Coupling dynamic response of saturated soil with anisotropic thermal conductivity under fractional order thermoelastic theory.

In this paper, a two-dimensional (2D) thermo-hydro-mechanical dynamic (THMD) coupling analysis in the presence of a half-space medium is studied using Ezzat's fractional order generalized theory of thermoelasticity. Using normal mode analysis (NMA), the influence of the anisotropy of the thermal conduction coefficient, fractional derivatives, and frequency on the THMD response of anisotropy, fully saturated, and poroelastic subgrade is then analyzed with a time-harmonic load including mechanical load and thermal source subjected to the surface. The general relationships among the dimensionless physical variables such as the vertical displacement, excess pore water pressure, vertical stress, and temperature distribution are graphically illustrated. The NMA method does not require the integration and inverse transformation, increases the decoupling speed, and eliminates the limitation of numerical inverse transformation. The obtained results can guide the geotechnical engineering construction according to different values of load frequency, fractional order coefficient, and anisotropy of thermal conduction coefficient. This improves the subgrade stability and enriches the theoretical studies on thermo-hydro-mechanical coupling.

High thermal conductivity regenerated cellulose/carboxylated carbon nanotubes composite films with semi-insulating properties prepared via ionic coordination and hydrothermal synthesis of zinc oxide.

With the rapid development of miniaturization and integration of electronic products, its heat dissipation has become the focus of research. In order to improve the heat dissipation efficiency of electronic components, flexible thermal conduction materials are constantly studied. Cellulose has good flexibility and load capacity, which is often used in the preparation of thermal conduction materials. In this paper, carboxylated multi-walled carbon nanotubes (C-MWCNTs) were modified by metal ion coordination and hydrothermal synthesis of zinc oxide (ZnO) to prepare semi-insulating thermal conduction fillers, which were dispersed into regenerated cellulose (RC) to cast to be composite films. The results show that the two modification methods can reduce the probability of phonon scattering and block the electron transport path, so as to improve the thermal conductivity (TC) and electrical insulation properties of the composite films. Especially for the RC/C-MWCNTs@ZnO composite films, when the total filler content is 20 wt%, the in-plane TC can reach 11.89 ± 0.19 (W/(m·K)), and the surface electrical resistivity (ρs) is (5.24 ± 0.17) × 106 Ω. Compared with the RC/C-MWCNTs composite films, the in-plane TC and ρs of the RC/C-MWCNTs@ZnO composites films are increased by about 94.92 % and 555 %, respectively. Therefore, the developed RC-based composite film has broad application prospects in thermal management.

Heat conduction in live tissue during radiofrequency electrosurgery.

In this paper, we propose a method to model radiofrequency electrosurgery to capture the phenomena at higher temperatures and present the methods for parameter estimation. Experimental data taken from our surgical trials performed on in vivo porcine liver show that a non-Fourier Maxwell-Cattaneo-type model can be suitable for this application when used in combination with an Arrhenius-type model that approximates the energy dissipation in physical and chemical reactions. The resulting model structure has the advantage of higher accuracy than existing ones, while reducing the computation time required.

Effect of interface layer on the enhancement of thermal conductivity of SiC-Water nanofluids: Molecular dynamics simulation.

To investigate the impact of interfacial layer effects on the thermal conductivity of nanofluids and the microscopic mechanisms of enhanced thermal conductivity, this study employed non-equilibrium molecular dynamics to compute the thermal conductivity, number density, radial distribution function, and mean square displacement distribution of SiC nanofluids. The impact of nanoparticle volume fraction and particle size parameters on the thermal conductivity of nanofluids and the structure of interfacial adsorption layers was discussed. The simulation calculation results show that the coefficient of thermal conductivity of nanofluid is positively related to the volume fraction of nanoparticles, increasing from 0.6529 W/(m·K) to 0.8159 W/(m·K), and the enhancement of thermal conductivity by the volume fraction can be up to 33.97 %. The thermal conductivity is inversely correlated with the change in particle size, and the maximum improvement in thermal conductivity by particle size can reach up to 12.05 %. The simulated results of the thermal conductivity of nanofluid are almost consistent with the predicted results of the Yu&Choi model, and the error is controlled within 5 %. Simultaneously, the thickness of the interfacial adsorption layer decreases with an increase in particle size. This reduction arises due to larger particles having a smaller specific surface area, resulting in fewer particle surfaces covered by the interface layer. Moreover, the impact of particle size on the arrangement and affinity of molecules within the interface layer contributes to this decrease. Overall, interface layer effects exhibit a dual impact on the thermal conduction of nanofluids. The structured formation and high-density distribution of the adsorption layer contribute to enhanced heat transfer, while thermal resistance between nanoparticle surfaces and the fluid restricts heat transmission.

