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Single Hidden Layer Intelligent Approach to Modeling Relative Cooling Power of Rare-Earth-Transition-Metal-Based Refrigerants for Sustainable Magnetic Refrigeration Application

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  • Abdullah Alqahtani

    (Computer Information System Department, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia)

Abstract

Solid-state magnetocaloric-based magnetic refrigeration offers green and sustainable refrigeration with improved efficiency, compactness and environmental friendliness compared with commercialized gas compression refrigeration systems. Relative cooling power (RCP) plays a significant role in the candidature of any magnetic material refrigerants in this application, while the tunable physical and magnetic properties of rare-earth-transition-metal-based materials strengthen the potential of these materials to be used in a cooling system. This work develops single hidden layer (SIL) extreme learning machine intelligent models for predicting the RCP of rare-earth-transition-metal-based magnetocaloric compounds using elemental constituent ionic radii (IR) and maximum magnetic entropy change (EC) descriptors. The developed model based on the sine (SN) activation function with ionic radii (IR) descriptors (SN-SIL-IR) shows superior performance over the sigmoid (SG) activation function-based model, represented as SG-SIL-IR, with performance improvements of 71.86% and 69.55% determined using the mean absolute error (MAE) and root mean square error (RMSE), respectively, upon testing rare-earth-transition-metal-based magnetocaloric compounds. The developed SN-SIL-IR further outperforms the SN-SIL-EC and SG-SIL-EC models which employed maximum magnetic entropy change (EC) descriptors with improvements of 45.74% and 24.79%, respectively, on the basis of MAE performance assessment parameters. Estimates of the developed model agree well with the measured values. The dependence of the RCP on an applied magnetic field for various classes of rare-earth-transition-metal-based magnetocaloric compounds is established using a developed SN-SIL-IR model. The improved precision of the developed SN-SIL-IR model, coupled with ease of its descriptors, will strengthen and facilitate the comprehensive exploration of rare-earth-transition-metal-based magnetocaloric compounds for their practical implementation as magnetic refrigerants for promoting a sustainable system of refrigeration that is known to be efficient and environmentally friendly.

Suggested Citation

  • Abdullah Alqahtani, 2024. "Single Hidden Layer Intelligent Approach to Modeling Relative Cooling Power of Rare-Earth-Transition-Metal-Based Refrigerants for Sustainable Magnetic Refrigeration Application," Sustainability, MDPI, vol. 16(4), pages 1-15, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1542-:d:1337631
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    References listed on IDEAS

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    1. Miloud Souiyah & Taoreed O. Owolabi & Saibu Saliu & Talal F. Qahtan & Nahier Aldhafferi & Abdullah Alqahtani & Ramin Ranjbarzadeh, 2022. "Specific Surface Area Characterization of Spinel Ferrite Nanostructure Based Compounds for Photocatalysis and Other Applications Using Extreme Learning Machine Method," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, April.
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