AI-assisted battery material characterization and data analysis
With the rapid development of commercial lithium-ion batteries(LIBs),traditional experimental methods face challenges in handling complex data and optimizing designs.Recently,artificial intelligence(AI)technology has shown great potential in data processing,pattern recognition,and predictive analysis,providing new solutions for the research and development of LIBs.This paper reviews the application of AI in the characterization of LIB materials,including spectroscopic and imaging techniques.AI improves the accuracy and efficiency of spectroscopic analysis through feature extraction and data analysis.Combined with advanced imaging techniques,researchers can now explore the microstructure of materials with unprecedented precision and speed using AI.AI applications in image recognition,classification,and segmentation further enhance data processing efficiency and accuracy.In the future,AI will play a crucial role in the battery community through technological innovation and interdisciplinary collaboration,driving the development and application of high-performance batteries.
万方数据
维普
