The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

Replacing FE with machine learning. Given the recent advances in machine learning (ML) and data-driven methods, many branches of science and engineering have started implementing ML for different ...

Physics-based simulations, that staple of traditional HPC, may be evolving toward an emerging, AI-based technique that could radically accelerate simulation runs while cutting costs. Called “surrogate ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin ...

Machine learning, in which artificial intelligence autonomously acquires and applies new knowledge, will soon enable researchers to develop complex material systems in a purely virtual environment.

Using computational software and a proprietary machine learning technology that directly interfaces to the simulation kernel, Xcelium ML learns iteratively over an entire simulation regression.

Numerical simulation of materials-oriented ultra-precision diamond cutting: Review and outlook Mar 17, 2023 Machine learning aids in simulating dynamics of interacting atoms ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have used machine learning and supercomputer simulations to investigate how tiny gold nanoparticles bind to blood ...

Long overlooked and underestimated, glial cells – non-neuronal cells that support, protect and communicate with neurons – are finally stepping into the neuroscience spotlight.

The deep learning tool, Audioflow, performed almost as well as a specialist machine used in clinics, and achieves similar results to urology residents in assessing urinary flow.