An exhaustive guide to Explainable AI for Material Science & Informatics

High-performance AI models have struggled to explain their predictions. This white paper shares a practical, solution-centric application of Explainable AI for material synthesis using SHAP.

What's inside

Why high-performing models still fail to explain their predictions, and what it costs R&D teams
A closed-loop strategy that pairs AI engineers with polymer scientists
Explainable AI for material synthesis with SHAP, including code and fundamental guidelines
Lessons from building and enhancing the Polymerize Labs AI engine over time