FluxMateria has launched a deterministic physics-based screening platform that claims to outperform traditional Density Functional Theory (DFT) by a factor of 3.6 million. By eschewing AI in favor of a unified physics kernel, the platform aims to revolutionize molecular and materials R&D workflows.
FluxMateria has launched a deterministic physics-based screening platform that claims to outperform traditional Density Functional Theory (DFT) by a factor of 3.6 million. By eschewing AI in favor of a unified physics kernel, the Sardinia-based startup aims to revolutionize R&D across molecular and material sciences.
FluxMateria has launched a deterministic physics-based screening platform that outperforms traditional Density Functional Theory (DFT) by a factor of 3.6 million. The unified engine allows for rapid discovery in molecular and materials science without the use of AI, potentially accelerating the development of green technologies.
FluxMateria has launched a deterministic physics-based screening platform that operates 3.6 million times faster than traditional Density Functional Theory (DFT). By eschewing probabilistic AI in favor of a unified physics kernel, the platform offers a breakthrough in molecular and materials R&D efficiency.