RESEARCH PROGRESS OF ARTIFICIAL INTELLIGENCE IN THE FIELD OF RENEWABLE ENERGY MATERIALS RESEARCH AND DEVELOPMENT
Keywords:
Material preparation, Artificial Intelligence (AI), Renewable energy, Material optimizationAbstract
In recent years, traditional energy sources such as coal, oil, and natural gas have been gradually depleted, and the use of large amounts of fossil energy has caused environmental pollution. In order to reduce carbon dioxide emissions, the country actively promotes wind, The development of renewable energy sources such as light, hydropower, and hydrogen energy, and the key to the promotion and application of these energy technologies is the research and development of new materials. At present, the development of new materials mainly relies on researchers to conduct experimental optimization based on the material structure and its expected catalytic activity for a specific system, resulting in a slow development process of new materials. With the further development of computational materials science, researchers have integrated a large number of material databases on material structure and performance characterization, and gradually optimized and screened new materials through comparison. This paper reviews the current design ideas and synthesis methods of material development, focusing on artificial intelligence (AI) and expounding the recent research based on AI Method design, models and algorithms in the process of preparing renewable energy materials, and summarized AI The research significance and development process used in material design, and finally the AI Methods The development of design and preparation of renewable energy materials is prospected, the material optimization model proposed by this research group is introduced, and cases of the model's successful application in material optimization for hydrogen evolution from electrolysis of water and hydrogen production from sodium borohydride are listed. The future, AI The technology has very broad application prospects in theoretical calculations, synthetic design, performance prediction, and material microstructure characterization analysis of new materials.References
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