Matches in SemOpenAlex for { <https://semopenalex.org/work/W1187410758> ?p ?o ?g. }
- W1187410758 endingPage "48" @default.
- W1187410758 startingPage "42" @default.
- W1187410758 abstract "The native form of lignocellulosic biomass is resistant to enzymatic breakdown. A well-designed pretreatment that can promote enzymatic hydrolysis of biomass with reasonable processing cost is therefore necessary. To this end, a number of different types of pretreatment technologies have been developed with a common goal of making biomass more susceptible to enzymatic saccharification. Among those, a pretreatment method using alkaline reagent has emerged as one of the most viable process options due primarily to its strong pretreatment effect and relatively simple process scheme. The main features of alkaline pretreatment are that it selectively removes lignin without degrading carbohydrates, and increases porosity and surface area, thereby enhancing enzymatic hydrolysis. In this review, the leading alkaline pretreatment technologies are described and their features and comparative performances are discussed from a process viewpoint. Attempts were also made to give insights into the chemical and physical changes of biomass brought about by pretreatment." @default.
- W1187410758 created "2016-06-24" @default.
- W1187410758 creator A5026717849 @default.
- W1187410758 creator A5063507621 @default.
- W1187410758 creator A5075150288 @default.
- W1187410758 date "2016-01-01" @default.
- W1187410758 modified "2023-10-14" @default.
- W1187410758 title "A review on alkaline pretreatment technology for bioconversion of lignocellulosic biomass" @default.
- W1187410758 cites W1522459688 @default.
- W1187410758 cites W1550965069 @default.
- W1187410758 cites W1972235474 @default.
- W1187410758 cites W1974091558 @default.
- W1187410758 cites W1976874012 @default.
- W1187410758 cites W1980114983 @default.
- W1187410758 cites W1991018022 @default.
- W1187410758 cites W1993844771 @default.
- W1187410758 cites W1994653676 @default.
- W1187410758 cites W1995586898 @default.
- W1187410758 cites W2000746218 @default.
- W1187410758 cites W2002682883 @default.
- W1187410758 cites W2004378008 @default.
- W1187410758 cites W2015023129 @default.
- W1187410758 cites W2016429076 @default.
- W1187410758 cites W2041062214 @default.
- W1187410758 cites W2046663612 @default.
- W1187410758 cites W2047811710 @default.
- W1187410758 cites W2053030559 @default.
- W1187410758 cites W2053113581 @default.
- W1187410758 cites W2064110421 @default.
- W1187410758 cites W2065937359 @default.
- W1187410758 cites W2070511279 @default.
- W1187410758 cites W2091882995 @default.
- W1187410758 cites W2107106811 @default.
- W1187410758 cites W2110919001 @default.
- W1187410758 cites W2121829930 @default.
- W1187410758 cites W2140214874 @default.
- W1187410758 cites W2140743417 @default.
- W1187410758 cites W2143728833 @default.
- W1187410758 cites W2150081899 @default.
- W1187410758 cites W2154168297 @default.
- W1187410758 cites W2158627762 @default.
- W1187410758 cites W2166109955 @default.
- W1187410758 cites W2166515173 @default.
- W1187410758 cites W2169336460 @default.
- W1187410758 cites W2169790911 @default.
- W1187410758 cites W2214767249 @default.
- W1187410758 cites W2315124704 @default.
- W1187410758 cites W258783637 @default.
- W1187410758 cites W2935772463 @default.
- W1187410758 cites W422806581 @default.
- W1187410758 cites W4229528025 @default.
- W1187410758 cites W4242137597 @default.
- W1187410758 cites W4245414499 @default.
- W1187410758 cites W4245677564 @default.
- W1187410758 doi "https://doi.org/10.1016/j.biortech.2015.08.085" @default.
- W1187410758 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26341010" @default.
- W1187410758 hasPublicationYear "2016" @default.
- W1187410758 type Work @default.
- W1187410758 sameAs 1187410758 @default.
- W1187410758 citedByCount "983" @default.
- W1187410758 countsByYear W11874107582016 @default.
- W1187410758 countsByYear W11874107582017 @default.
- W1187410758 countsByYear W11874107582018 @default.
- W1187410758 countsByYear W11874107582019 @default.
- W1187410758 countsByYear W11874107582020 @default.
- W1187410758 countsByYear W11874107582021 @default.
- W1187410758 countsByYear W11874107582022 @default.
- W1187410758 countsByYear W11874107582023 @default.
- W1187410758 crossrefType "journal-article" @default.
- W1187410758 hasAuthorship W1187410758A5026717849 @default.
- W1187410758 hasAuthorship W1187410758A5063507621 @default.
- W1187410758 hasAuthorship W1187410758A5075150288 @default.
- W1187410758 hasConcept C100544194 @default.
- W1187410758 hasConcept C115540264 @default.
- W1187410758 hasConcept C127413603 @default.
- W1187410758 hasConcept C178790620 @default.
- W1187410758 hasConcept C185592680 @default.
- W1187410758 hasConcept C206139338 @default.
- W1187410758 hasConcept C2778234585 @default.
- W1187410758 hasConcept C2780074830 @default.
- W1187410758 hasConcept C2780301381 @default.
- W1187410758 hasConcept C2781052789 @default.
- W1187410758 hasConcept C528095902 @default.
- W1187410758 hasConcept C53270655 @default.
- W1187410758 hasConcept C6557445 @default.
- W1187410758 hasConcept C86803240 @default.
- W1187410758 hasConcept C94412978 @default.
- W1187410758 hasConceptScore W1187410758C100544194 @default.
- W1187410758 hasConceptScore W1187410758C115540264 @default.
- W1187410758 hasConceptScore W1187410758C127413603 @default.
- W1187410758 hasConceptScore W1187410758C178790620 @default.
- W1187410758 hasConceptScore W1187410758C185592680 @default.
- W1187410758 hasConceptScore W1187410758C206139338 @default.
- W1187410758 hasConceptScore W1187410758C2778234585 @default.
- W1187410758 hasConceptScore W1187410758C2780074830 @default.
- W1187410758 hasConceptScore W1187410758C2780301381 @default.
- W1187410758 hasConceptScore W1187410758C2781052789 @default.
- W1187410758 hasConceptScore W1187410758C528095902 @default.