Experimental investigation of synthesized Al2O3 Ionanofluid's energy storage properties: Model-prediction using gene expression programming

Praveen Kumar Kanti, K. V. Sharma, Anil Rao H N, Masoud Karbasi, Zafar Said

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

In this work, 3-hydroxy-1-(4-(1-methyl piperidine-1-ium-1-yl) butyl) quinuclidine-1-ium bromide ionic liquid (IL) is synthesized. Al2O3 (~50 nm) nanoparticles (NPs) were dispersed in the IL as base fluid to prepare Ionanofluids (INF). The experiments were undertaken to determine the stability, viscosity (VST), and thermal conductivity (TC) of IL and INF in the temperature and concentration range of 30 to 60 °C and 0 to 10 wt%, respectively. The IL is characterized by nuclear magnetic resonance (NMR) spectroscopy. The pH and zeta potential values of INF are determined. The experimental outcomes show the maximum TC and VST enhancement of 32.9 and 76.3 % at 60 and 30 °C compared to IL. Additionally, the experimental data of TC and VST is compared with the theoretical models presented in the literature. The correlations are presented for the evaluation of the TC and VST of the studied INF based on experimental data. Furthermore, the gene expression programming (GEP) model is adopted. The predicted values of TC and VST of INF are attained with R2 = 0.9978 and 0.9972, respectively. The performance enhancement ratio (PER) indicates that studied INFs are beneficial for energy storage applications.

Original languageEnglish
Article number105718
JournalJournal of Energy Storage
Volume55
DOIs
Publication statusPublished - Nov 25 2022
Externally publishedYes

Keywords

  • AlO
  • Heat transfer
  • Ionanofluid
  • Machine learning techniques
  • Stability
  • Thermal conductivity
  • Viscosity

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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