Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric Materials
First Order Reversal Curve (FORC) distributions of magnetic materials are a well-known tool to extract information about hysteresis sources and magnetic interactions, or to fingerprint them. Recently, a temperature variant of this analysis technique (Temperature-FORC, TFORC) has been used for the an...
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doaj-0cef559fe78544f5bd1dd576458ea3ae2020-11-25T03:21:33ZengMDPI AGMetals2075-47012020-08-01101039103910.3390/met10081039Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric MaterialsLuis M. Moreno-Ramírez0Victorino Franco1Dpto. Física de la Materia Condensada, ICMSE-CSIC, Universidad de Sevilla, P.O. Box 1065, 41080 Sevilla, SpainDpto. Física de la Materia Condensada, ICMSE-CSIC, Universidad de Sevilla, P.O. Box 1065, 41080 Sevilla, SpainFirst Order Reversal Curve (FORC) distributions of magnetic materials are a well-known tool to extract information about hysteresis sources and magnetic interactions, or to fingerprint them. Recently, a temperature variant of this analysis technique (Temperature-FORC, TFORC) has been used for the analysis of the thermal hysteresis associated with first-order magnetocaloric materials. However, the theory supporting the interpretation of the diagrams is still lacking, limiting TFORC to a fingerprinting technique so far. This work is a first approach to correlate the modeling of first-order phase transitions, using the Bean–Rodbell model combined with a phenomenological transformation mechanism, with the features observed in experimental TFORC distributions of magnetocaloric materials. The different characteristics of the transformations, e.g., transition temperatures, symmetry, temperature range, etc., are correlated to distinct features of the distributions. We show a catalogue of characteristic TFORC distributions for magnetocaloric materials that exhibit some of the features observed experimentally.https://www.mdpi.com/2075-4701/10/8/1039TFORCthermal hysteresismagnetocaloric materials |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Luis M. Moreno-Ramírez Victorino Franco |
spellingShingle |
Luis M. Moreno-Ramírez Victorino Franco Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric Materials Metals TFORC thermal hysteresis magnetocaloric materials |
author_facet |
Luis M. Moreno-Ramírez Victorino Franco |
author_sort |
Luis M. Moreno-Ramírez |
title |
Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric Materials |
title_short |
Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric Materials |
title_full |
Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric Materials |
title_fullStr |
Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric Materials |
title_full_unstemmed |
Setting the Basis for the Interpretation of Temperature First Order Reversal Curve (TFORC) Distributions of Magnetocaloric Materials |
title_sort |
setting the basis for the interpretation of temperature first order reversal curve (tforc) distributions of magnetocaloric materials |
publisher |
MDPI AG |
series |
Metals |
issn |
2075-4701 |
publishDate |
2020-08-01 |
description |
First Order Reversal Curve (FORC) distributions of magnetic materials are a well-known tool to extract information about hysteresis sources and magnetic interactions, or to fingerprint them. Recently, a temperature variant of this analysis technique (Temperature-FORC, TFORC) has been used for the analysis of the thermal hysteresis associated with first-order magnetocaloric materials. However, the theory supporting the interpretation of the diagrams is still lacking, limiting TFORC to a fingerprinting technique so far. This work is a first approach to correlate the modeling of first-order phase transitions, using the Bean–Rodbell model combined with a phenomenological transformation mechanism, with the features observed in experimental TFORC distributions of magnetocaloric materials. The different characteristics of the transformations, e.g., transition temperatures, symmetry, temperature range, etc., are correlated to distinct features of the distributions. We show a catalogue of characteristic TFORC distributions for magnetocaloric materials that exhibit some of the features observed experimentally. |
topic |
TFORC thermal hysteresis magnetocaloric materials |
url |
https://www.mdpi.com/2075-4701/10/8/1039 |
work_keys_str_mv |
AT luismmorenoramirez settingthebasisfortheinterpretationoftemperaturefirstorderreversalcurvetforcdistributionsofmagnetocaloricmaterials AT victorinofranco settingthebasisfortheinterpretationoftemperaturefirstorderreversalcurvetforcdistributionsofmagnetocaloricmaterials |
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