化工学报2025，Vol.76Issue(8)：3805-3821,17.DOI:10.11949/0438-1157.20250289
机器学习驱动液态有机储氢技术的系统优化
Machine learning drives system optimization of liquid organic hydrogen storage technology
摘要
Abstract
Under the dual challenges of global climate change and energy structure transformation,the development of efficient and clean hydrogen storage and transportation technology has become a key path to achieve the goal of carbon neutrality.Liquid organic hydrogen carriers(LOHCs)technology has become a research hotspot in the field of hydrogen energy storage and transportation due to its high safety and the ability to utilize existing infrastructure.However,the slow dehydrogenation kinetics and strong catalyst dependence limit the industrialization process.In recent years,breakthroughs in machine learning(ML)in new material design,reaction optimization,and data-driven modeling have injected new momentum into LOHCs technology.This paper focuses on the latest research of ML in aspects such as the molecular screening of LOHCs,catalyst design,and reaction condition optimization,points out the current research shortcomings,and prospects the future development directions.关键词
有机化合物/制氢/机器学习/优化设计/脱氢催化剂Key words
organic compounds/hydrogen production/machine learning/optimal design/dehydrogenation catalyst分类
化学化工引用本文复制引用
范夏雨,孙建辰,李可莹,姚馨雅,商辉..机器学习驱动液态有机储氢技术的系统优化[J].化工学报,2025,76(8):3805-3821,17.基金项目
碳中和联合研究院自主基金项目(CNIF20240102) （CNIF20240102）
