Solid Power (SLDP) investor relations material

Role of artificial intelligence and materials informatics

• AI and materials informatics accelerate solid-state electrolyte design, integration, and scale-up, targeting faster, more reliable, and innovative outcomes.

• Machine learning models are integrated across R&D, process engineering, and production, leveraging over 10 years of proprietary and open-source data.

• Physics-aware AI solutions are tailored for robustness, interpretability, and sustainable deployment with minimal ongoing support.

Impact of materials informatics & modeling

• Centralized data platforms and custom AI pipelines have enabled ~50x faster data evaluation and rapid materials discovery.

• Over 18 months, 5+ patent disclosures, 2 journal publications, and a public GitHub repo were produced.

• Awarded significant computational resources for AI/ML on solid-state electrolytes.

Ultra-early cell performance prediction & failure mode detection

• SPARK-IT platform predicts cell performance and failure modes within minutes after formation, compressing months of R&D into days.

• Achieves <5% RMSE in time series prediction and 85%+ accuracy in failure cause assignment.

• Combines neural networks with physics-based models for interpretable, mechanism-aware diagnostics.

• Enables rapid, actionable feedback for process optimization and customer support.