木质纤维素生物质光催化转化研究进展:途径、局限与展望

IF 5.1 Q2 ENGINEERING, CHEMICAL
Kavitha S, Yukesh Kannah Ravi, Ginni G, Lise Appels, Mieczysław Łapkowski, Yogendra Kumar Mishra, Palanivelu Kandasamy, Palanichamy Rajaguru, Pugalenthi Velan and Rajesh Banu Jeyakumar*, 
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引用次数: 0

摘要

木质纤维素生物质(LCB)是回收燃料和高附加值产品的丰富资源。尽管进行了广泛的调查和研究,但LCB效力的完全解锁尚未完成。在温和条件下利用可再生太阳能的LCB光催化转化已被公认为当前可持续发展的热点研究课题。为了有效的实际实施,已经确定了许多技术挑战。简而言之,光催化转化氧化LCB中的Cβ─O/Cα─Cβ键以回收燃料和生化物质。从化学的角度来看,通过适当调节氧化基和自由基中间体的类型和回收率来优化氧化基和自由基中间体的排他相互作用对于选择性地生成理想的产物至关重要。本文综述了通过活性氧(ROS)行为优化和系统设计对LCB选择性转化的机制途径的最新见解。此外,本文还介绍了LCB及其组分的光催化以及木质素、天然生物质增值、纤维素、半纤维素及其衍生物的选择性氧化的最新进展。此外,还详细讨论了通过LCB光催化升级生物平台和发电的新方法。讨论了利用LCB光催化提高LCB光催化转化活性的前景和机遇。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recent Advances in Photocatalytic Conversion of Lignocellulosic Biomass: Routes, Limitations, and Outlook

Lignocellulosic biomass (LCB) is an abundant resource for recovering fuels and value-added products. Despite extensive investigations and research, the complete unlocking of LCB potency has yet to be accomplished. The photocatalytic conversion of LCB, which utilizes renewable solar light under mild conditions, has been recognized as the hottest current research topic receiving attention for sustainable development. Numerous technical challenges have been identified for effective practical implementations. In brief, photocatalytic conversion oxidizes Cβ─O/Cα─Cβ linkages in LCB to recover fuels and biochemicals. From a chemical viewpoint, optimizing the exclusive interaction of oxidizing radical groups and radical intermediates through suitable regulation of their type and recovery is crucial for selectively generating desirable products. This review provides recent insights into the mechanistic pathways of the selective conversion of LCB via reactive oxygen species (ROS) behavior optimization and system design. In addition, this review highlights the up-to-date achievements in the photocatalysis of LCB and its components as well as the selective oxidation of the prominent linkages of lignin, native biomass valorization, cellulose, hemicellulose, and its derivatives. Further, upgrading of bioplatforms and electricity generation via LCB photocatalysis is discussed in detail as a novel approach. The prospects and opportunities of using LCB photocatalysis to improve the viability of photocatalytic conversion of LCB are also discussed.

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来源期刊
ACS Engineering Au
ACS Engineering Au 化学工程技术-
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期刊介绍: )ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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