Quantifying chemical short-range order in metallic alloys

What is it about?

In this work, we have introduced a method to decipher the atomic-scale arrangement of atoms in metallic alloys containing a large number of chemical elements. Think of the chemical layout in these alloys like a complex "connect the dots" puzzle in a child's coloring book. At first, the dots seem randomly scattered, but as you start connecting them, a hidden picture emerges. Similarly, by defining the dots (the minimal building block of chemical arrangements) and the rules for connecting them (using machine learning and information theory), our research quantified that despite the seemingly chaotic arrangement of atoms in these alloys, subtle patterns lie beneath the randomness (known as short-range order - SRO). Like the hidden picture in a dot puzzle, these patterns—though challenging to measure experimentally—are crucial to various material properties.

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Photo by Annebell Dogger on Unsplash

Photo by Annebell Dogger on Unsplash

Why is it important?

Our work enables the realization of simulations with much higher physical fidelity than it was possible before. Additionally, it serves as a valuable resource for experimental groups aiming to characterize these patterns, providing guidance on key aspects such as pattern size and temperature-dependent changes. This not only helps us understand how the arrangement of these patterns can change the behavior of the alloys, but also paves the way for the rigorous incorporation of these patterns into predictive models. The advancements detailed in the PNAS paper equip us with enhanced capabilities to understand and control the formation of SRO within metals, thus facilitating more accurate engineering of materials to meet specific requirements. These breakthroughs in metallurgy theory are crucial to the systematic design of chemically complex materials, with potential applications in structural, manufacturing, and energy-related fields.