The claim
Materials discovery is experiment-constrained rather than compute-constrained; closing the physical loop can materially shorten materials R&D.
What has to hold for this route to work.
Experiments are the bottleneck. Compute can generate far more candidates than a physical lab can validate; the scarce resource is high-quality physical feedback.
Composition is not the material. Real performance also depends on structure, microstructure, processing and manufacturing history.
The lab must sit inside the AI loop. Hypothesis, synthesis, characterization, property testing and the next campaign must form a continuous feedback loop.
The loop must reach manufacturing. Sample throughput becomes industrial value only if the advantage survives scale-up, qualification and application.

