Materials by Machines: A Review on Intuition and Knowledge-driven Learning for Rapid Discovery and Optimization

• Four AI frontiers integrated into one closed-loop materials discovery cycle. • Foundation models and LLMs propose viable compounds and synthesis routes. • Explainable AI interprets predictions and surfaces candidate design rules. • Causal inference moves beyond correlation to identify property mechanisms. • Autonomous laboratories run, analyze, and learn from experiments continuously.