![]() Fast and highly accurate electronic properties of materials, interfaces, and gate stack (e.g.Examples include amorphous HfO2 and GST phase-change materials, HKMG stacks, etc.Use ML MTPs for obtaining realistic crystalline, amorphous materials, interface, gate stack structures, simulating dopant diffusion, thermal transport, and crystallization. ![]() Use MTPs with MD, nudged elastic band and accelerated MD methods, such as force-bias Monte Carlo, now also with pressure control, to sample rare events and unlock slow mechanisms.Employ provided MTP potentials for Si or develop potentials for new materials and problems using automated training and simulation workflows.Obtain realistic amorphous material and liquid structures, in particular, at high temperatures.Active learning MTP simulations to automatically add DFT training data during molecular dynamics (MD) simulations.For cases where no conventional potentials exist or need better accuracy.One of the most accurate and efficient ML potentials on the market.Trained on a dataset of ab-initio calculations.100-1000x faster generation of realistic structures of complex multi-element crystalline, amorphous materials & interfaces, defect and dopant migration barriers, thermal transport, crystallization vs.
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