Thiacyclopentane: Heat Capacity, Heats of Fusion and Vaporization, Vapor Pressure, Entropy, Heat of Formation and Thermodynamic Functions1

Low-temperature heat capacity and pseudorotation in 2 methyltetrahydrofuran

The heat capacity and phase transitions of 2-methyltetrahydrofuran in the temperature range from 7 to 350 K were measured by adiabatic calorimetry. The smoothed molar thermodynamic functions in the condensed...

Efficient Ab Initio Estimation of Formation Enthalpies for Organic Compounds: Extension to Sulfur and Critical Evaluation of Experimental Data

The efficient protocol for the estimation of gas-phase enthalpies of formation developed previously for C, H, O, N, and F elements was extended to sulfur. The protocol is based on a local coupled cluster with single, double, and perturbative triple excitation [CCSD(T)] approximation and allows rapid evaluation of compounds with sizes computationally prohibitive to canonical CCSD(T) using quadruple zeta basis sets. As a part of model development, a comprehensive review and critical evaluation of experimental data were performed for 87 sulfur-containing organic and inorganic compounds. A compact model with only three empirical parameters for sulfur introduced to address the effects beyond frozen core CCSD(T) was developed. The model exhibits approximately 2 kJ·mol^-1 standard deviation over a set of experimental values for a diverse collection of sulfur-containing compounds. The complete basis set version of the model demonstrates a similar performance and requires only one empirical parameter. Multiple problems with the existing experimental data were identified and discussed. In addition, a lack of reliable data for certain important classes of sulfur compounds was found to impede the model generalization and confident performance assessment.

Saturated-liquid heat capacity: New polynomial models and review of the literature experimental data

In this paper a review of selected literature experimental data for saturated-liquid heat capacities was presented. Two-, three- and four-parameter polynomial correlation models are tested on those data. Obtained results lead to the conclusion that correlation quality depends on the number of parameters, and slightly on the type of models. The best two three- and four-parameter models were proposed.