Muhammad Sheraz, Lixia Cao, Shengyong Zhao, Haigang Gao, Panchan Dansawad, Cong Xue, Yanxiang Li, Wangliang Li
{"title":"Lignocellulosic Biomass Pretreatment Methods and Application of Extracted Fractions","authors":"Muhammad Sheraz, Lixia Cao, Shengyong Zhao, Haigang Gao, Panchan Dansawad, Cong Xue, Yanxiang Li, Wangliang Li","doi":"10.1007/s13369-024-09930-6","DOIUrl":null,"url":null,"abstract":"<div><p>Lignocellulosic biomass (LCB) is a promising renewable energy source. However, its efficient utilization, extraction of different fractions like cellulose, hemicellulose and lignin, and conversion to value-added products require pretreatment to break down its complex structure. This review explores various conventional and green pretreatment techniques for LCB fractionation into cellulose, hemicellulose and lignin. Besides, comparative analysis evaluates the merits/demerits of each method based on the treatment conditions and yield of the extracted fractions. It emphasizes on the importance of developing efficient, eco-friendly and cost-effective green pretreatment techniques to enhance the utilization of LCB for extracting its constituents and creating valuable products. Finally, the review explores the emerging role of machine learning-assisted pretreatment processes for optimizing process efficiency and product yield by appropriate model selection. It also discusses the application of these extracted fractions in various industries such as oil/water separation, effluent processing and electrochemistry especially in electrodes.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"50 6","pages":"3717 - 3736"},"PeriodicalIF":2.6000,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Arabian Journal for Science and Engineering","FirstCategoryId":"103","ListUrlMain":"https://link.springer.com/article/10.1007/s13369-024-09930-6","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Lignocellulosic biomass (LCB) is a promising renewable energy source. However, its efficient utilization, extraction of different fractions like cellulose, hemicellulose and lignin, and conversion to value-added products require pretreatment to break down its complex structure. This review explores various conventional and green pretreatment techniques for LCB fractionation into cellulose, hemicellulose and lignin. Besides, comparative analysis evaluates the merits/demerits of each method based on the treatment conditions and yield of the extracted fractions. It emphasizes on the importance of developing efficient, eco-friendly and cost-effective green pretreatment techniques to enhance the utilization of LCB for extracting its constituents and creating valuable products. Finally, the review explores the emerging role of machine learning-assisted pretreatment processes for optimizing process efficiency and product yield by appropriate model selection. It also discusses the application of these extracted fractions in various industries such as oil/water separation, effluent processing and electrochemistry especially in electrodes.
期刊介绍:
King Fahd University of Petroleum & Minerals (KFUPM) partnered with Springer to publish the Arabian Journal for Science and Engineering (AJSE).
AJSE, which has been published by KFUPM since 1975, is a recognized national, regional and international journal that provides a great opportunity for the dissemination of research advances from the Kingdom of Saudi Arabia, MENA and the world.