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2021
Conference Paper
Titel
Unravelling an efficient fractionation of complex mixed lignocellulosic feedstocks in a pilot scale biorefinery
Abstract
Successful future lignocellulosic biorefineries should combine both â high efficiency and flexibility. An efficient fractionation is necessary in order to obtain all major fractions - cellulose, lignin and hemicellulose â at high yields and qualities. Flexibility for different feedstocks or even mixtures of them leads to an economic advantage. Low requirements on a feedstock enables the use of un- or underutilized streams and creates independence from the individual product markets. As fractionation conditions usually have to be adjusted to each feedstock, this is a challenge. Within the H2020-BBI JU project UNRAVEL (www.unravel-bbi.eu) an innovative concept for the pretreatment of different kinds of hardwood and agricultural feedstocks is developed and scaled up to pilot scale. A special focus lies on the processing of a mix of feedstocks for the first time on this scale. The process chain involves pre-extraction, FABIOLA⢠organosolv fractionation [1] and LigniSe p advanced continuous lignin precipitation with integrated solvent recovery [2]. Pre-extraction is applied to unify the feedstock properties and to increase product purity. The extract can be used for renutrition of soil or isolation of high value products like betulin from birch bark. Using acetone as a solvent, the FABIOLA⢠process was designed to enable a low temperature organosolv pretreatment [1].It results in a relatively unaltered lignin fraction, high cellulose yield and high yields of monomeric hemicellulose sugars compared to ethanol pulping. Furthermore solvent recovery is efficient with low energy demand. In this concept, it is integrated in an advanced continuous lignin precipitation by solvent evaporation [2]. The pulp fraction is saccharified in an enzymatic hydrolysis and all sugar streams are concentrated to a syrup. In the project, the lignin is tested in PUR/PIR foams and bitumen applications.
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