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Saturated Vapor Pressure Measurements for Tetraethyl, Tetrapropyl, and Tetrabutyl Orthosilicates up to 473 K

The saturated vapor pressures of tetraethyl orthosilicate (TEOS, (CH3CH2O)4Si), tetrapropyl orthosilicate (TPOS, (CH3CH2CH2O)4Si), and tetrabutyl orthosilicate (TBOS, (CH3CH2CH2CH2O)4Si) were measured at temperatures up to 473 K using an apparatus based on the general static method. The standard unc...

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Bibliographic Details
Published in:Journal of chemical and engineering data 2024-11, Vol.69 (11), p.3783-3793
Main Authors: Matsukawa, Hiroaki, Otake, Katsuto
Format: Article
Language:English
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Summary:The saturated vapor pressures of tetraethyl orthosilicate (TEOS, (CH3CH2O)4Si), tetrapropyl orthosilicate (TPOS, (CH3CH2CH2O)4Si), and tetrabutyl orthosilicate (TBOS, (CH3CH2CH2CH2O)4Si) were measured at temperatures up to 473 K using an apparatus based on the general static method. The standard uncertainties (u s ) were u s (T) = 0.029 K and u s (p) = 0.015 kPa, and the maximum combined expanded uncertainties U (0.95 level of confidence) were U(T) = (0.52, 8.60, and 1.64 K) and U(p sat) = (2.81, 3.09, and 0.82 kPa) for TEOS, TPOS, and TBOS, respectively. Furthermore, the saturated vapor pressure was correlated using the Antoine equation to determine its parameters. The measured saturated vapor pressures were correlated with previously reported pressure–volume-temperature data using the PC-SAFT equation of state (EoS), followed by optimizing the pure component parameters of the PC-SAFT EoS. A relationship between the molecular structure and component parameters was identified, and the occupied volumes were determined according to the Sanchez–Lacombe and PC-SAFT EoS, revealing significant differences. Our findings highlight the potential of using the molecular structure to predict pure component parameters. In addition to providing accurate vapor pressure data for these orthosilicates, this study offers insights into correlation methods, emphasizing the importance of parameter determination in equation of state modeling.
ISSN:0021-9568
1520-5134
DOI:10.1021/acs.jced.4c00325