Generalized thermomechanical interaction in two-dimensional skin tissue using eigenvalues approach.

The aim of this work is to analytically study the thermo-mechanical response of two-dimensional skin tissues when subjected to instantaneous heating. A complete understanding of the heat transfer process and the associated thermal and mechanical effects on the patient's skin tissues is critical to ensuring the effective applications of thermal therapy techniques and procedures. The surface boundary of the half-space undergoes a heat flux characterized by an exponentially decaying pulse, while maintaining a condition of zero traction. The utilization of Laplace and Fourier transformations is employed, and the resulting formulations are then applied to human tissues undergoing regional hyperthermia treatment for cancer therapy. To perform the inversion process for Laplace and Fourier transforms, a numerical programming method based on Stehfest numerical inverse method is employed. The findings demonstrate that blood perfusion rate and thermal relaxation time significantly influence all the analyzed distributions. Numerical findings suggest that thermo-mechanical waves propagate through skin tissue over finite distances, which helps mitigate the unrealistic predictions made by the Pennes' model.

Characterization of the Optical and Thermal Properties of Cardiac Tissue as a Function of Temperature.

In this work, we devised the first characterization of the optical and thermal properties of ex vivo cardiac tissue as a function of different selected temperatures, ranging from room temperature to hyperthermic and ablative temperatures. The broadband (i.e., from 650 nm to 1100 nm) estimation of the optical properties, i.e., absorption coefficient (µa) and reduced scattering coefficient $({\mu ^{\prime}}_s)$, was performed by means of time-domain diffuse optics. Besides, the measurement of the thermal properties was based on the transient hot-wire technique, employing a dual-needle probe to estimate the tissue thermal conductivity (k), thermal diffusivity (α), and volumetric heat capacity (Cv). Increasing the tissue temperature led to variations in the spectral characteristics of µa (e.g., the redshift of the 780 nm peak, the rise of a new peak at 840 nm, and the formation of a valley at 900 nm). Moreover, an increase in the values of ${\mu ^{\prime}}_s$ was assessed as tissue temperature raised (e.g., for 800 nm, at 25 °C ${\mu ^{\prime}}_s = 9.8{\text{ c}}{{\text{m}}^{{\text{ - 1}}}}$, while at 77 °C ${\mu ^{\prime}}_s = 29.1{\text{ c}}{{\text{m}}^{{\text{ - 1}}}}$). Concerning the thermal properties characterization, k was almost constant in the selected temperature interval. Conversely, α and Cv were subjected to an increase and a decrease with temperature, respectively; thus, they registered values of 0.190 mm2/s and 3.03 MJ/(m3•K) at the maximum investigated temperature (79 °C), accordingly.Clinical Relevance- The experimentally obtained optical and thermal properties of cardiac tissue are useful to improve the accuracy of simulation-based tools for thermal therapy planning. Furthermore, the measured properties can serve as a reference for the realization of tissue-mimicking phantoms for medical training and testing of medical instruments.

Effect of the alumina micro-particle sizes on the thermal conductivity and dynamic mechanical property of epoxy resin.

Epoxy thermal conductive adhesives with high thermal conductivity and dynamic mechanical properties are important thermally conductive materials for fabricating highly integrated electronic devices. In this paper, micro-Al2O3 is used as a thermally conductive filler for the epoxy resin composite and investigated the effect of micron-sized alumina particle size on the thermal conductivity and dynamic mechanical property of epoxy resin by the transient planar hot plate method and DMA (Dynamic mechanical analysis). The experimental results show that with the same amount of alumina filling, the thermal conductivity and Tg (glass transition temperature) of epoxy/Al2O3 composite material decrease with the increase of alumina particle size. The maximum thermal conductivity of the composite material is 0.679 (W/mK), while the energy storage modulus of epoxy/Al2O3 composite material increases with the increase of alumina particle size, and the maximum energy storage modulus of the composite material is 160MPa. Compared with pure epoxy resin, the thermal conductivity and energy storage modulus have increased by 2.7 and 3.2 times, respectively. The epoxy/Al2O3 composite was applied to the COB (Chips On Board) type LED package, and the substrate temperature of the LED dropped to the lowest after 1.5 hours of operation using EP-A5 composite, and the temperature was stabilized at 38.2°C, indicating that the addition of 5-micron alumina composite has the best heat dissipation in the COB type LED package. These results are critical for the implementation of particulate-filled polymer composites in practical applications because relaxed material specifications and handling procedures can be incorporated in production environments to improve efficiency.

