Interface engineering and safety in solid-state batteries: Advancing from human-centered insights to AI-driven...

Area of Science:

• Materials Science
• Electrochemistry
• Energy Storage

Background:

• Solid-state batteries (SSBs) promise superior safety and energy density over traditional lithium-ion batteries (LIBs).
• Key challenges include interface engineering for stable performance and preventing lithium dendrite formation, which impacts safety and reliability.
• Overcoming these interfacial issues is crucial for widespread SSB adoption.

Purpose of the Study:

• To highlight the critical role of interface engineering in solid-state battery development.
• To explore the potential of artificial intelligence (AI) and machine learning (ML) in optimizing SSB interfaces.
• To address challenges hindering SSB commercialization in applications like electric vehicles and grid storage.

Main Methods:

• Review of interface engineering strategies for SSBs.
• Discussion of AI/ML applications in predictive modeling of interfacial behavior.
• Analysis of methods to enhance mechanical stability and prevent dendrite growth.

Main Results:

• Effective interface engineering is vital for mitigating resistance, improving mechanical stability, and preventing thermal runaway.
• AI/ML accelerates material discovery and failure prediction for SSB interfaces.
• Addressing interfacial challenges is key to unlocking SSB potential.

Conclusions:

• Interface engineering, supported by AI/ML, is pivotal for safe and reliable solid-state battery operation.
• These advancements pave the way for commercializing SSBs in demanding applications.
• Optimized interfaces are fundamental to realizing the full benefits of SSB technology.