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High-Level Ab Initio Predictions of Thermochemical Properties of Organosilicon Species: Critical Evaluation of Experimental Data and a Reliable Benchmark Database for Extending Group Additivity Approaches.
Vuori, Hannu T; Rautiainen, J Mikko; Kolehmainen, Erkki T; Tuononen, Heikki M.
Afiliação
  • Vuori HT; Department of Chemistry, Nanoscience Centre, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014, Finland.
  • Rautiainen JM; Department of Chemistry, Nanoscience Centre, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014, Finland.
  • Kolehmainen ET; Department of Chemistry, Nanoscience Centre, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014, Finland.
  • Tuononen HM; Department of Chemistry, Nanoscience Centre, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014, Finland.
J Phys Chem A ; 126(10): 1729-1742, 2022 Mar 17.
Article em En | MEDLINE | ID: mdl-35254831
A high-level composite quantum chemical method, W1X-1, is used herein to calculate the gas-phase standard enthalpy of formation, entropy, and heat capacity of 159 organosilicon compounds. The results set a new benchmark in the field that allows, for the first time, an in-depth assessment of existing experimental data on standard enthalpies of formation, enabling the identification of important trends and possible outliers. The calculated thermochemical data are used to determine Benson group additivity contributions for 60 Benson groups and group pairs involving silicon. These values allow fast and accurate estimation of thermochemical parameters of organosilicon compounds of varying complexity, and the data acquired are used to assess the reliability of experimental work of Voronkov et al. that has been repeatedly criticized by Becerra and Walsh. Recent results from other computational investigations in the field are also carefully discussed through the prism of reported advancements.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article