This study proposed an integrated generative artificial intelligence(AI)assisted literature review method,focusing on improving the efficiency and depth of literature review research in the field of green hydrogen preparation.Green hydrogen preparation,as a key technical path to achieve the goal of carbon neutrality,covers a variety of technologies such as electrolytic water hydrogen production,photolytic water hydrogen production,and biological hydrogen production.In this study,the AI large language model and thinking chain prompt method were used to optimize the literature retrieval strategy,build a comprehensive knowledge base,and configure an intelligent agent"green hydrogen intelligent analyst"for in-depth analysis.By constructing a review outline using the thought tree method,this study not only ensures the comprehensiveness and systemicity of the literature review,but also shows the ability of the agent to provide accurate qualitative description and quantitative technical index data in the specific technical description of green hydrogen preparation technology.For example,the principles,characteristics,energy consumption,efficiency,and application scenarios of the different methods of PEM,Alkaline,and Solid Oxide hydrogen production technology are compared in detail.In addition,the interactive question and answer function of the agent enhances the flexibility and pertinence of the research,and validates the advantages of the method flow in accurately extracting key information.
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