A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has made strides in the theoretical design of nonlinear optical (NLO) materials by ...

Researchers have developed an integrated framework for estimating battery state of health, or SOH, by combining incremental ...

STANFORD, California, USA, 24 June 2025 – In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is revolutionizing our understanding of brain ...

Making high-performance proteins for medicines or consumer products can take trial after trial of tweaks, experiments and fine-tuning. A new machine learning framework squeezes all that into a single ...

Underpinnings and advantages of the scDiffEq model The new machine learning-based framework developed by the researchers models how cells change over time using neural stochastic differential ...

Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control. AI-driven robotics and digital twins are closing the gap between simulation and ...

Urea is an extremely important chemical, especially for fertilizers. But, making urea is energy intensive and relies heavily ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

For his research in machine learning-based electron density prediction, Michigan Tech researcher Susanta Ghosh has been recognized with one of the National Science Foundation's highest honors. The NSF ...

Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...