Study on thermal conductivity of improved soil under different freezing temperatures.

Based on the influence of moisture content, dry density and temperature (≦ 0°C) on the thermal conductivity of lime-modified red clay, the thermal conductivity was measured by transient hot wire method. A total of 125 data were obtained and the evolution law of thermal conductivity with influencing factors was analyzed. The fitting formula of thermal conductivity of lime-modified red clay and a variety of intelligent prediction models were established and compared with previous empirical formulas. The results show that the thermal conductivity of lime-modified red clay increases linearly with water content and dry density. The change of thermal conductivity with temperature is divided into three stages. In the first stage, the thermal conductivity increases slowly with the decrease of temperature in the temperature range of-2°Cto 0°C. In the second stage, in the temperature range of-5°Cto (-2)°C, the thermal conductivity increases rapidly with the decrease of temperature. In the third stage, in the range of-10°Cto (-5)°C, the thermal conductivity changes little with the decrease of temperature, and the fitting curve tends to be stable. The fitting formula model and various intelligent prediction models can realize the accurate prediction of the thermal conductivity of lime-improved soil. Using RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error) to evaluate the model, it is found that the GBDT decision tree model has the best prediction effect, the RMSE value of the predicted value is 0.084, and the MAPE value is 4.1%. The previous empirical models have poor prediction effect on the thermal conductivity of improved red clay. The intelligent prediction models such as GBDT decision tree with strong universality and high prediction accuracy are recommended to predict the thermal conductivity of soil.

Toward Three-Dimensional Printed Thermal Conductive Polymeric Composites Using a Binary-Composite Hybrid Based on Boron Nitride Nanoparticles and Micro-Diamonds.

Thermally conductive polymeric composites are promising for heat management in microelectronic devices. This work presents a binary-hybrid composite of boron nitride (BN) nanoparticles and micro-diamond (D) fillers in an elastomeric polyurethane (PU) matrix which can be three- dimensionally printed to produce a highly flexible and self-supporting structure. The research shows that a combination of 16.7 wt% BN and 16.7 wt% D results in a robust network within the polymer matrix to improve the tensile modulus more than nine times with respect to neat PU. Significantly, the hybrid matrix enhances the thermal conductivity by more than two times when compared to neat PU. The enhancement in mechanical, and thermal features make this three-dimensional printable multiscale hybrid composite suitable for flexible and stretchable microelectronic applications.

Machine learning-based models for accessing thermal conductivity of liquids at different temperature conditions.

Combating global warming-related climate change demands prompt actions to reduce greenhouse gas emissions, particularly carbon dioxide. Biomass-based biofuels represent a promising alternative fossil energy source. To convert biomass into energy, numerous conversion processes are performed at high pressure and temperature conditions, and the design and dimensioning of such processes requires thermophysical property data, particularly thermal conductivity, which are not always available in the literature. In this paper, we proposed the application of Chemoinformatics methodologies to investigate the prediction of thermal conductivity for hydrocarbons and oxygenated compounds. A compilation of experimental data followed by a careful data curation were performed to establish a database. The support vector machine algorithm has been applied to the database leading to models with good predictive abilities. The support vector regression (SVR) model has then been applied to an external set of compounds, i.e. not considered during the training of models. It showed that our SVR model can be used for the prediction of thermal conductivity values for temperatures and/or compounds that are not covered experimentally in the literature.

Measurement of Thermal Conductivity and Thermal Diffusivity of Porcine and Bovine Kidney Tissues at Supraphysiological Temperatures up to 93 °C.

