Computer simulation of metallic alloy where atoms (spheres) are arranged in subtle chemical patterns beneath a network of dislocations (green lines). Credit: Rodrigo Freitas
Researchers have discovered a new physical phenomenon that explains why the chemical patterns in metal alloys and conventionally manufactured metals can never be mixed in a random way.
While science has known that these tiny chemical patterns exist in metal alloys for decades, it was often thought that they had almost no impact on properties of the alloy.
But recent studies have shown that these patterns can change a metal’s durability, mechanical properties and radiation tolerance in a lab setting. Now a team from Massachusetts Institute of Technology in the US has demonstrated they also impact the properties of conventionally manufactured metals.
The researchers offer a simple model to predict these chemical patterns in metals, giving engineers further insight as to how metals perform in environments like aerospace, semiconductors and nuclear reactions.
“This is the first paper showing these non-equilibrium states that are retained in the metal,” says Rodrigo Freitas, assistant professor in the Department of Materials Science and Engineering at MIT.
“Right now, this chemical order is not something we’re controlling for or paying attention to when we manufacture metals.”
The research team initially set out to investigate how fast elements mix during metal processing. The team hoped that by finding the point at which the chemical composition of metals is completely uniform, they could design simple alloys with different atomic orders.
However, as Freitas and the team continued to observe the mixing process, they realised the alloys never reached a fully random state.
“You can never completely randomise the atoms in a metal. It doesn’t matter how you process it,” says Freitas.
The team set out to find an explanation by creating a model that predicts how atoms will behave under certain conditions. They used a machine-learning technique to observe how over a million atoms moved and organised themselves in the metal manufacturing process.
“The first thing we did was to deform a piece of metal,” says Freitas.
“We did that and we tracked chemical order. The thought was as you deform the material, its chemical bonds are broken and that randomises the system. These violent manufacturing processes essentially shuffle the atoms.”
However, no matter how deformed the metals were, the atoms were never truly ordered randomly.
They used statistical models to quantify how the atoms arranged themselves in the metal. Some of the chemical patterns they found had never been seen outside of manufacturing processes.
Eventually, their model revealed an explanation for 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.”
These findings have been published in Nature Communications.
“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,” says Freitas.
“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.”
Freitas is hopeful that their model could help explain other unexplained findings about metallic properties.
“You can think of areas where you need very optimised alloys, like aerospace,” Freitas says.
“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.”
The team has now set their sights on further investigating these chemical patterns across a variety of different manufacturing environments.
“My favourite part of this project is how non-intuitive the findings are,” says Freitas.
“The fact that you cannot completely mix something together, people didn’t see that coming.”