Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

Through a novel combination of machine learning and atomic force microscopy, researchers in China have unveiled the molecular ...

And unlike traditional machine-learning, assisted-feature extraction in spectroscopy, the new method pinpoints phase transitions based on characteristic spectral features inside an energy gap, making ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Jaipal Reddy Padamati's journey in the Information Technology sector is a testament to his relentless pursuit of knowledge and passion for innovation. Born and raised in Hyderabad, India, Padamati's ...

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...

This study leverages advanced genomics and machine learning to refine the understanding of key fruit quality traits in ...

With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.