Magnetism in Metastable and Annealed Compositionally Complex Alloys

TL;DR

This study explores the magnetic properties of metastable and annealed CCMs, revealing low coercivity at room temperature, high coercivity at low temperatures, and significant changes upon annealing, with implications for designing advanced magnetic materials.

Contribution

It introduces a combinatorial sputtering method to access and study metastable CCMs outside their stable phases, revealing unique magnetic behaviors and the effects of annealing.

Findings

Low coercivity (<1 mT) at room temperature

High coercivity (~500 mT) at 50 K

Annealing increases Curie temperature and saturation magnetization, reduces coercivity

Abstract

Compositionally complex materials (CCMs) present a potential paradigm shift in the design of magnetic materials. These alloys exhibit long-range structural order coupled with limited or no chemical order. As a result, extreme local environments exist with a large opposing magnetic energy term, which can manifest large changes in the magnetic behavior. In the current work, the magnetic properties of (Cr, Mn, Fe, Ni) alloys are presented. These materials were prepared by room-temperature combinatorial sputtering, resulting in a range of compositions with a single BCC structural phase and no chemical ordering. The combinatorial growth technique allows CCMs to be prepared outside of their thermodynamically stable phase, enabling the exploration of otherwise inaccessible order. The mixed ferromagnetic and antiferromagnetic interactions in these alloys causes frustrated magnetic behavior, which results in an extremely low coercivity (<1 mT), which increases rapidly at 50 K. At low temperatures, the coercivity achieves values of nearly 500 mT, which is comparable to some high-anisotropy magnetic materials. Commensurate with the divergent coercivity is an atypical drop in the temperature dependent magnetization. These effects are explained by a mixed magnetic phase model, consisting of ferro-, antiferro , and frustrated magnetic regions, and are rationalized by simulations. A machine-learning algorithm is employed to visualize the parameter space and inform the development of subsequent compositions. Annealing the samples at 600 {\deg}C orders the sample, more-than doubling the Curie temperature and increasing the saturation magnetization by as much as 5x. Simultaneously, the large coercivities are suppressed, resulting in magnetic behavior that is largely temperature independent over a range of 350 K.