Machine learning accelerates catalyst discovery by combining theory, AI, and experiments to identify efficient materials for ...

Achieving high efficiency, long operational lifetime, and excellent color purity is essential for organic light-emitting ...

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

AI-designed materials cool better than paint and save energy. Their uses span homes, clothes, and space tech. A new class of ...

Model for predicting molecular crystal properties is readily adaptable to specific tasks, even with limited data ...

Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties even with limited ...

Novel machine learning model can predict material failure before it happens. ScienceDaily . Retrieved July 12, 2025 from www.sciencedaily.com / releases / 2025 / 04 / 250416135453.htm ...

To cut emissions and reduce energy bills, an international engineering team has created the whitest paint coating yet—with ...

The newly invented materials, called meta-emitters, could reduce the level of heat the buildings absorb and decrease the cost ...

Researchers in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a machine learning framework that can predict with quantum-level accuracy how materials ...

Through the program, he intends to use computational materials modeling expedited by machine learning to advance the science of space hardened electronics. The fellowship provides four years of ...

Both generative AI and machine learning use algorithms to address complex challenges, but generative AI uses more sophisticated modeling and more advanced algorithms to add a creative element ...