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For decades, it’s been known that subtle chemical patterns exist in metal alloys, but researchers thought they were too minor to matter — or that they got erased during manufacturing. However, recent studies have shown that in laboratory settings, these patterns can change a metal’s properties, including its mechanical strength, durability, heat capacity, radiation tolerance, and more.
Now, researchers at MIT have found that these chemical patterns also exist in conventionally manufactured metals. The surprising finding revealed a new physical phenomenon that explains the persistent patterns.
In a paper published in Nature Communications today, the researchers describe how they tracked the patterns and discovered the physics that explains them. The authors also developed a simple model to predict chemical patterns in metals, and they show how engineers could use the model to tune the effect of such patterns on metallic properties, for use in aerospace, semiconductors, nuclear reactors, and more.
“The conclusion is: You can never completely randomize the atoms in a metal. It doesn’t matter how you process it,” Freitas says. “This is the first paper showing these non-equilibrium states that are retained in the metal. Right now, this chemical order is not something we’re controlling for or paying attention to when we manufacture metals.”
For Freitas, an early-career researcher, the findings offer vindication for exploring a crowded field that he says few believed would lead to unique or broadly impactful results. He credits the U.S. Air Force Office of Scientific Research, which supported the work through their Young Investigator Program. He also credits the collaborative effort that enabled the paper, which features three MIT PhD students as co-first authors: Mahmudul Islam, Yifan Cao, and Killian Sheriff.
“There was the question of whether I should even be tackling this specific problem because people have been working on it for a long time,” Freitas says. “But the more I learned about it, the more I saw researchers were thinking about this in idealized laboratory scenarios. We wanted to perform simulations that were as realistic as possible to reproduce these manufacturing processes with high fidelity. My favorite part of this project is how non-intuitive the findings are. The fact that you cannot completely mix something together, people didn’t see that coming.”
From surprises to theories
Freitas’ research team began with a practical question: How fast do chemical elements mix during metal processing? Conventional wisdom held that there’s a point where the chemical composition of metals becomes completely uniform from mixing during manufacturing. By finding that point, the researchers thought they could develop a simple way to design alloys with different levels of atomic order, also known as short-range order.
The researchers used machine-learning techniques to track millions of atoms as they moved and rearranged themselves under conditions that mimicked metal processing.
“The first thing we did was to deform a piece of metal,” Freitas explains. “That’s a common step during manufacturing: You roll the metal and deform it and heat it up again and deform it a little more, so it develops the structure you want. We did that and we tracked chemical order. The thought was as you deform the material, its chemical bonds are broken and that randomizes the system. These violent manufacturing processes essentially shuffle the atoms.”
The researchers hit a snag during the mixing process: The alloys never reached a fully random state. That was a surprise, because no known physical mechanism could explain the result.
“It pointed to a new piece of physics in metals,” the researchers write in the paper. “It was one of those cases where applied research led to a fundamental discovery.”
To uncover the new physics, the researchers developed computational tools, including high-fidelity machine-learning models, to capture atomic interactions, along with new statistical methods that quantify how chemical order changes over time. They then applied these tools in large-scale molecular dynamics simulations to track how atoms rearrange during processing.
The researchers found some standard chemical arrangements in their processed metals, but at higher temperatures than would normally be expected. Even more surprisingly, they found completely new chemical patterns never seen outside of manufacturing processes. This was the first time such patterns were observed. The researchers referred to the patterns as “far-from-equilibrium states.”
The researchers also built a simple model that reproduced key features of the simulations. The model explains how the chemical patterns arise from defects known as dislocations, which are like three-dimensional scribbles within a metal. As the metal is deformed, those scribbles warp, shuffling nearby atoms along the way. Previously, researchers believed that shuffling completely erased order in the metals, but they found that dislocations favor some atomic swaps over others, resulting not in randomness but in subtle patterns that explain their findings.
“These defects have chemical preferences that guide how they move,” Freitas says. “They look for low energy pathways, so given a choice between breaking chemical bonds, they tend to break the weakest bonds, and it’s not completely random. This is very exciting because it’s a non-equilibrium state: It’s not something you’d see naturally occurring in materials. It’s the same way our bodies live in non-equilibrium. The temperature outside is always hotter or colder than our bodies, and we’re maintaining that steady state equilibrium to stay alive. That’s why these states exist in metal: the balance between an internal push toward disorder plus this ordering tendency of breaking certain bonds that are always weaker than others.”
Applying a new theory
The researchers are now exploring how these chemical patterns develop across a wide range of manufacturing conditions. The result is a map that links various metal processing steps to different chemical patterns in metal.
To date, this chemical order and the properties they tune have been largely considered an academic subject. With this map, the researchers hope engineers can begin thinking of these patterns as levers in design that can be pulled during production to get new properties.
“Researchers have been looking at the ways these atomic arrangements change metallic properties — a big one is catalysis,” Freitas says of the process that drives chemical reactions. “Electrochemistry happens at the surface of the metal, and it’s very sensitive to local atomic arrangements. And there have been other properties that you wouldn't think would be influenced by these factors. Radiation damage is another big one. That affects these materials’ performance in nuclear reactors.”
Researchers have already told Freitas the paper could help explain other surprise findings about metallic properties, and he’s excited for the field to move from fundamental research into chemical order to more applied work.
“You can think of areas where you need very optimized alloys like aerospace,” Freitas says. “They care about very specific compositions. Advanced manufacturing now makes it possible to combine metals that normally wouldn’t mix through deformation. Understanding how atoms actually shuffle and mix in those processes is crucial, because it’s the key to gaining strength while still keeping the low density. So, this could be a huge deal for them.”
This work was supported, in part, by the U.S. Air Force Office of Scientific Research, MathWorks, and the MIT-Portugal Program.
