Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...

Understanding and predicting complex physical systems remain significant challenges in scientific research and engineering. Machine learning models, while powerful, often fail to follow the ...

A case study in aerospace manufacturing provides an overview of how physics-informed digital twin systems transform robotics processes—from adaptive process planning and real-time process monitoring ...

Complex network theory has become a key analytical framework in modern physics for studying structure, dynamics, and emergent behaviour in complex systems.

In a new study Bar-Ilan University Prof. Ido Kanter examines how the classic idea of “more is different” applies to AI, finding a contrast between physics and artificial intelligence: from an ...

Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots to scalable, physics-based intelligence across assets. Here’s how SciML can ...

A breakthrough deterministic physics kernel delivers molecular, materials, and reaction screening across three ...