Thermal Conductivity Of Matrix Research Articles

Synergistic effect of amino and hydroxyl bifunctional modified h-BN on interfacial thermal conductivity in polydimethylsiloxane matrix: Simulations and experiments

As a widely used thermal conductive matrix material, the interface problem between polydimethylsiloxane (PDMS) and thermal conductive fillers needs to be solved urgently. The interfacial heat transfer mechanism between PDMS and hexagonal boron nitride (h-BN) modified by different groups was studied by combining density functional theory (DFT) simulation and molecular dynamics (MD) simulation. The bi-functionalization of h-BN was achieved by the environmentally friendly 6-aminocaproic acid (ACA) additive-assisted water ball milling process. The h-BN/PDMS composite thermal interface materials were prepared using a simple rolling method. The thermal conductivity of the obtained sample reached 1.256 W m−1 K−1 at a filler loading of 15 wt%. The proposed bifunctional synergistic heat transfer mechanism is expected to provide theoretical guidance for the preparation of high thermal conductivity and insulating PDMS used in electronic communications.

Application of machine learning in predicting the thermal conductivity of single-filler polymer composites

Polymer composites with superior thermal conductivity and low electrical conductivity are pivotal in the cooling of electronic devices. Despite their prevalence, the accurate prediction of the thermal conductivity of these composites remains a challenge. The emergence of machine learning (ML) provides a groundbreaking approach to solving this issue. In this study, we constructed a comprehensive dataset collected from previous experimental papers and successfully predicted the thermal conductivity of single-filler polymer composites using four ML regression algorithms: random forest regression (RFR), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and Gaussian process regression (GPR). By employing feature engineering to select pertinent features from the original datasets, the accuracy of the four models on the test set was improved, among which GBDT exhibited the highest accuracy with the Pearson correlation coefficient value of 0.981. Factors such as filler volume fraction and matrix thermal conductivity significantly influence the thermal conductivity of composite materials, while the thermal conductivity of the fillers has a relatively minor impact. Additionally, we identified the topological polar surface area (TPSA) as a crucial descriptor for surface modifications, quantifying diverse surface-modifying agents. Due to the incorporation of more descriptors, ML models exhibit higher precision and broader applicability compared to empirical formulas. Our study provides an effective tool for predicting the thermal conductivity of polymer composites with single fillers and underscores the potential of machine learning in accelerating materials design.

Machine learning backpropagation network analysis of permeability, Forchheimer coefficient, and effective thermal conductivity of macroporous foam–fluid systems

Macroporous materials exhibit outstanding properties in heat and mass transfer due to their high pore volume, high surface area, and high Young's modulus. Consequently, understanding their thermofluidic properties is crucial in the design, synthesis, and optimal application of these materials. Therefore, this study, premieres, the use of a machine learning (ML) backpropagation network to develop and train a series of datasets for permeability, Forchheimer coefficient, and effective thermal conductivity of variable macroporous foam–fluid systems with respect to degrees of interstices, fluid and solid properties. To account for permeability values for flowing fluids in the Darcy regime, numerical simulations of slow–moving fluids were implemented over the materials' interstices. In comparison to similarly substantiated values of permeability in the Forchheimer regime, these values were a bit lower. The ML-based backpropagation algorithm was used to analyze data, which produced predictions (output signals) that are more than 90 % in correlation to CFD datasets. This provided insight into the effect of porosity and reduced mean pore openings on macroporous structures' thermofluidic behaviour. Material porosity was observed to play a dominant role in estimating Forchheimer coefficients and effective thermal conductivities for these foam-fluid systems. However, reduced mean pore openings were observed to be more critical for estimating permeability. The contributory effects of reduced mean pore openings on the effective thermal conductivity for these macroporous foam–fluid systems were determined to vary between 5.8 and 13.2 percent. Furthermore, the effective thermal conductivity of macroporous foam–fluid systems was also evaluated in relation to changes in the interstitial fluid and solid matrix thermal conductivity.

Thermal hydraulic method of optimizing the thermal resistance of nuclear fuel of reactor installations

An original thermal-hydraulic method for optimizing the thermal resistance of thermal conductivity of fuel rod matrix upgrades has been developed to achieve the maximum burnup depth of nuclear fuel while ensuring safety conditions in operating and emergency modes of nuclear power plants. Based on the developed method, the boundaries of the optimization area for upgrades of the thermal resistance of the fuel rod matrix thermal conductivity are determined in accordance with the accepted optimization criteria and safety conditions. It is established that when optimizing upgrades to the thermal resistance of nuclear fuel, it is necessary to take into account both normal operating conditions and emergency conditions with impaired heat removal from the reactor core. It is established that the optimal values of thermal resistance of nuclear fuel thermal conductivity depend on the design and technical parameters of reactor installations, composition, and condition of nuclear fuel, accident management systems, and other factors.

