Researchers from the University of California, San Diego, have developed a machine learning-based system that detects the evolution of lithium components inside a battery during operation, according to a study published in the npj Computational Materials journal. The team used automatised image segmentation to split micro-CT battery scans into components including dendrites (lithium structures growing on electrode surfaces) and deposited lithium. The system measured changes in each component’s volume and the spatial correlation between different elements. The researchers anticipate potential applications in automating quality control checks on energy devices.
The researchers do
Lithium Plating Dynamics Detected in Solid-State Batteries Using X-ray CT and Machine Learning
Date:
Frequently Asked Questions (FAQs) Related to the Above News
Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.
More like thisRelated
Enhancing Credit Risk Assessments with Machine Learning Algorithms
Enhance credit risk assessments with machine learning algorithms to make data-driven decisions and gain a competitive edge in the market.
Foreign Investors Boost Asian Stocks in June with $7.16B Inflows
Foreign investors drove a $7.16B boost in Asian stocks in June, fueled by AI industry growth and positive Fed signals.
Samsung Launches Galaxy Book 4 Ultra with Intel Core Ultra AI Processors in India
Samsung launches Galaxy Book 4 Ultra in India with Intel Core Ultra AI processors, Windows 11, and advanced features to compete in the market.
Motorola Razr 50 Ultra Unveiled: Specs, Pricing, and Prime Day Sale Offer
Introducing the Motorola Razr 50 Ultra with a 4-inch pOLED 165Hz cover screen and Snapdragon 8s Gen 3 chipset. Get all the details and Prime Day sale offer here!