Free Energy, Entropy and Heat Capacity of the Hydrophobic Interaction as a Function of Pressure

2000 ◽  
Vol 104 (29) ◽  
pp. 6884-6888 ◽  
Author(s):  
Steven W. Rick
Keyword(s):  
Heat Capacity ◽  
Free Energy ◽  
Hydrophobic Interaction ◽  
Energy Entropy

scholarly journals HIGH-TEMPERATURE FREE ENERGY, ENTROPY, ENTHALPY AND HEAT CAPACITY OF THORIUM SULFATE1

1960 ◽  
Vol 64 (7) ◽  
pp. 911-914 ◽  
Author(s):  
S. W. Mayer ◽  
B. B. Owens ◽  
T. H. Rutherford ◽  
R. B. Serrins
Keyword(s):  
Heat Capacity ◽  
Free Energy ◽  
High Temperature ◽  
Energy Entropy

Enthalpy, free energy, entropy and heat capacity of cyclohexane and acetaldehyde

2010 ◽  
Vol 75 (9-10) ◽  
pp. 655-667 ◽  
Author(s):  
E. R. Lippincott ◽  
G. Nagarajan ◽  
J. E. Katon
Keyword(s):  
Heat Capacity ◽  
Free Energy ◽  
Energy Entropy

Statistical Thermodynamics Enthalpy, Free Energy, Entropy, and Heat Capacity of Some Hexafluorides of Octahedral Symmetry

1971 ◽  
Vol 26 (10) ◽  
pp. 1658-1666 ◽  
Author(s):  
G. Nagarajan ◽  
Donald C. Brinkley
Keyword(s):  
Heat Capacity ◽  
Free Energy ◽  
Infrared Absorption ◽  
Infrared Absorption Spectrum ◽  
Point Group ◽  
Structural Data ◽  
Octahedral Symmetry ◽  
Symmetry Point Group ◽  
Rigid Rotator ◽  
Energy Entropy

Abstract A detailed analysis of the molecular structural data and infrared absorption and Raman spectra of the hexafluoride of sulfur, selenium, tellurium, molybdenum, technetium, ruthium, rhodium, tungsten, thenium, osmium, iridium, platinum, uranium, neptunium, and plutonium has been made. These molecules, having the greatest number of symmetry elements of all existing molecules, possess an octahedral symmetry with the symmetry point group Oh. They give rise to six fundamental frequencies of which three are allowed in the Raman spectrum, two are allowed in the infrared absorption spectrum, and one is inactive. The inactive mode in normally determined from the overtones and combinations. On the basis of a rigid rotator and harmonic oscillator model, enthalpy, free energy, entropy, and heat capacity for temperatures from 200 °K to 2000 °K have been computed for these molecules. The results are briefly discussed and compared with available experimental data.

scholarly journals Estimating a Stoichiometric Solid’s Gibbs Free Energy Model by Means of a Constrained Evolutionary Strategy

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 471
Author(s):  
Constantino Grau Turuelo ◽  
Sebastian Pinnau ◽  
Cornelia Breitkopf
Keyword(s):  
Heat Capacity ◽  
Free Energy ◽  
Evolutionary Strategy ◽  
Data Sets ◽  
Automatic Data ◽  
Physical Constraints ◽  
Stoichiometric Model ◽  
Covariance Matrix Adaptation ◽  
Dsc Measurements ◽  
Capacity Data

Modeling of thermodynamic properties, like heat capacities for stoichiometric solids, includes the treatment of different sources of data which may be inconsistent and diverse. In this work, an approach based on the covariance matrix adaptation evolution strategy (CMA-ES) is proposed and described as an alternative method for data treatment and fitting with the support of data source dependent weight factors and physical constraints. This is applied to a Gibb’s Free Energy stoichiometric model for different magnesium sulfate hydrates by means of the NASA9 polynomial. Its behavior is proved by: (i) The comparison of the model to other standard methods for different heat capacity data, yielding a more plausible curve at high temperature ranges; (ii) the comparison of the fitted heat capacity values of MgSO4·7H2O against DSC measurements, resulting in a mean relative error of a 0.7% and a normalized root mean square deviation of 1.1%; and (iii) comparing the Van’t Hoff and proposed Stoichiometric model vapor-solid equilibrium curves to different literature data for MgSO4·7H2O, MgSO4·6H2O, and MgSO4·1H2O, resulting in similar equilibrium values, especially for MgSO4·7H2O and MgSO4·6H2O. The results show good agreement with the employed data and confirm this method as a viable alternative for fitting complex physically constrained data sets, while being a potential approach for automatic data fitting of substance data.

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