Prediction Of Heat Capacity Research Articles

A general three-dimensional simulation approach for micro-channel heat exchanger based on graph theory

For meeting the requirements of quickly designing high performance micro-channel heat exchanger, a general three-dimensional simulation approach considering the factors of heat conductions via fins, quality distribution among micro-channel tubes and flexible flow circuit arrangements is proposed in this paper. In the simulation approach, an approximate analytical solution for describing the three-dimensional heat conductions via fins is presented, having higher computation speed over the numerical method of directly calculating heat conductions; a theory-based refrigerant distribution model for predicting the quality distribution among micro-channel tubes is established instead of using homogeneous quality distribution, resulting in the improvement of evaporator model accuracy; and a graph-theory based computation algorithm is developed to calculate any possible flow circuit conveniently and quickly. The presented model is validated by experiments, and the deviations of the predicted heat capacity of micro-channel evaporator, condenser and gas cooler from the measured ones are within ±5%.

Phase transition and thermodynamic properties of ThO2 from first-principles calculations

Within the framework of the quasi-harmonic approximation, the thermodynamic properties and the phase transition of ThO2 from the cubic structure to the orthorhombic structure are studied using the first-principles projector-augmented wave method. The vibrational contribution to Helmholtz free energy is evaluated from the first-principles phonon density of states and the Debye–Grüneisen model. The calculated results reveal that at ambient temperature, the phase transition from the cubic phase to the orthorhombic phase occurs at 26.49GPa, which is in agreement with the experimental and theoretical data. With increasing temperature, the transition pressure decreases almost linearly above room temperature. The predicted heat capacity and linear thermal expansion coefficient of cubic ThO2 are in good consistence with the experimental data. By comparing the experimental results with the calculation results from the first-principles and Debye–Grüneisen model, it is found that the thermodynamic properties of ThO2 are depicted well by the first-principles phonon treatment after including the an-harmonic correction to quasi-harmonic free energy.

Prediction of Heat Capacities of Hydration of Various Organic Compounds Using Partial Least Squares and Artificial Neural Network

A quantitative structure–property relationship study based on artificial neural network (ANN) was carried out for the prediction of the heat capacities of hydration of a set of 289 organic compounds of very different chemical natures. The genetic algorithm-partial least squares (GA-PLS) method was applied as a variable selection tool. A PLS method was used to select the best descriptors, and the selected descriptors were then used as input neurons in a neural network model. These descriptors are: number of H atoms (NHA), maximum partial charge in the molecule (Q max), atomic charge weighted PPSA (PPSA3), relative positive charge (RPCG), minimum net atomic charge (Q min), fractional PPSA (FPSA3), and Randic index (order 1) (1 χ). The results obtained show the ability of the developed artificial neural network model to predict heat capacities of hydration of various organic compounds. Also, the results reveal the superiority of the ANN over the PLS model.

Heat capacity prediction of complex molecules by mass connectivity index

Heat capacity prediction and estimation methods of solid organic compounds in terms of temperature are limited, particularly concerning complex molecules with functional groups such as active principles and intermediaries used in pharmaceutical field.Recently a correlation between heat capacity at constant pressure (Cp), temperature and a new concept named mass connectivity index (MCI), for ionic liquids, was published [1-3]. In this predictive method, heat capacity can be calculated at different temperatures, if standard heat capacity at 298.15 K is known. The effect of molecular structure on heat capacity is accounted for in this model by the mass connectivity index, a molecular descriptor, which differentiates between compounds. The Valderrama generalized correlation admits, in addition, two universal coefficients, which are obtained from experimental data regression.In the present work, a similar approach is used to predict solid state heat capacity of organics and pharmaceutical products. In order to find model parameters, a database was grouped comprising (104) different compounds and a set of more than 5,791 experimental values of solid state Cps obtained from literature. These collected data were used in multiple linear regression to find model parameters. It was found that the values of predicted heat capacities of compounds non-included in the database were good; they are quite close to the ones presented in the literature. Moreover, this method is simple to use, since only molecular structure of the component and its solid state heat capacity at 298.15 K should be known.