Performance of Ce:YAG-MgO composite ceramics as high-power LED phosphor densified by non-reactive sintering

A novel white light converter has been successfully synthesized using a non-reactive sintering process to afford a fully densified Ce:YAG-MgO composite ceramic phosphor with high wavelength conversion efficiency under excitation at 450 nm. The composite obtained by HIP (hot isostatic pressing) treatment at 1080 ºC has no residual pores and the XRD (X-ray diffraction) analysis shows that there are no secondary phases other than Ce:YAG and MgO, moreover, the EDS (Energy-dispersive X-ray spectroscopy) analysis indicates no interdiffusion at the Ce:YAG-MgO contact interface. The thermal conductivity of 5–7.5 wt% Ce:YAG-added MgO composites is over 40 W/mK, nearly reaching the theoretical value. Due to the synergetic effect of “the difference in refractive index between MgO and Ce:YAG” and “MgO matrix with strong birefringence”, the excitation light (450 nm) is multiply scattered inside the composite medium, which provides efficient excitation even in a thin medium, resulting in the photoluminescence intensity that is 2.6 times higher than that of transparent Ce:YAG ceramics. This innovative white light converter combines a highly thermal conductive MgO matrix and Ce:YAG phosphor with high emission intensity.

Experimental study on an integrated system of thermosyphon loop and vapor compression assisted with phase change material for pulse heat load

In order to safely and energy-efficient handle the pulse heat load of avionics, the paper proposes an integrated system of thermosyphon loop and vapor compression cycle, especially assisted with phase change material (PCM). Under low heat load and heat sink temperature, the system operates as a thermosyphon loop (TL) for energy saving; otherwise as a vapor compression cycle (VCC) for safety. A prototype of the integrated system was developed, where a whole three-dimensional (3D) printed structure worked as the evaporator of the system, consisting of a mini-channel cold plate and a high thermal-conductivity matrix containing PCM. The dynamic performance of the proposed system has been experimented under different pulse heat loads and heat sink temperatures, and compared to the integrated system without PCM and a traditional VCC. The proposed system can handle a peak heat load of 1000 W for 120 s without running the compressor, saving 100 % energy compared to traditional VCC. The PCM enhances both the safety and energy efficiency of the integrated system. On the one hand, it reduces wall temperature during the transition from TL to VCC, avoiding overheating issue. On the other hand, it reduces the operating time of VCC, which is more significant with lower peak heat load and heat sink temperature. Overall, the integrated system assisted with PCM is a promising solution for solving pulsating heat loads.

Interlayer growth of SiC nanowires in graphene aerogel for thermal conductivity enhancement of epoxy resin and its mechanism

AbstractThe chemical reduction method is a simple and popular way to contrast the graphene network to improve the polymer matrix's thermal conductivity. And hybrid thermal conductive fillers composed of two or more mixed fillers through chemical synthesis usually have better thermal conductivity because of the synergistic effort. In this work, silicon carbide nanowires (SiC NWs) in graphene aerogels are synthesized with the chemical vapor deposition method, acting as bridges for phonon transmission between adjacent graphene sheets. The RGO/SiC NWs aerogel‐endowed EP composites have a high thermal conductivity of 3.79 W/mK at a filler loading of 5.5 wt%, and 4.23 W/mK at a filler loading of 7.5 wt%, which is 1895% and 2126% higher than pure EP resin, respectively. Finite element analysis (FEA) is utilized to analyze the heat conduction mechanism of composites at last.

Thermoelectric coupling effect in BNT-BZT-xGaN pyroelectric ceramics for low-grade temperature-driven energy harvesting

Pyroelectric energy harvesting has received increasing attention due to its ability to convert low-grade waste heat into electricity. However, the low output energy density driven by low-grade temperature limits its practical applications. Here, we show a high-performance hybrid BNT-BZT-xGaN thermal energy harvesting system with environmentally friendly lead-free BNT-BZT pyroelectric matrix and high thermal conductivity GaN as dopant. The theoretical analysis of BNT-BZT and BNT-BZT-xGaN with x = 0.1 wt% suggests that the introduction of GaN facilitates the resonance vibration between Ga and Ti, O atoms, which not only contributes to the enhancement of the lattice heat conduction, but also improves the vibration of TiO6 octahedra, resulting in simultaneous improvement of thermal conductivity and pyroelectric coefficient. Therefore, a thermoelectric coupling enhanced energy harvesting density of 80 μJ cm−3 has been achieved in BNT-BZT-xGaN ceramics with x = 0.1 wt% driven by a temperature variation of 2 oC, at the optical load resistance of 600 MΩ.

