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Foundation potentials (FPs), i.e., universal machine learning interatomic potentials with periodic-table-wide coverage, are now proliferating. New pre-trained FPs seem to appear almost daily, making hyped-up claims about performance. For those not deep in the field, it’s becoming increasingly difficult to separate signal from noise. Here’s my expert, very opinionated take on how to choose an FP that actually fits your needs. 1️⃣ Dataset quality and size drive everything. Arch

At Materialyze.AI Lab, we are on a mission to pioneer the integration of theory, experiments, and AI to accelerate the discovery and deployment of breakthrough materials. We welcome postdoctoral and PhD applicants. We believe that the right team can make all the difference. Our Core Values At Materialyze.AI Lab, our core values guide everything we do. Here are the key principles we stand by: Integrity : We practice integrity in all forms. We are honest and fair to fellow grou