Deconstruction of Woody Biomass via Protic and Aprotic Ionic Liquid Pretreatment for Ethanol Production

Ionic liquids (ILs) have emerged as important solvents for conversion of lignocellulosic feedstocks to fuels and chemicals due to their ability to enable efficient biomass deconstruction and fractionation. Woody biomass derived from forest and agricultural residues has the potential to be used for production of biofuels and its removal from forests can help mitigate disastrous wildfires in fire-prone states like California. This study evaluated woody biomass types (pine, almond, walnut, and fir) from California as potential biofuel feedstocks. The feedstocks were pretreated with the ILs cholinium lysinate ([Ch][Lys]) and ethanolamine acetate ([EOA][OAc]), followed by enzymatic hydrolysis and fermentation of lignocellulosic sugars to produce ethanol. Under optimal conditions, [EOA][OAc] pretreatment and enzymatic hydrolysis generated glucose and xylose yields in the range of 24-82 and 14-80%, respectively, while glucose and xylose yields for the [Ch][Lys] ranged between 28-83 and 23-80%, respectively. Maximum fermentable sugar was released from almond wood, and the lowest amount was from pine and fir. Blends of feedstocks were also explored, and a blend with a mass ratio of 2/2/1 (almond/walnut/pine) resulted in maximum glucose and xylose (>90%) yields using [Ch][Lys]. Fermentation of this hydrolysate using a C5-utilizing strain of Saccharomyces cerevisiae resulted in a maximum ethanol concentration of 17.9 g/L for mixture biomass hydrolysate, corresponding to 60.8% fermentation efficiency. This study represents the first demonstration of the use of these ILs for pretreatment of woody biomass blends that resulted in a high overall conversion efficiency for ethanol production

A predictive toolset for the identification of effective lignocellulosic pretreatment solvents: a case study of solvents tailored for lignin extraction

Pretreatment of lignocellulosic biomass is essential for efficient conversion into biofuels and bioproducts. The present study develops a predictive toolset to computationally identify solvents that can efficiently dissolve lignin and therefore can be used to extract it from lignocellulose during pretreatment, a process known to reduce recalcitrance to enzymatic deconstruction and increase conversion efficiency. Two approaches were taken to examine the potential of eleven organic solvents to solubilize lignin, Hansen solubility parameters (HSP) and activity coefficients and excess enthalpies of solvent/lignin mixtures predicted by COSMO-RS (COnductor like Screening MOdel for Real Solvents). The screening revealed that diethylenetriamine was the most effective solvent, promoting the highest lignin removal (79.2%) and fermentable sugar yields (>72%). Therefore, a COSMO-RS-based predictive model for the lignin removal as a function of number and type of amines was developed. Among the fitted models, the non-linear regression model predicts the lignin solubility more accurately than the linear model. Experimental results demonstrated a >65% lignin removal and >70% of sugar yield from several amine-based solvents tested, which aligned very well with the model's prediction. Finally, to help understand the dissolution mechanism of lignin by these solvents, quantum theory of atoms in molecules (QTAIM) and quantum chemical calculations (interaction energies and natural bond orbital (NBO) analysis) was performed and suggest that amines exhibit strong electrostatic interactions and hydrogen bonding strengths with lignin leading to higher lignin removal. Together, these computational tools provide an effective approach for rapidly identifying solvents that are tailored for effective biomass pretreatment

A predictive toolset for the identification of effective lignocellulosic pretreatment solvents: a case study of solvents tailored for lignin extraction

Pretreatment of lignocellulosic biomass is essential for efficient conversion into biofuels and bioproducts. The present study develops a predictive toolset to computationally identify solvents that can efficiently dissolve lignin and therefore can be used to extract it from lignocellulose during pretreatment, a process known to reduce recalcitrance to enzymatic deconstruction and increase conversion efficiency. Two approaches were taken to examine the potential of eleven organic solvents to solubilize lignin, Hansen solubility parameters (HSP) and activity coefficients and excess enthalpies of solvent/lignin mixtures predicted by COSMO-RS (COnductor like Screening MOdel for Real Solvents). The screening revealed that diethylenetriamine was the most effective solvent, promoting the highest lignin removal (79.2%) and fermentable sugar yields (>72%). Therefore, a COSMO-RS-based predictive model for the lignin removal as a function of number and type of amines was developed. Among the fitted models, the non-linear regression model predicts the lignin solubility more accurately than the linear model. Experimental results demonstrated a >65% lignin removal and >70% of sugar yield from several amine-based solvents tested, which aligned very well with the model's prediction. Finally, to help understand the dissolution mechanism of lignin by these solvents, quantum theory of atoms in molecules (QTAIM) and quantum chemical calculations (interaction energies and natural bond orbital (NBO) analysis) was performed and suggest that amines exhibit strong electrostatic interactions and hydrogen bonding strengths with lignin leading to higher lignin removal. Together, these computational tools provide an effective approach for rapidly identifying solvents that are tailored for effective biomass pretreatment

High-Efficiency Conversion of Ionic Liquid-Pretreated Woody Biomass to Ethanol at the Pilot Scale

With a diverse and widely distributed global resource base, woody biomass is a compelling organic feedstock for conversion to renewable liquid fuels. In California, woody biomass comprises the largest fraction of underutilized biomass available for biofuel production, but conversion to fuels is challenged both by recalcitrance to deconstruction and by toxicity toward downstream saccharification and fermentation due to organic acids and phenolic compounds generated during pretreatment. In this study, we optimize pretreatment and scale-up of an integrated one-pot process for deconstruction of California woody biomass using the ionic liquid (IL) cholinium lysinate [Ch][Lys] as a pretreatment solvent. By evaluating the impact of solid loading, solid removal, yeast acclimatization, fermentation temperature, fermentation pH, and nutrient supplementation on final ethanol yields and titers, we achieve nearly full conversion of both glucose and xylose to ethanol with commercial C5-utilizing Saccharomyces cerevisiae. We then demonstrate process scalability in 680 L pilot-scale fermentation, achieving >80% deconstruction efficiency, >90% fermentation efficiency, 27.7 g/L ethanol titer, and >80% ethanol distillation efficiency from the IL-containing hydrolysate post fermentation. This fully integrated process requires no intermediate separations and no intermediate detoxification of the hydrolysate. Using an integrated biorefinery model, current performance results in a minimum ethanol selling price of $8.8/gge. Reducing enzyme loading along with other minor process improvements can reduce the ethanol selling price to$3/gge. This study is the largest scale demonstration of IL pretreatment and biofuel conversion known to date, and the overall biomass-to-ethanol efficiencies are the highest reported to date for any IL-based biomass-to-biofuel conversion