This experimental study aimed to characterize the thermal properties of ex vivo porcine and bovine kidney tissues in steady-state heat transfer conditions in a wider thermal interval (23.2-92.8 °C) compared to previous investigations limited to 45 °C. Thermal properties, namely thermal conductivity (k) and thermal diffusivity (α), were measured in a temperature-controlled environment using a dual-needle probe connected to a commercial thermal property analyzer, using the transient hot-wire technique. The estimation of measurement uncertainty was performed along with the assessment of regression models describing the trend of measured quantities as a function of temperature to be used in simulations involving heat transfer in kidney tissue. A direct comparison of the thermal properties of the same tissue from two different species, i.e., porcine and bovine kidney tissues, with the same experimental transient hot-wire technique, was conducted to provide indications on the possible inter-species variabilities of k and α at different selected temperatures. Exponential fitting curves were selected to interpolate the measured values for both porcine and bovine kidney tissues, for both k and α. The results show that the k and α values of the tissues remained rather constant from room temperature up to the onset of water evaporation, and a more marked increase was observed afterward. Indeed, at the highest investigated temperatures, i.e., 90.0-92.8 °C, the average k values were subject to 1.2- and 1.3-fold increases, compared to their nominal values at room temperature, in porcine and bovine kidney tissue, respectively. Moreover, at 90.0-92.8 °C, 1.4- and 1.2-fold increases in the average values of α, compared to baseline values, were observed for porcine and bovine kidney tissue, respectively. No statistically significant differences were found between the thermal properties of porcine and bovine kidney tissues at the same selected tissue temperatures despite their anatomical and structural differences. The provided quantitative values and best-fit regression models can be used to enhance the accuracy of the prediction capability of numerical models of thermal therapies. Furthermore, this study may provide insights into the refinement of protocols for the realization of tissue-mimicking phantoms and the choice of tissue models for bioheat transfer studies in experimental laboratories.

Interaction, Insensitivity and Thermal Conductivity of CL-20/TNT-Based Polymer-Bonded Explosives through Molecular Dynamics Simulation.

Binders mixed with explosives to form polymer-bonded explosives (PBXs) can reduce the sensitivity of the base explosive by improving interfacial interactions. The interface formed between the binder and matrix explosive also affects the thermal conductivity. Low thermal conductivity may result in localized heat concentration inside the PBXs, causing the detonation of the explosive. To investigate the binder-explosive interfacial interactions and thermal conductivity, PBXs with polyurethane as the binder and 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane/2,4,6-trinitrotoluene (CL-20/TNT) co-crystal as the matrix explosive were investigated through molecular dynamics (MD) simulations and reverse non-equilibrium molecular dynamics (rNEMD) simulation. The analysis of the pair correlation function revealed that there are hydrogen bonding interactions between Estane5703 and CL-20/TNT. The length of the trigger bonds was adopted as a theoretical criterion of sensitivity, and the effect of polymer binders on the sensibility of PBXs was correlated by analyzing the interfacial trigger bonds and internal trigger bonds of PBXs for the first time. The results indicated that the decrease in sensitivity of CL-20/TNT mainly comes from the CL-20/TNT contact with Estane5703. Therefore, the sensitivity of CL-20/TNT-based PBXs can be further reduced by increasing the contact area between CL-20/TNT and Estane5703. The thermal conductivity of PBXs composed of Estane5703 and CL-20/TNT (0 0 1), (0 1 0) and (1 0 0) crystal planes, respectively, were calculated through rNEMD simulations, and the results showed that only the addition of Estane5703 to the (1 0 0) crystal plane can improve the thermal conductivity of PBX100.

A new model to predict soil thermal conductivity.

Thermal conductivity is a basic parameter of soil heat transferring, playing an important role in many fields including groundwater withdrawal, ground source heat pump, and heat storage in soils. However, it usually requires a lot of time and efforts to obtain soil thermal conductivity. To conveniently obtain accurate soil thermal conductivity, a new model describes the relationship between soil thermal conductivity (λ) and degree of saturation (Sr) was proposed in this study. Dry soil thermal conductivity (λdry) and saturated soil thermal conductivity (λsat) were described using a linear expression and a geometric mean model, respectively. A quadratic function with one constant was added to calculate λ beyond the lower λdry and upper λsat limit conditions. The proposed model is compared with five other frequently used models and measured data for 51 soil samples ranging from sand to silty clay loam. Results show that the proposed model match the measured data well. The proposed model can be used to determine soil thermal conductivity of a variety of soil textures over a wide range of water content.

