Parametric study for the optimization of ionic liquid pretreatment of corn stover. (October 2017)

• Record Type: Journal Article
• Authors: Papa, Gabriella; Feldman, Taya; Sale, Kenneth L.; Adani, Fabrizio; Singh, Seema; Simmons, Blake A.
• Is Part Of: Bioresource technology. Volume 241(2017)
• Page Start: 627
• Page End: 637
• Publication Date: 2017-10
• Subjects: Corn stover -- Ionic liquid pretreatment -- Particle size -- Mass balance -- Pretreatment efficiency; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2017.05.167
• Languages: English
• ISSNs: 0960-8524

Abstract

Highlights: [Ch][Lys] and [C2 C1 Im][OAc] ionic liquids pretreated large particle sized corn stover. Sugar yields were observed even at the low enzyme dosage. Lignin and xylan removal improved sugar yields. Temperature and solid loading affected energy requirement and process efficiency. Abstract: A parametric study of the efficacy of the ionic liquid (IL) pretreatment (PT) of corn stover (CS) using 1-ethyl-3-methylimidazolium acetate ([C2 C1 Im][OAc]) and cholinium lysinate ([Ch][Lys]) was conducted. The impact of 50% and 15% biomass loading for milled and non-milled CS on IL-PT was evaluated, as well the impact of 20 and 5 mg enzyme/g glucan on saccharification efficiency. The glucose and xylose released were generated from 32 conditions – 2 ionic liquids (ILs), 2 temperatures, 2 particle sizes (S), 2 solid loadings, and 2 enzyme loadings. Statistical analysis indicates that sugar yields were correlated with lignin and xylan removal and depends on the factors, where S did not explain variation in sugar yields. Both ILs were effective in pretreating large particle sized CS, without compromising sugar yields. The knowledge from material and energy balances is an essential step in directing optimization of sugar recovery at desirable process conditions.