A new fragment contribution‐corresponding states method for physicochemical properties prediction of ionic liquids

A new fragment contribution‐corresponding states (FC—CS) method based on the group contribution method and the corresponding states principle is developed to predict critical properties of ionic liquids (ILs). There are 46 fragments specially classified for ILs considering the ionic features of ILs, and the corresponding fragment increments are determined using the experimental density data. The accuracy of the developed method is verified indirectly via predicting density and surface tension of ILs. The results show that the FC—CS method is reasonable with an average absolute relative deviation less than 4%. With the calculated critical properties, corresponding states heat capacity (CSHC) and corresponding states thermal conductivity (CSTC) correlations are proposed to predict heat capacity and thermal conductivity of ILs, respectively. The predicted results agreed well with the experimental data. The proposed FC—CS method and the two corresponding states correlations are important for design, simulation, and analysis of new ionic liquid processes. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1348–1359, 2013

A simple correlation for prediction of heat capacities of ionic liquids

Ionic liquids, owing to their unique characteristics grasp many researchers’ attention in both academia and industrial fields. In this communication, the attention is focused on the heat capacity of ionic liquids, as one of the most basic and important thermophysical properties. The simple 5-term temperature dependent correlation based on basic molecular parameters is presented to predict heat capacities of ILs. A total data set of 2940 experimental data belonging to 56 ionic liquids was used to develop a general correlation. The global absolute average deviation of the model results from experimental values is 2.5%. The proposed model could be safely applied for thermodynamic and industrial applications.

Thermophysical properties needed for the development of the supercritical diesel combustion technology: Evaluation of diesel fuel surrogate models

Development of supercritical fuel combustion technology requires reliable data on fuel properties. In this paper, twenty diesel fuel surrogates (DFSs) have been evaluated for representing real diesel fuel (DF) properties including critical point, density, heat capacity, viscosity and thermal conductivity. The critical temperatures of DF were estimated to be 717–745K largely depending on DF distillation profiles, while those of DFSs varied significantly from 540 to 734K and only those of DFSs #5(n-hexadecane), #17 and #19 were within the range for DF. The best predictions of density, heat capacity, viscosity and thermal conductivity of DF were achieved by DFSs #8 (AAD=0.3%), #4 (1.5%), #20 (13%) and #14 (1.7%), respectively, and DFS #4 (n-tetradecane) had the best overall performance with an AAD of 8%. Finally, a simple methodology has been demonstrated for the evaluation of DFSs, and the current results lead to the best predictions of DF thermophysical properties.

Quantitative Structure–Property Relationship Prediction of Liquid Heat Capacity at 298.15 K for Organic Compounds

Novel QSPR models were developed and evaluated for the prediction of heat capacity of liquids at 298.15 K with only three descriptors. Two linear and nonlinear models were produced using genetic function approximation (GFA) and adaptive neurofuzzy inference system (ANFIS) methods based on a data set of 706 compounds with a wide variety of functional groups. The results showed that both GFA and ANFIS methods could model the relationship between the liquid heat capacity of organic compounds and their structures with high accuracy. The predictive quality of the QSPR models were tested for an external test set, where the squared correlation coefficients of prediction for the GFA and ANFIS methods were 0.970 and 0.973, respectively.

Thermophysical study of sandstone reservoir rocks

Thermal conductivity of both dry and fully water (brine solution, 5 g/l NaCl concentration) saturated rocks have been measured for 35 sandstone core samples obtained from both Hungary and Egypt. Measurements are executed in order to look for thermal anisotropy. The rock porosity, permeability and density were measured beside thermal conductivity, while some correlations were performed in order to differentiate among clayey laminated, flaser bedding and clean sandstone reservoirs. There is a very close correlation among thermal conductivity, rock porosity, bulk density, gas permeability and ultrasonic wave velocities for non laminated clean sandstones, while in banded sandstone reservoirs these relations show more than one trend giving a strong impression indicating the presence of more than one grain–fabric system and/or complex diagenesis. The relationship among the measured thermal conductivity for the core axis, the top and bottom are close and homogeneous for isotropic clean non laminated Szolnok sandstones, while they are vary in a wide range for banded and laminated Bahariya sandstone samples. The measured specific heat capacity indicates that some banded sandstone samples of the Bahariya Formation have bound water appears at 100 °C and giving low specific heat capacity value. This bound water can acted on all petrophysical parameters especially electrical properties. The prediction of specific heat capacity and heat flow from the reservoir temperature is possible using the calculated multi-regression and linear regression models.

Prediction of high pressure liquid heat capacities of organic compounds by a group contribution method

A new method for estimating high pressure liquid heat capacities based on molecular structure and group contribution is proposed. A common set of structural groups was employed. The method was developed using 67 sets of 43 organic compounds with 3449 experimental heat capacity data. A small number of measured compounds, data points per compound and other comparable methods were observed. This is a simple first-order approximation with acceptable accuracy of 2.548%.

