Reliable thermodynamic estimators for screening caloric materials

Abstract

Reversible, diffusionless, first-order solid-solid phase transitions accompanied by caloric effects are critical for applications in the solid-state cooling and heat-pumping devices. Accelerated discovery of caloric materials requires reliable but faster estimators for predictions and high-throughput screening of system-specific dominant caloric contributions. We assess reliability of the computational methods that provide thermodynamic properties in relevant solid phases at or near a phase transition. We test the methods using the well-studied B2 FeRh alloy as a "fruit fly" in such a materials genome discovery, as it exhibits a metamagnetic transition which generates multicaloric (magneto-, elasto-, and baro-caloric) responses. For lattice entropy contributions, we find that the commonly-used linear-response and smalldisplacement phonon methods are invalid near instabilities that arise from the anharmonicity of atomic potentials, and we offer a more reliable and precise method for calculating lattice entropy at a fixed temperature. Then, we apply a set of reliable methods and estimators to the metamagnetic transition in FeRh (predicted 346 ± 12 K, observed 353 ± 1 K) and calculate the associated caloric properties, such as isothermal entropy and isentropic temperature changes.

Temperature-dependent lattice dynamics of antiferromagnetic and ferromagnetic phases of FeRh

“…The red curve is obtained with the force constants calculated in the low-temperature limit, and the blue curve corresponds to the high-temperature force constants. At low temperatures (red curve) we obtained a negative entropy difference, which agrees with the experimental [23] and earlier theoretical data [53]. On the contrary, at temperatures close to the phase transition temperature (blue curve) the calculated difference of the vibrational entropies is positive and is about 16 J/kg/K.…”

“…On the contrary, at temperatures close to the phase transition temperature (blue curve) the calculated difference of the vibrational entropies is positive and is about 16 J/kg/K. This value is much larger than the values predicted in other theoretical works: ∼3.66 J/kg/K [53] and ∼5.85 J/kg/K [24]. This emphasizes the importance of taking into account the temperature dependence of atomic motions consistently.…”

“…A linear interpolation of the calculated frequencies at the X point between T = 0 K and 100 K gives the estimation of the dynamical stabilization temperature of the cubic AFM phase at about 50 K. In Ref. [53] the dynamical stabilization of the cubic structure was observed by means of the so-called large displacement method even at T = 0 K. Here we provide a much more physical picture of the dynamical stabilization of the AFM phase of FeRh by anharmonic effects of the lattice…”

First-Principles Prediction of Incipient Order in Arbitrary High-Entropy Alloys: Exemplified in Ti _0.25CrFeNiAl _x

“…Importantly, SRO estimate gives robust trends without additional calculations. The direct evaluation of the formation energies, E f orm , of the partially LRO state relative to the disordered state establish order-disorder transition temperatures, for example, k B T od = E LRO f orm − E dis f orm in ordering systems [60,61] and slightly more complicated in segregating systems [62].…”

Modeling the Maximum Magnetic Entropy Change of Doped Manganite Using a Grid Search-Based Extreme Learning Machine and Hybrid Gravitational Search-Based Support Vector Regression

“…Identifying the relationship between the nature as well as the concentration of the dopants supports the understanding of their physical properties, while the synthesis of new manganite-based compounds having multifunctional applications becomes possible. Some screening approaches to developing and identifying materials with a large magnetocaloric effect have been proposed in the literature [19], [20]. However, machine learning techniques have been identified as effective and efficient tools for determining the influence of dopants on the physical properties (such as magnetic ordering temperature, relative cooling power and magnetocaloric effect) of doped manganite-based compounds [6,[21][22][23][24][25].…”