I worked on projects in this area and honestly this isn’t far off the mark. Industry is desperate to get new materials to market faster, but after seeing the en

I worked on projects in this area and honestly this isn’t far off the mark. Industry is desperate to get new materials to market faster, but after seeing the entire development chain, the scale-up is a far greater bottleneck than the generation of promising leads. You can even see some of it buried at the end of this paper - they’re using some optical property as a surrogate for catalytic activity, acknowledging that > Catalyst testing for water oxidation is far more expensive than the optical screening from our high throughput workflow, and even though there is no known connection between the optical properties and the catalytic properties, we use the analysis of optical properties to select a small number of compositions for catalyst testing I’m not saying these high throughput screening techniques don’t have value - they do and they have their place. They get overhyped because software companies see a potential ML application and throw their weight behind it. However the ML-based search algorithm is usually the lowest value-add to the process. Automating the characterization (the part the Caltech people did.. built a custom microscope) is the biggest de-bottleneck in this workflow.