Duke Researchers Find a Shortcut to Predicting New Magnetic Materials

Using high throughput computational models that predict magnetism in new materials, the scientists have successfully developed, atom by atom, two new magnetic materials.

High-performance magnets are ubiquitous in technology today, from hard drives to hybrid and electric vehicles to medical imaging equipment. The development of these magnets is a story itself. Only about 5 percent of inorganic materials are magnetic at all, and the development of high-performance magnets has proven to be a long and unpredictable process that largely relied on trial and error.
Magnetism is a highly sensitive phenomenon. From the perspective of the atomic structure, it requires the right confluence of properties and conditions, yielding a multitude of mechanisms for achieving magnetic ordering. It’s also not a very intuitive process, which makes it hard for humans to predict. Today, there are only about two dozen magnets suitable for technological applications.

Materials scientists from Duke University have demonstrated a shortcut to the traditional trial-and-error process. Using high throughput computational models that predict magnetism in new materials, the scientists have successfully developed, atom by atom, two new magnetic materials: cobalt, magnesium and titanium (Co2MnTi); and manganese, platinum and palladium (Mn2PtPd).

Using the computer model, the researchers focused on Heusler alloys, or materials made with atoms from three different elements arranged in one of three different structures. With 55 elements to choose from (and all possible potential arrangements), the manual process would have required testing 236,115 combinations. The model permitted the team to test hundreds of thousands of possibilities rapidly, resulting in two magnets that could be fabricated at thermodynamic equilibrium.

Corey Oses, a doctoral student in the Center for Materials Genomics at Duke and one of the co-authors of the research paper, told Design News that the goal was to speed up the process of developing new magnets.
“Not much progress had been made since about the 1980s, considering the current market for permanent magnets is still dominated by neodymium/samarium-based materials,” he said. “Unfortunately, the trial-and-error approach is not systematic: there is no known or direct path to the discovery of a new magnets. This research represents such a path, and has been validated by the discovery of two new magnets.”


Duke magnets

1Unit cells and phase stability of HAs. Possible HAs: (A) regular Heusler, (B) inverse Heusler, and (C) half Heusler. In (D), we show the unit cell used to construct the electronic structure database. (E) Ternary convex hull diagram for Al-Mn-Ni (note the presence of the stable HA, Ni2MnAl). (Image Source: Duke)


The team used the High-Throughput Framework AFLOW (Automatic FLOW for Materials Discovery), which leverages VASP (the Vienna Ab-Initio Simulation Package) for calculating the electronic structure and optimized atomic geometries. The AFLOW package populates the AFLOW.org repositories consisting of nearly 1.7 million compounds and their properties. One of these repositories is the Heusler database used by the team in their research. From the 236,115 possible combinations, the computational model identified 35,602 potentially stable compounds. Further testing for stability narrowed the list to 248, but only 22 materials showed a calculated magnetic moment. From here, the team narrowed the list to 14 by eliminating any materials with competing alternative structures “too close for comfort.”

“A thermodynamic analysis indicates the stability of candidate

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