Alkaline twin-screw extrusion pretreatment for fermentable sugar production

BACKGROUND: The inevitable depletion of fossil fuels has resulted in an increasing worldwide interest in exploring alternative and sustainable energy sources. Lignocellulose, which is the most abundant biomass on earth, is widely regarded as a promising raw material to produce fuel ethanol. Pretreatment is an essential step to disrupt the recalcitrance of lignocellulosic matrix for enzymatic saccharification and bioethanol production. This paper established an ATSE (alkaline twin-screw extrusion pretreatment) process using a specially designed twin-screw extruder in the presence of alkaline solution to improve the enzymatic hydrolysis efficiency of corn stover for the production of fermentable sugars. RESULTS: The ATSE pretreatment was conducted with a biomass/liquid ratio of 1/2 (w/w) at a temperature of 99°C without heating equipment. The results indicated that ATSE pretreatment is effective in improving the enzymatic digestibility of corn stover. Sodium hydroxide loading is more influential factor affecting both sugar yield and lignin degradation than heat preservation time. After ATSE pretreatment under the proper conditions (NaOH loading of 0.06 g/g biomass during ATSE and 1 hour heat preservation after extrusion), 71% lignin removal was achieved and the conversions of glucan and xylan in the pretreated biomass can reach to 83% and 89% respectively via subsequent enzymatic hydrolysis (cellulase loading of 20 FPU/g-biomass and substrate consistency of 2%). About 78% of the original polysaccharides were converted into fermentable sugars. CONCLUSIONS: With the physicochemical functions in extrusion, the ATSE method can effectively overcome the recalcitrance of lignocellulose for the production of fermentable sugars from corn stover. This process can be considered as a promising pretreatment method due to its relatively low temperature (99°C), high biomass/liquid ratio (1/2) and satisfied total sugar yield (78%), despite further study is needed for process optimization and cost reduction.