A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

Spin density symmetry breaking in single-atom catalysts can significantly enhance the performance of hydrogen evolution ...

Artificial intelligence (AI) and machine learning (ML) hold significant promise in advancing the field of toxicology by ...

A research team led by Prof. Zhonghua Li from Harbin Institute of Technology has discovered how spin density symmetry breaking in single-atom ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently ...

Artificial intelligence has become an integral part of modern cybersecurity operations. As digital threats grow in scale and ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

A new review shows how AI helps food companies predict formulation, processing, and sensory outcomes. AI does not ...

In a constantly evolving anti-ageing market, brands are facing a dual challenge: to demonstrate the efficacy of their ...