Autonomous Experimentation System for Electrolyte Materials Discovery

Autonomous Experimentation System for Electrolyte Materials Discovery

This is an electrolyte materials discovery system that integrates machine-learning-based experiment planning with automated experimentation technologies. The system can explore electrolyte compositions for a wide range of battery systems, including lithium-ion batteries and sodium-ion batteries. By utilizing the autonomous experimentation support software NIMO, experiments can be conducted using a various kinds of searching algorithms.

Other Protocols

• Electrode particle design based on reaction transport models
• Machine learning for evaluation of electrode structure and battery characteristics
• 3D Structure Analysis
• Operando Electrode Reaction Analysis
• Operando Nano X-ray CT Imaging
• Operando Soft X-ray Absorption Spectroscopy
• Operando Mechanical Characterization of Battery Cross‑Sections
• Explosion-Proof Operando X-ray CT Imaging
• Rapid safety screening with small batteries
• High-Throughput Pouch Cell Production and Evaluation Platform
• Cathode & Solid Electrolyte Database
• Data-Driven Inorganic Materials Design Tool