Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

In a recent perspective published in Nature, Lawrence Livermore National Laboratory (LLNL) scientists and international collaborators outline key challenges and future directions in using machine ...

Combining concepts from statistical physics with machine learning, researchers at the University of Bayreuth have shown that highly accurate and efficient predictions can now be made as to whether a ...

A case study in aerospace manufacturing provides an overview of how physics-informed digital twin systems transform robotics processes—from adaptive process planning and real-time process monitoring ...

From DFT calculation to ML prediction, the potential catalysts with highly active and selective performance are efficiently screened by four ML models, i.e. decision tree, random forest, support ...

Since the first FEA solver, Nastran, was developed for NASA in the 1960s, the simulation software industry has contended with a number of hurdles. For one, while the software (FEA, CFD, CEM) is ...

AI has started to emerge as one of the most effective technologies being used in cosmology lately. The power of machine learning technologies is seen when analysing galaxies and models that predict ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

LOS ANGELES--(BUSINESS WIRE)--Quilter, the first and only company to publicly demonstrate fully autonomous PCB layout through physics-driven AI, today announced $25 million in Series B funding led by ...

The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and ...

This paper systematically reviews the research progress and application of machine learning in adsorption processes. By virtue of outstanding nonlinear modeling and data mining capabilities, machine ...