ESTIMATION OF CRITICAL PARAMETERS AND STANDARD BOILING POINTS OF ALKYLAROMATIC HYDROCARBONS USING THE QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIPS PRINCIPLE

Based on the scaling approach, empirical QSRR models are proposed to predict the critical temperature, critical pressure, and critical volume of alkylaromatic hydrocarbons through the known standard boiling points. The need for the development of models is related to the optimization of technological processes for the production of alkylbenzenes. The scaling law always defines only some asymptotics, the applicability of which, taking into account the specificity of the system, should be analyzed specifically for each case. The models obtained in this work adequately describe the critical parameters of the liquid-vapor phase transition. In addition, we consider the case when the standard boiling point of a compound is unknown or cannot be determined because the substance is metastable and its degradation temperature is below the boiling point. In this case, based on the structure-property method, the standard boiling points of alkylaromatic hydrocarbons are estimated through the Cvetkovich topological index, which indirectly reflects the energy spectrum. The adequacy of the models is confirmed by statistical evaluations. It is found that the critical properties (temperature, pressure and volume) depend linearly and exponentially on the standard boiling point. The average approximation error (average relative deviation of calculated values from actual values) for all critical properties of the hydrocarbons under consideration does not exceed 2%. The results of the main indicator reflecting the measure of model quality are not lower than 97%. The Akaike information criterion was used to select the optimal model from several alternatives in terms of complexity. The proposed models can be used for prediction of properties of new compounds in organic chemistry, as well as for calculations of critical properties in chemical technology and petrochemistry. For citation: Dolomatov M.Yu., Kovaleva E.A., Garipov R.V. Estimation of critical parameters and standard boiling points of alkylaromatic hydrocarbons using the quantitative structure-property relationships principle. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2025. V. 68. N 6. P. 52-58. DOI: 10.6060/ivkkt.20256806.7175.

Authors

Publication Details

Journal
IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENIY KHIMIYA KHIMICHESKAYA TEKHNOLOGIYA
Published
2025-05-14
DOI
https://doi.org/10.6060/ivkkt.20256806.7175
Primary Topic
Chemical Thermodynamics and Molecular Structure
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ESTIMATION OF CRITICAL PARAMETERS AND STANDARD BOILING POINTS OF ALKYLAROMATIC HYDROCARBONS USING THE QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIPS PRINCIPLE

E.. Kovaleva, R. V. Garipov, Mikhail Yu. Dolomatov
IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENIY KHIMIYA KHIMICHESKAYA TEKHNOLOGIYA
Chemical Thermodynamics and Molecular Structure
article

ESTIMATION OF CRITICAL PARAMETERS AND STANDARD BOILING POINTS OF ALKYLAROMATIC HYDROCARBONS USING THE QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIPS PRINCIPLE

E.. Kovaleva, R. V. Garipov, Mikhail Yu. Dolomatov
article en

Abstract

Based on the scaling approach, empirical QSRR models are proposed to predict the critical temperature, critical pressure, and critical volume of alkylaromatic hydrocarbons through the known standard boiling points. The need for the development of models is related to the optimization of technological processes for the production of alkylbenzenes. The scaling law always defines only some asymptotics, the applicability of which, taking into account the specificity of the system, should be analyzed specifically for each case. The models obtained in this work adequately describe the critical parameters of the liquid-vapor phase transition. In addition, we consider the case when the standard boiling point of a compound is unknown or cannot be determined because the substance is metastable and its degradation temperature is below the boiling point. In this case, based on the structure-property method, the standard boiling points of alkylaromatic hydrocarbons are estimated through the Cvetkovich topological index, which indirectly reflects the energy spectrum. The adequacy of the models is confirmed by statistical evaluations. It is found that the critical properties (temperature, pressure and volume) depend linearly and exponentially on the standard boiling point. The average approximation error (average relative deviation of calculated values from actual values) for all critical properties of the hydrocarbons under consideration does not exceed 2%. The results of the main indicator reflecting the measure of model quality are not lower than 97%. The Akaike information criterion was used to select the optimal model from several alternatives in terms of complexity. The proposed models can be used for prediction of properties of new compounds in organic chemistry, as well as for calculations of critical properties in chemical technology and petrochemistry. For citation: Dolomatov M.Yu., Kovaleva E.A., Garipov R.V. Estimation of critical parameters and standard boiling points of alkylaromatic hydrocarbons using the quantitative structure-property relationships principle. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2025. V. 68. N 6. P. 52-58. DOI: 10.6060/ivkkt.20256806.7175.

IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENIY KHIMIYA KHIMICHESKAYA TEKHNOLOGIYAVol. 68(6)
Openalex Percentile: Top 91%
Chemical Thermodynamics and Molecular Structure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.