The polymers found in plant cell walls represent the largest reserves of renewable carbon on Earth - it has been estimated that the United States has approximately 1.3 billion tons of plant biomass available per year. Ionic liquids (ILs) are salts with melting points less than 100oC, typically containing organic cations, that possess a wide range of extraordinary properties as compared to traditional organic solvents. The unusual catalytic and solvation properties of ionic liquids have attracted the biofuel and biomass communities because IL-pretreatment provides higher fermentable sugar yields than those obtained by acid- or alkali-pretreatment under similar severities. This research used lignin, a major by-product of the biofuel and pulping industries, as raw material for IL synthesis. The goal is to lower the cost of IL production, and enable a more "closed-loop" biorefinery. The lignin is oxidatively depolymerized, purified, and used to prepare a new class of renewable ILs. Biomass pretreatment was the target application for the lignin-derived ILs, while we continue to investigate additional applications within the growing IL market - process chemistry, biotechnology and materials recycling. When comparing our corn stover pretreatment data to recently published reports, we have shown comparable glucose and xylose yields by using neat and 10% aqueous solutions of lignin-derived ILs.

Feedstock blending as a strategy to mitigate risks in the supply of lignocellulosic biomass to commercial scale biorefineries across various geographical areas in the United States. Machine learning predictive models estimate sugar yields from feedstock blends expected to be available in Florida and Kansas. Performance of each model was assessed based on feature selection along with two-stack ensembles applied in both linear and nonlinear algorithms. Linear-weighted ensemble and nonlinear stochastic gradient boosting model ensembled with four base learners exhibited similar predictions as previously developed linear regression models when predicting glucose yields in the higher range. The ensemble models achieved a 10–50 % improvement in the root mean squared error with feature selection compared to models with full features from validation. Machine learning has the potential to predict sugar yields at high confidence for a given feedstock blend ratio and pretreatment conditions.

Systems biology and synthetic biology are increasingly used to examine and modulate complex biological systems. As such, many issues arising during scaling-up microbial production processes can be addressed using these approaches. We review differences between laboratory-scale cultures and larger-scale processes to provide a perspective on those strain characteristics that are especially important during scaling. Systems biology has been used to examine a range of microbial systems for their response in bioreactors to fluctuations in nutrients, dissolved gases, and other stresses. Synthetic biology has been used both to assess and modulate strain response, and to engineer strains to improve production. We discuss these approaches and tools in the context of their use in engineering robust microbes for applications in large-scale production.

Lignin fractionation helps its valorization process and yields high-quality and -value products. In this study, cascading tangential flow filtration (TFF) was employed for the fractionation of lignin molecules. The lignin-rich stream was obtained from the pretreatment process of corn stover using alkali (NaOH) and cholinium lysinate ([Ch][Lys]) as the catalyst. The effect of TFF (microfiltration, ultrafiltration, and nanofiltration) on lignin molecular weight, sugar distribution, viscosity, and lignin functional groups was investigated. In general, the study concluded that the average molecular weight (MW) and polydispersity of the permeate stream decreased with the reduction of the membrane pore size. TFF was effective in separating the low-MW lignin (200-350 Da) from the aqueous stream. Approximately 2% of monomeric lignin and 10-20% of low-molecular-weight lignin were recovered from NaOH- and [Ch][Lys]-extracted streams. Techno-economic analysis (TEA) results show that a high percentage of the low-MW lignin extraction can be achieved via a cascade TFF membrane operating at high transmembrane pressures (TMPs) and cross membrane velocities. Additionally, a high initial concentration of lignin in the liquid stream plays a critical role in the lignin product yield and recovery cost.

This scale-up study demonstrated the feasibility of an ionic liquid (IL) pretreatment process at 40 kg scale, using the IL 1-ethyl-3-methylimidazolium acetate ([C2C1Im][OAc]) as the solvent. The pretreatment was followed by enzymatic hydrolysis through which the process efficiency for biomass conversion to monomeric sugars was determined. The results show that 43 wt% of switchgrass was dissolved in IL after 2 h of pretreatment at 160 °C with 15 wt% solid loading. A 120 h enzymatic hydrolysis of the pretreated switchgrass results in 96% glucan and 98% xylan conversion. [C2C1Im][OAc] pretreatment has been successfully scaled up to 40 kg with improved sugar titers and yields relative to bench scale (6 kg). The mass flow of the overall process was established and the major scale-up challenges of the process were identified.