How the 鈥淟iquid Drop鈥?Approach Could Be Efficiently Applied for Quantitative Structure鈥揚roperty Relationship Modeling of Nanofluids

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• 作者：Natalia Sizochenko ; Karolina Jagiello ; Jerzy Leszczynski ; Tomasz Puzyn
• 刊名：Journal of Physical Chemistry C
• 出版年：2015
• 出版时间：November 12, 2015
• 年：2015
• 卷：119
• 期：45
• 页码：25542-25547
• 全文大小：301K
• ISSN：1932-7455

文摘

The main goal of this paper is the evaluation of the applicability of the geometrical 鈥渓iquid drop鈥?model (LDM) to describe physicochemical properties of nanofluids in quantitative structure鈥損roperty relationship (QSPR) modeling. LDM-based descriptors are size-dependent, which allows them to be applied for a series of nanoparticles with the same chemical composition but different sizes. Thermal conductivity of nanofluids as the target property was investigated. Random forest regression as a nonparametric approach was utilized to determine important structural features of nanofluids responsible for enhancing their thermal conductivity.