Hydrogen online monitoring based on thermal conductivity for anaerobic microorganisms.

H2 -producing microorganisms are a promising source of sustainable biohydrogen. However, most H2 -producing microorganisms are anaerobes, which are difficult to cultivate and characterize. While several methods for measuring H2 exist, common H2 sensors often require oxygen, making them unsuitable for anaerobic processes. Other sensors can often not be operated at high gas humidity. Thus, we applied thermal conductivity (TC) sensors and developed a parallelized, online H2 monitoring for time-efficient characterization of H2 production by anaerobes. Since TC sensors are nonspecific for H2 , the cross-sensitivity of the sensors was evaluated regarding temperature, gas humidity, and CO2 concentrations. The systems' measurement range was validated with two anaerobes: a high H2 -producer (Clostridium pasteurianum) and a low H2 -producer (Phocaeicola vulgatus). Online monitoring of H2 production in shake flask cultivations was demonstrated, and H2 transfer rates were derived. Combined with online CO2 and pressure measurements, molar gas balances of the cultivations were closed, and an anaerobic respiration quotient was calculated. Thus, insight into the effect of medium components and inhibitory cultivation conditions on H2 production with the model anaerobes was gained. The presented online H2 monitoring method can accelerate the characterization of anaerobes for biohydrogen production and reveal metabolic changes without expensive equipment and offline analysis.

Performance analysis of a parabolic trough collector using partial metal foam inside an absorber tube: an experimental study.

This paper offers an experimental investigation of the effect of metal foam on the thermal and hydrodynamic performance of a parabolic trough collector (PTC). Metal foams play a crucial role in heat transfer improvement due to their high thermal conductivity. Three different arrangements of metal foams are applied inside the absorber tube of the PTC. The flow regime in the absorber tube is laminar at different Reynolds numbers of 422, 844, 1267, and 1689. Experimental tests are designed with Design-Expert software in which the response surface method is utilized. Experimental results revealed that maximum enhancement in thermal efficiency is related to the periodic array arrangement of the metal foam inside the tube. This arrangement leads to a 14% increase in thermal efficiency. However, in this arrangement, the friction factor increases considerably compared to a plain receiver tube.

Thermal conductivity vs depth profiling using the hot disk technique-Analysis of anisotropic, inhomogeneous structures.

A recently developed method for analyzing the thermal conductivity vs depth variation near a sample surface has been extended to include inhomogeneous samples with anisotropy. If not considered, the anisotropy ratio in the sample structure can distort the depth-position data of the original test method. The anisotropy ratio is introduced in the original computational scheme in order to improve the depth-position estimations for inhomogeneous structures with anisotropy. The proposed approach has been tested in experiments and shown to improve depth position mapping.

Experimental study on pore structure characteristics and thermal conductivity of fibers reinforced foamed concrete.

The pore structure characteristics and thermal conductivity of foamed concrete (FC) reinforced with glass fibers (GF), polyvinyl alcohol fibers (PVAF) and polypropylene fibers (PPF) were investigated experimentally in this article. Firstly, GF, PVAF or PPF with different mass fractions (0%, 1%, 1.5% and 2%) were added to the Portland cement, fly ash and plant protein foaming agent to prepare the FC. Then, SEM tests, dry density tests, porosity tests, and thermal conductivity tests were carried out on FRFC. Later, the adhesion of GF, PVAF and FFF with different mass fractions to the cementitious base was investigated by SEM images of FRFC. The pore size distribution, shape factor and porosity of FRFC were analyzed using Photoshop software and Image Pro Plus (IPP) software. Finally, the effects of different mass fractions and lengths of three types of fibers on the thermal conductivity of FRFC were discussed. The results indicated that proper fiber mass fraction can play a role of refining small pores and separating large pores, improving the structural compactness, reducing the pore collapse phenomenon and optimizing the pore structure of FRFC. The three types of fibers can promote the optimization of cellular roundness and increase the proportion of pores with diameters below 400 µm. The FC with larger porosity had smaller dry density. As the fiber mass fraction increased, the thermal conductivity performed a phenomenon of first decrease and then increase. The three types of fibers with 1% mass fraction achieved relatively low thermal conductivity. Compared with the FC without fibers, the thermal conductivities of GF reinforced FC, PVAF reinforced FC and PPF reinforced FC with 1% mass fraction were decreased by 20.73%, 18.23% and 7.00%, respectively.

