Materials Discovery

AI accelerates discovery and validation of novel materials for faster innovation and sustainability.

Business impact

• Time to market — Shortens development cycles by rapidly identifying and validating new materials
• R&D efficiency — Improves research productivity through automation and AI-guided experimentation
• Innovation rate — Increases novel material candidates and successful discoveries via AI generative models
• Cost reduction — Lowers experimental and development costs by reducing trial-and-error cycles
• Sustainability metrics — Enables design of environmentally friendly materials by integrating lifecycle assessment early

Data requirements

• Experimental synthesis data (Structured) — Used to train AI models on real-world material properties and synthesis outcomes
• Computational simulations (Numeric) — Provides theoretical property predictions and candidate screening via physics models
• Scientific literature and patents (Text) — Text data mined for synthesis recipes, constraints, and material characteristics
• High-throughput screening results (Numeric) — Generates large datasets for AI training and validation of material candidates
• Spectroscopy and imaging data (Image) — Characterizes material structure and stability for model feedback and validation

AI methods and techniques

• Generative AI — Generates novel material candidates conditioned on desired properties and constraints
• Predictive AI — Predicts material properties and synthesis outcomes to guide experimental design
• Agentic AI — Automates workflow planning and experimental execution in self-driving labs
• Symbolic AI — Incorporates domain knowledge and physics rules to constrain AI predictions

AI models and model families

GPT-4o, Claude, Llama, DeepMind GNoME, Microsoft Azure Quantum Elements, Diffusion models, Graph Neural Networks

Industries

Real-world evidence

15 documented case studies on record.

Companies using this: Asahi Kasei Corp, Cusp AI, Dunia Innovations, Lawrence Berkeley National Lab, Massachusetts Institute Technology MIT, Microsoft, Microsoft Research, Murata Manufacturing, North Carolina State University, Orbital Materials, SES S.A., Sepion Technologies, University Liverpool, Xtal Pi Holdings Limited, Zhejiang University.