A predictive model for the entropies and heat capacities of zeolites

The classical predictive models for thermodynamic entities are based on summation techniques. At the time these predictive methods were designed, no or few calorimetric data on zeolites were available. The number of calorimetric measurements (third-law entropy and heat capacities) performed since 1990 on various zeolitic minerals allows a quick verification of all algorithms. It shows that the predicted values display a discrepancy above 4 % relative to the measured values. Recent predictive methods for entropy and for heat capacity also give very high differences between predicted and experimental values. With a limited number of thermodynamic values of zeolites and their dehydrated forms, the entropy and heat capacity predictions have been improved by using the thermodynamic properties of zeolite-like silica polymorphs and of zeolitic water obtained from the difference between the thermodynamic parameters of anhydrous and hydrated zeolites. The improvements introduced in this work reduce the prediction errors to about 2.95 % for entropy and 2.86 % for heat capacities.

Prediction of heat capacities and heats of vaporization of organic liquids by group contribution methods

In the present work a group contribution method is proposed for the estimation of the heat capacity of organic liquids as a function of temperature for fatty compounds found in edible oil and biofuels industries. The data bank used for regression of the group contribution parameters (1395 values for 86 types of substances) included fatty compounds, such as fatty acids, esters, alcohols and triacylglycerols, and hydrocarbons. The performance of this method is compared with other published group contribution methods [Z. Kolská, J. Kukal, M. Zábranský, V. Růžička, Ind. Eng. Chem. Res. 47 (2008) 2075–2085] and the Rowlinson–Bondi equation. Also, the predictive performance of general correlations of heats of vaporization based on the corresponding-states method, such as Carruth and Kobayashi [G.F. Carruth, R. Kobayashi, Ind. Eng. Chem. Fundam. 11 (1972) 509–516], Sivaraman et al. [A. Sivaraman, J.W. Magee, R. Kobayashi, Ind. Eng. Chem. Fundam. 23 (1984) 97–100], and Morgan and Kobayashi [D.L. Morgan, R. Kobayashi, Fluid Phase Equilib. 94 (1994) 51–87], as well as of a group contribution model [C.H. Tu, C.P. Liu, Fluid Phase Equilib. 121 (1996) 45–65], have been studied for fatty compounds. An alternative method in the prediction of heats of vaporization of fatty compounds based on the vapor pressure model of Ceriani and Meirelles [R. Ceriani, A.J.A. Meirelles, Fluid Phase Equilib. 215 (2004) 227–236] and its combination with the Clausius–Clapeyron equation has been studied.

In Silico Prediction of Molecular Volumes, Heat Capacities, and Temperature-Dependent Densities of Ionic Liquids

We present a fast and reliable general estimation of the heat capacity, Cp, and temperature-dependent density, ρ, of ionic liquids, based on a new in silico method to calculate the molecular volume, Vm. The knowledge of Vm allows the prediction of many physical properties of hitherto unknown ionic liquids as well as the prediction of lattice energies and entropies of salts.

Some observations regarding the prediction of isochoric heat capacities by engineering EOS models

This study evaluates the accuracy of different analytical EOS models in predicting isochoric heat capacity experimental data, a subject that has not received major attention so far. Contributions of the temperature dependency for the cohesive parameter, the Dieterici's and the expression derived for the description of association empirically attached to a generalized van der Waals-like equation, have been considered. It has been found that the temperature dependency of the cohesive parameter may improve the performance of the model at low temperatures and the expression derived for the description of association may qualitatively improve the description of the trend of the data near the critical temperature. None of the analyzed models can describe the behavior of the data at very high pressures.

Hydrogen bond networks determine emergent mechanical and thermodynamic properties across a protein family

BackgroundGram-negative bacteria use periplasmic-binding proteins (bPBP) to transport nutrients through the periplasm. Despite immense diversity within the recognized substrates, all members of the family share a common fold that includes two domains that are separated by a conserved hinge. The hinge allows the protein to cycle between open (apo) and closed (ligated) conformations. Conformational changes within the proteins depend on a complex interplay of mechanical and thermodynamic response, which is manifested as an increase in thermal stability and decrease of flexibility upon ligand binding.ResultsWe use a distance constraint model (DCM) to quantify the give and take between thermodynamic stability and mechanical flexibility across the bPBP family. Quantitative stability/flexibility relationships (QSFR) are readily evaluated because the DCM links mechanical and thermodynamic properties. We have previously demonstrated that QSFR is moderately conserved across a mesophilic/thermophilic RNase H pair, whereas the observed variance indicated that different enthalpy-entropy mechanisms allow similar mechanical response at their respective melting temperatures. Our predictions of heat capacity and free energy show marked diversity across the bPBP family. While backbone flexibility metrics are mostly conserved, cooperativity correlation (long-range couplings) also demonstrate considerable amount of variation. Upon ligand removal, heat capacity, melting point, and mechanical rigidity are, as expected, lowered. Nevertheless, significant differences are found in molecular cooperativity correlations that can be explained by the detailed nature of the hydrogen bond network.ConclusionNon-trivial mechanical and thermodynamic variation across the family is explained by differences within the underlying H-bond networks. The mechanism is simple; variation within the H-bond networks result in altered mechanical linkage properties that directly affect intrinsic flexibility. Moreover, varying numbers of H-bonds and their strengths control the likelihood for energetic fluctuations as H-bonds break and reform, thus directly affecting thermodynamic properties. Consequently, these results demonstrate how unexpected large differences, especially within cooperativity correlation, emerge from subtle differences within the underlying H-bond network. This inference is consistent with well-known results that show allosteric response within a family generally varies significantly. Identifying the hydrogen bond network as a critical determining factor for these large variances may lead to new methods that can predict such effects.

