By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...

Artificial intelligence and machine learning are rapidly transforming scientific research, with researchers across multiple areas of physics leading the development and application of these tools. To ...

One would imagine that an AI capable of solving the hardest Olympiad problems would naturally produce novel scientific ...

This post examines the evolution of robotic laboratories and outlines the key breakthroughs required to advance toward genuinely embodied scientific intelligence. The earliest defining milestone of ...

Now in its 70th year, the Greater New Orleans Science and Engineering Fair is gearing up for another round of STEM presentations. Over 300 middle- and high-school students will congregate at Tulane ...

High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

SANTA CLARA, CA, Feb. 12, 2026 (GLOBE NEWSWIRE) -- SANTA CLARA, CA - February 12, 2026 - - ...