Revolutionizing Battery Innovation through Artificial Intelligence: The Next Frontier
Source abstract
Abstract
ABSTRACT The global thirst for sustainable energy storage systems has accelerated the limitations of conventional battery research and development methods. The complex nature of battery chemistries of cathode, anode, electrolytes and their performance metrics demands quicker, cleverer, and more extrapolative methodologies. In this aspect, Artificial Intelligence (AI) has arisen as a metamorphic tool, enabling the fast‐tracked invention, and design of battery materials and systems. This perspective article explores the growing incorporation of AI into battery research and development, and its applications in materials design, performance prognostication, troubleshooting, and process control in fabrication. Moreover, this work inspects contemporary innovations, current challenges, and the potential for AI to revolutionize the entire battery eco‐system, from atom‐level simulations to industrial‐scale production.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Machine Learning in Materials Science · Advancements in Battery Materials · Advanced Battery Technologies Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Council of Scientific and Industrial Research ‐ Central Electrochemical Research Institute (CECRI) ‐ Chennai Unit Chennai India
Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
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