghorbanpour Khamseh and Miccio (2012) showed by modeling that galacturonic acid concentrations decrease from 0.3 to 0.15 g/kg biomass during orange peel hydrolysis when changing from batch to continuous operation.…”

“…It is well-known that batch and fed-batch systems result in higher conversion yields than continuous processing, mainly due to operating at longer mixing times (Ghorbanian et al, 2014). The release of glucose yields during different modes of operation (batch, fed-batch, and continuous) has been compared for the enzymatic saccharification of corn stover (Lischeske and Stickel, 2019;Stickel et al, 2018) and orange peel wastes (Ghorbanpour Khamseh and Miccio, 2012). Although insoluble solid loadings were not set equally due to "clogging" issues during continuous processing, Stickel et al (2018) showed that batch hydrolysis yielded over 10 g glucose per g biomass (at 10%TS) whilst only 0.44 g glucose per gram biomass in continuous mode (5% TS).…”

“…Enzymatic hydrolysis has been traditionally performed in batch processes due to its simple design (Davis et al, 2013). However, it has been recently recognized that fed-batch and continuous strategies could bring down costs by improving sugar productivity and reducing enzyme usage (Ghorbanpour Khamseh and Miccio, 2012;Sotaniemi et al, 2016;Lischeske and Stickel, 2019). The cost of enzymes used in the process is a key limiting factor in the economic viability of enzymatic processing.…”

Investigating the effects of substrate morphology and experimental conditions on the enzymatic hydrolysis of lignocellulosic biomass through modeling

“…Other modeling strategies have incorporated the effect of the entire lignocellulosic structure on the biomass deconstruction, mainly in an implicit way. Specifically, the impact of mass transfer arising from biomass particle size and/or loading have been incorporated or considered through the use of empirically trained artificial neural networks [ 32 ], addition of corrective kinetic terms in fractal-like kinetic modeling [ 38 ], or phenomenological description of the hydrolytic process [ 39 ].…”