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  • 1 Saman Energy Giti Co., 3331619636, Tehran, Iran
  • | 2 Department of Chemical Engineering, Sharif University of Technology, 16558–65871, Tehran, Iran
  • | 3 Process Department, Sazeh Consultants Engineers, Tehran, Iran
  • | 4 Department of Chemistry, Islamic Azad University, North Tehran Branch, Tehran, Iran
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Abstract

In this study, the quantitative structure–property relationship method is applied to predict the enthalpy of fusion of pure chemical compounds at their normal melting point. A genetic algorithm-based multivariate linear regression is used to select the most statistically effective molecular descriptors for evaluating this property. To propose a comprehensive and predictive model, 3,846 pure chemical compounds are investigated. The root mean square of error and the average absolute deviation of the model are equal to 2.57 kJ/mol and 9.7%.

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  • Impact Factor (2019): 2.731
  • Scimago Journal Rank (2019): 0.415
  • SJR Hirsch-Index (2019): 87
  • SJR Quartile Score (2019): Q3 Condensed Matter Physics
  • SJR Quartile Score (2019): Q3 Physical and Theoretical Chemistry
  • Impact Factor (2018): 2.471
  • Scimago Journal Rank (2018): 0.634
  • SJR Hirsch-Index (2018): 78
  • SJR Quartile Score (2018): Q2 Condensed Matter Physics
  • SJR Quartile Score (2018): Q2 Physical and Theoretical Chemistry

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Journal of Thermal Analysis and Calorimetry
Language English
Size A4
Year of
Foundation
1969
Volumes
per Year
4
Issues
per Year
24
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 1388-6150 (Print)
ISSN 1588-2926 (Online)

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