Using Empire AI to Develop Next Generation Battery Materials

Prof. Mark Tuckerman | NYU
Using AI-driven simulations to design sustainable battery materials that use green compounds and reduce reliance on environmentally harmful mining.

Challenge

As demand for renewable energy grows, so does the need for large-scale energy storage solutions. However, most modern batteries rely on lithium and other critical minerals, whose extraction produces approximately 1.3 million tons of carbon emissions annually and can cause significant environmental degradation.

The challenge lies in discovering alternative materials that are both efficient and sustainable. This requires understanding complex chemical interactions at the molecular level — a process that involves simulating countless potential material combinations.

Traditional computational approaches are too slow and limited to explore this vast design space effectively.

Researcher’s Approach Using Empire AI

The team uses AI to predict  chemical interactions to design new organic battery materials.
Empire AI runs large-scale molecular simulations driven by the AI models.

Empire AI Enables

• Exploration of new materials
• Faster AI-driven simulations
• Improved prediction accuracy

Without Empire AI, Innovation would be slower and more limited.

Potential Impacts

• Enables development of cleaner, more sustainable battery technologies
• Reduces environmental damage from mineral extraction
• Supports the transition to renewable energy systems
• Strengthens New York’s role in clean energy innovation

For more information:

• Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes
• Structured electrolytes facilitate Grotthuss-type transport for enhanced proton-coupled electron transfer reactions
• Breakthrough Conductivity Enhancement in Deep Eutectic Solvents via Grotthuss-Type Proton Transport
• Elucidating the Proton Transport Pathways in Liquid Imidazole with First-Principles Molecular Dynamics