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Research

Most materials owe their properties to chemical complexity arising from multiple elements. This applies to structural materials such as steels, superalloys, lightweight alloys, and functional systems like catalysts or batteries. Yet it is often unclear how properties change when compositions are modified—whether intentionally, for replacing critical elements, or unintentionally, during recycling. Compositionally complex alloys (CCAs) and related multicomponent materials provide a strategy to exploit chemical diversity, addressing stability, safety, sustainability, and environmental impact.

The CCA group investigates mechanical, thermodynamic, and magnetic properties of such materials using first-principles and machine-learning methods in close collaboration with experimental partners. Current activities include:

• Development of thermodynamic ab initio approaches for lattice vibrations and magnetic fluctuations,
• Integration of first-principles and machine-learning interatomic potentials,
• Study of interstitial defects and their effect on stacking fault energies,
• Screening of magnetic properties of high-entropy alloys,
• Phase stability and short-range order in multicomponent alloys.

These activities extend previous methods for unaries and ordered compounds toward complex alloys, to identify compositions with targeted materials properties.