Estimation of Heat Capacity of 143 Pure Ionic Liquids Using Artificial Neural Network

被引：11

作者：

Azadfar, Roohollah ^{[1
]}

Shaabanzadeh, Masoud ^{[1
]}

Hashemi-Moghaddam, Hamid ^{[1
]}

Nafchi, Abdorreza Mohammadi ^{[2
]}

机构：

[1] Islamic Azad Univ, Dept Chem & Chem Engn, Damghan Branch, Damghan, Iran

[2] Univ Sains Malaysia, Sch Ind Technol, USM, George Town 11800, Malaysia

来源：

INTERNATIONAL JOURNAL OF THERMOPHYSICS | 2022年 / 43卷 / 06期

关键词：

Heat capacity; Ionic liquid; Correlation; NIST; Artificial neural network; ANN; SOLUBILITY; H2S; PREDICTION; CO2;

D O I：

10.1007/s10765-022-03003-2

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Based on artificial neural network (ANN), a new model is presented to estimate the heat capacity of pure ionic liquids. A database for the heat capacity of ionic liquids created by extracting experimental data from literature covering the period from 1971 to 2021 is reported. With the presented approach, heat capacity is calculated and evaluated by source data bank for 7059 data points of 143 ionic liquids. The accuracies of new ANN model are evaluated by comparing with the most commonly used correlations in the literatures, and the results reveal that the proposed network provides more accurate results than other literature correlations considered in this work. The average absolute percentage deviation from the new model is only 1.14%.

引用

页数：21