The search for next-generation electronic materials often starts with studying the Fermi surface, which serves as a map of a ...

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...

Schematic diagrams illustrating the atomic arrangement of an MoS₂ specimen observed using 4D-STEM, showing atomic-scale mapping in real-space coordinates x and y and corresponding diffraction patterns ...

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

A new study shows that combining machine learning with advanced material engineering can significantly improve the ...

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...

Google DeepMind, in collaboration with BIFOLD and the Technical University of Berlin, has developed Euclidean Fast Attention (EFA), a machine learning method that efficiently models long-range atomic ...

We are looking for a Doctoral Researcher for Quantum-inspired tensor network machine learning solvers for super-moiré van der Waals materials.

Jason Rivas is researching materials at the atomic level to improve reliability and resistance of electronics to space radiation. A PhD student in materials science and engineering at the University ...

Following award-winning performances at their regional science fair, three students from InTech Collegiate Academy — Hydyr ...