A firefly-inspired AI framework makes atomic structure prediction more robust by combining multimodal search with an uncertainty-aware machine learning technique. The method improves efficiency for ...

Overview By closely mimicking atom behavior, quantum processors offer the exact simulation needed to discover and design ...

Through a combination of smarter material choices and machine learning techniques, a team led by Sarah Haigh at the University of Manchester showed how these graphene “nano-aquariums” can work with ...

Addressing the VAKTAVYA 2026 organised by Hindu College, Union Minister of State (Independent Charge) for Science & ...

A web-based platform integrating generalized global neural network potentials and diffusion generative models was developed ...

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful ...

U.S. Secretary of Energy Chris Wright, Under Secretary for Science Darío Gil, and ARPA-E Director Conner Prochaska visited ...

In a recent study published in Nature Communications, researchers created a memristor that uses a built-in oxygen gradient to ...

The 2026 Symposium, themed “Innovation and Resilience in a Changing World – Safeguards as a Shared Responsibility,” comes at a pivotal moment for the global nuclear sector.

From self‑doubt to success, two computer science students gained confidence through experiential learning that turned theory ...