Abstract
The ideal magnetocaloric material would lay at the borderline of a first-order and a second-order phase transition. Hence, it is crucial to unambiguously determine the order of phase transitions for both applied magnetocaloric research as well as the characterization of other phase change materials. Although Ehrenfest provided a conceptually simple definition of the order of a phase transition, the known techniques for its determination based on magnetic measurements either provide erroneous results for specific cases or require extensive data analysis that depends on subjective appreciations of qualitative features of the data. Here we report a quantitative fingerprint of first-order thermomagnetic phase transitions: the exponent n from field dependence of magnetic entropy change presents a maximum of n > 2 only for first-order thermomagnetic phase transitions. This model-independent parameter allows evaluating the order of phase transition without any subjective interpretations, as we show for different types of materials and for the Bean–Rodbell model.
Highlights
The ideal magnetocaloric material would lay at the borderline of a first-order and a secondorder phase transition
La1Fe13−xSix-type alloys are selected in this work (x = 1.2, 1.4, 1.6, 1.8) to represent alloy series experiencing a change from FOPT to SOPT, which in this case is attained by increasing Si content[4]
In the case of FOPT, the curves should show a sharp peak associated to the latent heat, which is observed for Si 1.4 and Si 1.6 samples
Summary
The ideal magnetocaloric material would lay at the borderline of a first-order and a secondorder phase transition. We report a quantitative fingerprint of first-order thermomagnetic phase transitions: the exponent n from field dependence of magnetic entropy change presents a maximum of n > 2 only for first-order thermomagnetic phase transitions This model-independent parameter allows evaluating the order of phase transition without any subjective interpretations, as we show for different types of materials and for the Bean–Rodbell model. For cases close to the change of the order of phase transition[4], the complexity to evaluate the quality of the collapse of the data is highly dependent on subjective interpretations Just recently, another method based on the Bean and Rodbell model has been reported[30], but is still based on a particular equation of state that fulfill the mean field approach and, might not be generally applicable
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