The application of large language models in energy storage research
In the pursuit of carbon neutrality,energy storage technology plays an increasingly crucial role in modern society.Addressing future challenges requires innovative methods in energy storage research,given its interdisciplinary and information-intensive nature.With the rapid development of artificial intelligence technology,large language models(LLMs)have achieved significant success in various domains,including text processing,information collection and integration,and picture and video generation.Moreover,the application of LLMs has extended to natural science research,demonstrating promising potential for improving research efficiency.Thus,LLMs are expected to assist in addressing future challenges in energy storage science and technology.This paper first focuses on ChatGPT and reviews AI advancements and LLMs,analyzing their impact on civil use and scientific research,particularly focusing on domestic LLMs.Subsequently,it discusses the basic concepts and fundamentals of LLMs and their application in energy storage,covering information processing,information generation,and system integration.Detailed examples are provided to illustrate the effectiveness of these new methods.Finally,this study outlines the remaining challenges and future development directions of the interdisciplinary nature of LLMs and energy storage.
large language modelartificial intelligenceenergy storage technologysecondary battery
万方数据
维普