Investigation of memory influences on bio-heat responses of skin tissue due to various thermal conditions.

Advancement of new technologies such as laser, focused ultrasound, microwave and radio frequency for thermal therapy of skin tissue has increased numerous challenging situations in medical treatment. In this article, a new meticulous bio-heat transfer model based on memory-dependent derivative with dual-phase-lag has been developed under different thermal conditions such as thermal shock and harmonic-type heating. Laplace transform method is acquired to perceive the analytical consequences. Quantitative results are evaluated for displacement, strain and temperature along with stress distributions in time domain by adopting the technique of inverse Laplace transform. Impacts of the constituents of memory-dependent derivatives-kernel functions along with time-delay parameter are analysed on the studied fields (temperature, displacement, strain and stress) for both thermal conditions separately using computational results. It has been found that the insertion of the memory effect proves itself a unified model, and therefore, this model can better predict temperature field data for thermal treatment processes.

Numerical simulation of burn injuries with temperature-dependent thermal conductivity and metabolism under different surface heat sources.

In the present paper, the phenomena of heat transport inside human forearm tissue are studied through a one-dimensional nonlinear bioheat transfer model under the influence of various boundary and interface conditions. In this study, we considered temperature-dependent thermal conductivity and metabolic heat to predict temperature distribution inside the forearm tissue. We have studied the temperature distribution inside inner tissue and bone because it has been found that burn injuries are mostly affected by layer thickness. The temperature distribution inside human forearm tissue is analyzed using the finite difference and bvp4c numerical techniques. To examine the accuracy of present numerical code, we compare the obtained numerical result with the exact analytical result in a specific case and find an excellent agreement with the exact results. We also validated our present numerical code with a hybrid scheme based on Runge-Kutta (4,5) and finite difference technique and found it in good compliance. From the obtained results, we observed that the homogeneous heat flux has a greater impact on the temperature at the outer surface of the skin, but the sinusoidal heat flux has a greater impact on the temperature of the subcutaneous layer and inner tissue. It is found that there is no burn injury in the first type of heat source (Tw=44°C), but it may occur in the second and third types of heat sources. It has been observed that by raising the blood perfusion rate and reducing the values of reference metabolic heat, coefficient of thermal conductivity, and heat fluxes, we can manage and reduce burn injuries and achieve hyperthermia temperature.

Revised Enskog theory for Mie fluids: Prediction of diffusion coefficients, thermal diffusion coefficients, viscosities, and thermal conductivities.

Since the 1920s, the Enskog solutions to the Boltzmann equation have provided a route to predicting the transport properties of dilute gas mixtures. At higher densities, predictions have been limited to gases of hard spheres. In this work, we present a revised Enskog theory for multicomponent mixtures of Mie fluids, where the Barker-Henderson perturbation theory is used to calculate the radial distribution function at contact. With parameters of the Mie-potentials regressed to equilibrium properties, the theory is fully predictive for transport properties. The presented framework offers a link between the Mie potential and transport properties at elevated densities, giving accurate predictions for real fluids. For mixtures of noble gases, diffusion coefficients from experiments are reproduced within ±4%. For hydrogen, the predicted self-diffusion coefficient is within 10% of experimental data up to 200 MPa and at temperatures above 171 K. Binary diffusion coefficients of the CO2/CH4 mixture from simulations are reproduced within 20% at pressures up to 14.7 MPa. Except for xenon in the vicinity of the critical point, the thermal conductivity of noble gases and their mixtures is reproduced within 10% of the experimental data. For other molecules than noble gases, the temperature dependence of the thermal conductivity is under-predicted, while the density dependence appears to be correctly predicted. Predictions of the viscosity are within ±10% of the experimental data for methane, nitrogen, and argon up to 300 bar, for temperatures ranging from 233 to 523 K. At pressures up to 500 bar and temperatures from 200 to 800 K, the predictions are within ±15% of the most accurate correlation for the viscosity of air. Comparing the theory to an extensive set of measurements of thermal diffusion ratios, we find that 49% of the model predictions are within ±20% of the reported measurements. The predicted thermal diffusion factor differs by less than 15% from the simulation results of Lennard-Jones mixtures, even at densities well exceeding the critical density.