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

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 appr...

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Bibliographic Details
Published in:International journal of thermophysics 2022-06, Vol.43 (6), Article 81
Main Authors: Azadfar, Roohollah, Shaabanzadeh, Masoud, Hashemi-Moghaddam, Hamid, Nafchi, Abdorreza Mohammadi
Format: Article
Language:English
Subjects:
Artificial neural networks
Classical Mechanics
Condensed Matter Physics
Data points
Geophysics
Industrial Chemistry/Chemical Engineering
Ionic liquids
Ions
Neural networks
Physical Chemistry
Physics
Physics and Astronomy
Specific heat
Thermodynamics
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Summary: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%.
ISSN:0195-928X
1572-9567
DOI:10.1007/s10765-022-03003-2