Investigation on Thermal Conductivity Silver-coated Copper/GaInSn Composite Thermal Interface Materials

To enhance the heat transfer performance of GaInSn liquid metal, a new type of composite thermal interface material with GaInSn as thermal conductive matrix and silver-coated copper particles as thermal conductive fillers was prepared in this article. The morphology of the composites were characterized by scanning electron microscopy. The thermal conductivity of silver-coated copper/GaInSn composites with different silver-coated copper particle contents were measured by laser flash method. The interfacial bonding of the composites were investigated by X-ray diffraction. The results show that when the volume ratio of silver-coated copper particles is 15%, thermal conductivity of the silver-coated copper/GaInSn composite reaches the largest value of 25.01 W·m−1·K−1. The silver-coated copper/GaInSn composite material and commercially available thermal grease were put into the chip and copper plate to simulate the actual application scenarios for comparison. The heat dissipation capacity of silver-coated copper/GaInSn composite material is obviously better than that of the two commercially available thermal grease, and the chip temperature can be reduced by about 5°C.

Two-scale data-driven design for heat manipulation

Data-driven methods have gained increasing attention in computational mechanics and design. This study investigates a two-scale data-driven design for thermal metamaterials with various functionalities. To address the complexity of multiscale design, the design variables are chosen as the components of the homogenized thermal conductivity matrix originating from the lower scale unit cells. Multiple macroscopic functionalities including thermal cloak, thermal concentrator, thermal rotator/inverter, and their combinations, are achieved using the developed approach. Sensitivity analysis is performed to determine the effect of each design variable on the desired functionalities, which is then incorporated into topology optimization. Geometric extraction demonstrates an excellent matching between the optimized homogenized conductivity and the extraction from the constructed database containing both architecture and property information. The designed heterostructures exhibit multiple thermal meta-functionalities that can be applied to a wide range of heat transfer fields from personal computers to aerospace engineering.

Electromagnetic prediction of rock thermal properties beyond boreholes: Soultz-sous-Forets (France) case study

Estimation of deep temperature, thermo-hydro-dynamic and basin simulation, heat exchange and geothermal resource assessment require knowledge of the rock thermal properties beyond boreholes. At the absence of suitable methods and instruments for such estimates we propose a new approach to prediction of thermal conductivity, specific heat capacity and heat flow density based on results of electromagnetic sounding of the study area. Artificial neural network used to this end is taught by correspondence between laboratory measurements on cores from the drilled boreholes and adjacent electrical conductivity profiles determined by inversion of the electromagnetic sounding data collected in their vicinity. This approach is used to estimate rock thermal properties along NW-SE magnetotelluric profile crossing Soultz-sous-Forêts geothermal area, Alsace, France. We demonstrate that accuracy of such prediction both in depths below the boreholes and in the interwell space is comparable with that usually achievable in the borehole scale. In particular, it is shown that relative errors of thermal conductivity prediction at depths twice as large as the borehole depth are as small as 2%, and the accuracy of cross-well thermal conductivity prediction is 6% and 10% for dry and wet rocks, respectively. On the other hand, the prediction accuracy for matrix thermal conductivity of a rock from the known profile of dry thermal conductivity is about 8%. Based on the results of our studies, we constructed dry and wet thermal conductivity sections from the electrical conductivity model determined earlier by 2-D inversion of magnetotelluric data. The temperature model of the study area built along the same profile by means of electromagnetic geothermometer and the obtained thermal conductivity sections enabled estimating the profiles of the vertical component of heat flow density at the surface from dry and wet thermal conductivity sections. They could be considered as minimum and maximum constraints, respectively, bounding the area of its possible values, which, in turn, depend on in situ thermal conductivity of fluids filling the rock pores. The range of possible vertical heat flow density variations (100–150 ± 10% mW·m− 2) agrees well with heat flow estimates in the Upper Rhine graben and, in particular, in Soultz-sous-Forêts geothermal area roughly estimated earlier from borehole measurements. Using the artificial neural network trained on the correspondence between the specific heat capacity determined in the borehole and adjacent electrical conductivity profile, we built the model of specific heat capacity. Against the background, a zone of enhanced specific heat capacity ranging between 2.05 and 2.15 MJ·m− 3·K− 1 was observed in the domain located at the base of the sedimentary cover and upper part of the granitic basement.

