High-entropy alloys (HEAs) are rewriting the rules of materials science, and machine learning is accelerating their design. By predicting phase stability and performance from large datasets, ...

From atomic-scale imaging to machine learning predictions, AI is revolutionizing how scientists design and optimize high-entropy alloys. These materials, prized for their strength and resilience, are ...

Composed of five or more elements in nearly equal amounts, high-entropy alloys (HEAs) have emerged as promising catalysts due ...

The rapid increase in electric vehicle adoption in recent years has highlighted a crucial issue: the energy conversion ...

Composed of five or more elements in nearly equal amounts, high-entropy alloys (HEAs) have emerged as promising catalysts due ...

Magnetic domains can take on a wide range of structures. In certain soft magnetic materials, they form complex zig-zag ...

Maze magnetic domains in soft magnetic materials strongly influence energy loss in electric motors, particularly at high ...

Researchers develop a new computational model that helps identify origin of complex magnetization reversal in soft magnets.

The rapid increase in electric vehicle adoption in recent years has highlighted a crucial issue: the energy conversion efficiency of electric motors ...

Prompt engineering keeps adding new techniques. One is the String Seed-of-Thought (SSoT) that aids options-choosing, game ...