Lithium Metal

Lithium metal research centers on overcoming challenges in developing high-energy-density batteries by addressing issues like dendrite formation and inconsistent performance. Current efforts leverage machine learning, particularly neural networks (including transformers and convolutional neural networks) and physics-informed neural networks, to accelerate simulations, predict battery performance metrics (like Coulombic efficiency), and analyze microscopic structures from imaging data like X-ray computed tomography. These advancements enable faster material discovery, improved battery design, and enhanced quality control, ultimately contributing to safer and more efficient energy storage solutions.