Solid-state batteries (SSBs) are hailed as the future of energy storage, promising higher energy density, improved safety, and longer lifespan compared to conventional lithium-ion systems. Yet, their path to commercialization is riddled with challenges—complex material interactions, interface instability, and sluggish ion transport, to name a few. Enter artificial intelligence. In a groundbreaking review published in N ano- M icro L etters , researchers from Soochow University and Nanjing University, led by Professors Sheng Wang and Linwei Yu, unveil how machine learning (ML) is accelerating every stage of solid-state battery development—from atom to application.
Why AI Matters Now
Smart Strategies for Smarter Batteries
1. ML-Guided Material Screening
2. AI for Battery Management Systems
3. Decoding Ion Transport
Future Frontiers
From lab to grid, AI is not just a tool—it’s the catalyst turning solid-state batteries from laboratory curiosities into commercial juggernauts. Stay tuned as Professors Yu, and their teams redefine what’s possible in energy storage.
Nano-Micro Letters
Experimental study
Artificial Intelligence Empowers Solid-State Batteries for Material Screening and Performance Evaluation
6-Jun-2025