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<p>Nanomaterials have significant potential across various industries, including energy, medicine, and environmental science. Their diverse qualities, such as various thermal properties, complicate the selection process, particularly when balancing performance with cost. This study aims to employ a systematic approach to identify the most suitable nanomaterial for enhancing thermal heat storage in paraffin wax using Multiple Attribute Decision Making (MADM) techniques. We utilized the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank candidate materials based on their performance attributes. The entropy method was applied to assign relative weights to these attributes, facilitating a nuanced analysis. In Case 1, latent heat was identified as the most significant quality (W3 = 0.5505), while cost emerged as the dominant factor in Case 2 (W4 = 0.7067). Al₂O₃ (4%) ranked highest in Case 1 with a relative closeness value of 0.8553, whereas SiO₂ (11&#xa0;nm, 2%) excelled in Case 2 (0.9552). Sensitivity analysis revealed that metal oxides, such as Fe₂O₃, demonstrated greater percentage changes in output metrics compared to alumina and silica. The findings highlight the variability in nanomaterial effectiveness based on context-specific qualities. A comprehensive decision-making framework is essential for optimizing material selection, considering both performance attributes and cost, to enhance the efficacy of nanomaterial applications.</p>

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Analysis, evaluation and selection of nanoparticles added in paraffin using the MADM-TOPSIS approach

  • 期刊论文

  • 发表日期：

    2025年3月19日

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  • Kalpeshkumar P. Patel,
  • Tushar M. Patel

摘要

Nanomaterials have significant potential across various industries, including energy, medicine, and environmental science. Their diverse qualities, such as various thermal properties, complicate the selection process, particularly when balancing performance with cost. This study aims to employ a systematic approach to identify the most suitable nanomaterial for enhancing thermal heat storage in paraffin wax using Multiple Attribute Decision Making (MADM) techniques. We utilized the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank candidate materials based on their performance attributes. The entropy method was applied to assign relative weights to these attributes, facilitating a nuanced analysis. In Case 1, latent heat was identified as the most significant quality (W3 = 0.5505), while cost emerged as the dominant factor in Case 2 (W4 = 0.7067). Al₂O₃ (4%) ranked highest in Case 1 with a relative closeness value of 0.8553, whereas SiO₂ (11 nm, 2%) excelled in Case 2 (0.9552). Sensitivity analysis revealed that metal oxides, such as Fe₂O₃, demonstrated greater percentage changes in output metrics compared to alumina and silica. The findings highlight the variability in nanomaterial effectiveness based on context-specific qualities. A comprehensive decision-making framework is essential for optimizing material selection, considering both performance attributes and cost, to enhance the efficacy of nanomaterial applications.