Assessing pretreatment reactor scaling through empirical analysis. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Lischeske, James; Crawford, Nathan; Kuhn, Erik; Nagle, Nicholas; Schell, Daniel; Tucker, Melvin; McMillan, James; Wolfrum, Edward
• Is Part Of: Biotechnology for biofuels. Volume 9:Issue 1(2016)
• Page Start: 1
• Page End: 13
• Publication Date: 2016-12
• Subjects: Biomass -- Biofuels -- Pretreatment -- Enzymatic digestibility; Biotechnology -- Periodicals; Biomass energy -- Periodicals; Energy-Generating Resources -- Periodicals; 662.88
• DOI: 10.1186/s13068-016-0620-0
• Languages: English
• ISSNs: 1754-6834

Abstract

Abstract Background Pretreatment is a critical step in the biochemical conversion of lignocellulosic biomass to fuels and chemicals. Due to the complexity of the physicochemical transformations involved, predictively scaling up technology from bench- to pilot-scale is difficult. This study examines how pretreatment effectiveness under nominally similar reaction conditions is influenced by pretreatment reactor design and scale using four different pretreatment reaction systems ranging from a 3 g batch reactor to a 10 dry-ton/days continuous reactor. The reactor systems examined were an automated solvent extractor (ASE), steam explosion reactor (SER), ZipperClave® Reactor (ZCR), and large continuous horizontal screw reactor (LHR). To our knowledge, this is the first such study performed on pretreatment reactors across a range of reaction conditions and at different reactor scales. Results The comparative pretreatment performance results obtained for each reactor system were used to develop response surface models for total xylose yield after pretreatment and total sugar yield after pretreatment followed by enzymatic hydrolysis. Near- and very-near-optimal regions were defined as the set of conditions that the model identified as producing yields within one and two standard deviations of the optimum yield. Optimal conditions identified in the smallest scale system (the ASE) were within the near-optimal region of the largest scale reactor system evaluated. The maximum total sugar yields for the ASE and LHR were $$95\, \%$$ 95 %, while $$89\, \%$$ 89 % was the optimum observed in the ZipperClave. Conclusions The optimum condition identified using the automated and less costly to operate ASE system was within the very-near-optimal space for the total xylose yield of both the ZCR and the LHR, and was within the near-optimal space for total sugar yield for the LHR. This indicates that the ASE is a good tool for cost effectively finding near-optimal conditions for operating pilot-scale systems. Additionally, using a severity factor approach to optimization was found to be inadequate compared to a multivariate optimization method. Finally, the ASE and the LHR were able to enable significantly higher total sugar yields after enzymatic hydrolysis relative to the ZCR, despite having similar optimal conditions and total xylose yields. This underscores the importance of mechanical disruption during pretreatment to improvement of enzymatic digestibility.