Prediction of heat capacity, density and freezing point of liquid refrigerant solutions using an excess Gibbs energy model

Immersion chilling and freezing (ICF) of foods use aqueous solutions at low temperature that are considered secondary refrigerants. These solutions contain solutes such as NaCl, CaCl 2, KCl, ethanol, glucose, etc. The ICF processes have several advantages over the conventional food chilling and freezing methods. The aim of this work was to study the behavior of an excess Gibbs energy model for predicting thermodynamic properties of mixtures of electrolytes and non-electrolytes, considering the physical conditions used in immersion chilling and freezing of foods. The extended UNIQUAC model was used. Data obtained from literature for heat capacity, density and freezing point for binary aqueous solutions of NaCl, CaCl 2, KCl and ethanol were compared with predicted values. Additional parameters for the density estimation were included into the model. In general, the model accuracy was satisfactory.

Application of CALPHAD to high pressures

The current methods of performing CALPHAD (CALculation of PHAse Diagrams) calculations of high-pressure phase equilibria often lead to spurious predictions of negative thermal expansion or negative heat capacity at high pressures. It is shown that the origin of the problem lies in an incompatibility between the temperature dependence of the widely used SGTE (Scientific Group Thermodata Europe) database and that of typical equations of state of the Mie–Grüneisen type. This inconsistency is also linked to the general problem of describing mechanical instability in CALPHAD. In the present work, a new free energy formulation is developed specifically for inclusion of pressure effects in CALPHAD methodology. It is based on an interpolation between SGTE data at low pressures and the quasiharmonic lattice model at high pressures. The new formulation is constrained to physically credible predictions of the thermophysical properties, while preserving the simplicity of the CALPHAD method. Examples are given of calculations of thermophysical properties and high-pressure phase equilibria in Al, Si, MgO, Fe and the Al–Si binary alloy system.

Prediction of sound velocity and heat capacities of n-alkanes from the modified SAFT-BACK equation of state

Based on thermodynamic perturbation theory of Wertheim, statistical associating fluid theory (SAFT) has proven to be quite successful in the prediction of thermodynamic properties of polar and non-polar fluids. In this work, a new version of SAFT (modified SAFT-BACK) equation of state has been developed to determine the speed of sound for some chain fluids (from C 1 to C 10) in the wide density and temperature ranges including critical temperature. We have also calculated the isobaric and isochoric heat capacities over the wide density and temperature ranges, including liquid and supercritical regions. Moreover, we have investigated the different microscopic contributions to the isochoric heat capacity. The ability of the modified SAFT-BACK EOS to predict the speed of sound and heat capacities of chain fluids near and far from critical regions is discussed.

Prediction of liquid heat capacities by the group contribution equation of state VTPR

Liquid heat capacities of 33 pure compounds have been calculated using the group contribution equation of state VTPR (volume translated Peng–Robinson). Since the predicted heat capacities were not always in good agreement with the experimental data, systematic investigations were performed to improve the situation. Distinct improvements were obtained by fitting the Twu-α-parameters simultaneously to vapor pressure, enthalpy of vaporization and heat capacity data.

Amino acid substitutions affecting protein dynamics in eglin C do not affect heat capacity change upon unfolding

The heat capacity change upon unfolding (deltaC(p)) is a thermodynamic parameter that defines the temperature dependence of the thermodynamic stability of proteins; however, physical basis of the heat capacity change is not completely understood. Although empirical surface area-based calculations can predict heat capacity changes reasonably well, accumulating evidence suggests that changes in hydration of those surfaces is not the only parameter contributing to the observed heat capacity changes upon unfolding. Because packing density in the protein interior is similar to that observed in organic crystals, we hypothesized that changes in protein dynamics resulting in increased rigidity of the protein structure might contribute to the observed heat capacity change upon unfolding. Using differential scanning calorimetry we characterized the thermodynamic behavior of a serine protease inhibitor eglin C and two eglin C variants with altered native state dynamics, as determined by NMR. We found no evidence of changes in deltaC(p) in either of the variants, suggesting that changes in rigidity do not contribute to the heat capacity change upon unfolding in this model system.