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Alireza Fazlali

Alireza Fazlali

Academic rank: Professor
ORCID: https://orcid.org/0000-0001-8970-2479
Education: PhD.
ScopusId: 15723406500
HIndex:
Faculty: Engineering
Address: Arak University
Phone:

Research

Title
Prediction of Solubility of Sodium Valproate in Supercritical Carbon 2 Dioxide: Experimental Study and Thermodynamic Modeling
Type
JournalPaper
Keywords
Sodium Valproate
Year
2020
Journal J CHEM ENG DATA
DOI
Researchers gholamhossein Sodeifian ، Neda Sadati Ardestani ، Seyed ali Sajadian ، Mohamma reza Golmohammadi ، Alireza Fazlali

Abstract

The key factor for designing of micro- and nanosized particles 6 production processes is determination of a solid solute solubility. In the current 7 investigation, for the first time, the solubility of sodium valproate in supercritical 8 CO2 was investigated. Solubility investigations were conducted at different 9 temperatures (308.15−338.15 K) and pressure values (12−27 MPa). Sodium 10 valproate provided mole fraction solubility values of 0.05 × 10−5 to 3.71 × 10−5 11 within the experimental range studied. For the studied system, data correlation has 12 been examined by equations of state (EoSs) including Soave−Redlich−Kwong 13 (SRK), Peng−Robinson (PR), and Estevez models as well as SAFT-VR and four 14 semi-empirical models (Kumar and Johnston, Mendez-Santiago and Teja, Jouyban ́ et al., Sodeifian et al., Bartle et al., Chrastil’s 15 models and Reddy and Garlapati models). Statistical criteria (AARD, Radj, and F-value) were used to appraise their precision. The 16 analysis of variance (ANOVA) also indicated the superior performance of the PR, SRK, Estevez, and SAFT-VR EoSs. Furthermore, 17 density-based models generally exhibited excellent agreement with the experimental data.