Abstract:

Biomass pyrolysis can produce high-grade energy products such as biochar, biogas and bio-oil, which has the advantages of high efficiency and multi-product utilization. However, the products obtained from direct pyrolysis with poor quality are inconducive to realizing high-value utilization. It is urgent to regulate and optimize the process of biomass pyrolysis. Starting from the optimization strategies for pyrolysis reactions, this review systematically outlined the influences of feedstock selection, pretreatment, pyrolysis parameters, reactor types, catalysts, and auxiliary techniques on the pyrolysis conversion process. Additionally, the methods for pyrolysis reaction optimization and product regulation were comprehensively summarized. To realize the green, low-carbon and value-added utilization of biomass, the regulation of pyrolysis products was reviewed from three parts: directional preparation of hydrogen-rich syngas, selective tuning of hydrocarbon liquid fuel, biochar structure tailoring and high-value utilization. Finally, the challenges and development prospects of biomass pyrolysis were summarized. The introduction of mhachine learning methods to accelerate the development of pyrolysis was also discussed, providing an important reference for the efficient pyrolysis conversion of biomass.

Key words: biomass, pyrolysis, catalyst, directional regulation, low-carbon utilization, machine learning

摘要：

生物质热解转化可制备炭、气、油等高品位能源产品，具有高效可控、多产物利用等优势。然而，生物质直接热解所得产物品质不高，无法实现高附加值利用，亟需对生物质热解反应进行调控与优化。本文从热解反应的优化策略出发，系统概述了原料选择及预处理、热解参数与反应器类型、催化剂及辅助热解技术的引入对热解转化过程的影响，全面总结了热解反应优化与产物调控方法。从富氢合成气定向制备、烃类液体燃料选择调控、炭结构调变与高值利用三部分综述了热解产物的定向调控，以期实现生物质的绿色、低碳和增值利用。最后总结了生物质热解转化的挑战与发展前景，同时对机器学习方法的引入加速热解领域的发展进行了展望，为生物质高效热解转化提供一定的参考价值。

关键词: 生物质, 热解, 催化剂, 定向调控, 低碳利用, 机器学习