Flexible and thermally conductive epoxy‐dispersed liquid crystal composites filled with functionalized boron nitride nanosheets

AbstractIn view of the problem of heat accumulation in electronic devices, the development of new composites with high thermal conductivity (TC) is the current research focus. Nowadays, improving TC often lead to inevitable deterioration of the mechanical properties of materials. In this work, the E‐functionalized boron nitride nanosheets (f‐BNNS)/liquid crystal monomer (LCM)/Epoxy‐thiol films with high TC were prepared by using flexible epoxy‐thiol polymer as matrix and LCM and f‐BNNS as thermal fillers via high voltage orientation molding. The epoxy‐thiol polymer possessed high intrinsic TC due to the regular arrangement of molecular chains and the f‐BNNS showed favorable dispersibility because of the modification by isopropyl tri(dioctylpyrophosphate) titanate (ITDPT). The results show that TC of E‐f‐BNNS/LCM/Epoxy‐thiol films with 30 wt% f‐BNNS content achieves 1.65 W/m·K and is 511.11% higher than that of pure epoxy‐thiol polymer (0.27 W/m·K). The tensile strength and elongation at break increase to 24.9 MPa and 47.41%, respectively. The favorable results are attributed to the ordered arrangement of f‐BNNS and molecular chains, resulting from the hydrogen‐bonding interaction between OH group in f‐BNNS, LCM and epoxy‐thiol polymer. This research provides a simple and feasible method for preparing flexible epoxy polymer films with high TC.Highlights The functional BNNS was achieved by isopropyl tri(dioctylpyrophosphate) titanate. Effects of matrix thermal conductivity on films thermal conductivity are probed. High voltage orientation molding are used for preparing epoxy composite films. The films demonstrate excellent thermal conductivity and favorable tensile strength.

Fabrication of diamond/AlSi10Mg composite using SLM: Effects of processing parameters and pre−/post-treatments

Diamond reinforced aluminum is a promising thermal management material for electronics applications because of an excellent combination of high thermal conductivity and low density. Since diamond reinforced aluminum is difficult to machine due to high hardness, it is attractive to manufacture diamond/aluminum composite parts with complex structures using additive manufacturing (AM) technology. However, the effect of the AM process on the thermal properties of diamond reinforced aluminum is unclear so far. In this study, selective laser melting (SLM) was used to prepare a diamond/AlSi10Mg composite with different diamond contents. The effects of pre-treatments of the diamond particles and post heat treatments of the SLMed samples were also investigated. It was found that the SLMed diamond/AlSi10Mg indeed possessed an enhanced thermal conductance than the pure AlSi10Mg. However, there were aspects that differentiated the SLMed diamond/AlSi10Mg from that fabricated by conventional processes. Increasing the diamond content from 15 wt% to 30 wt% did not further increase the thermal conductivity as it resulted in higher porosity of the SLMed samples. A pre-treatment of Ti coating on the diamond particles, a commonly used technique for conventional diamond/aluminum composite processing, was found to be unhelpful for the thermal property, as the diffusion of Ti into the aluminum matrix during SLM reduced the matrix thermal conductivity. On the other hand, the post heat treatments significantly increased the thermal conductivity of the SLMed samples by reducing the solute concentration.

A New Theoretical Method for Studying Effects of Microstructure on Effective Thermal Conductivity of Vermicular Graphite Cast Iron

To provide the basis for thermal conductivity regulation of vermicular graphite cast iron (VGI), a new theoretical method consisting of shape interpolation, unit cell model and numerical calculation was proposed. Considering the influence of the graphite anisotropy and interfacial contact thermal conductivity (ICTC), the effective thermal conductivity of a series of unit cell models was calculated by numerical calculation based on finite difference. The effects of microstructure on effective thermal conductivity of VGI were studied by shape interpolation. The experimental results were in good agreement with the calculated ones. The effective thermal conductivity of VGI increases in power function with the decrease in graphite shape parameter, and increases linearly with the increase in graphite volume fraction and thermal conductivity of matrix. When the graphite volume fraction increases by 1%, the thermal conductivity of nodular cast iron increases by about 0.18 W/(m·K), while that of gray cast iron increases by about 3 W/(m·K). The thermal conductivity of cast iron has the same sensitivity to the thermal conductivity of matrix regardless of the graphite shape parameter. The thermal conductivity of matrix increased by 15 W/(m·K) and the thermal conductivity of cast iron increased by about 12 W/(m·K). Moreover, the more the graphite shape deviates from the sphere, the greater the enhancement effect of graphite anisotropy on thermal conductivity than the hindrance effect of interface between graphite and matrix. This work can provide guidance for the development of high thermal conductivity VGI and the study of thermal conductivity of composites containing anisotropic dispersed phase particles with complex shapes.

Effect of short carbon fibers on the thermal conductivities of Csf/AZ91D composites

Developing metal matrix composites with lightweight and high thermal conductivities (TCs) to realize high-efficiency thermal management is of great significance. Herein, a strategy for preparing short carbon fiber preform without any chemical binder through the application of vacuum filtration is proposed. High in-plane and nearly unaltered out-plane thermal conductive magnesium matrix composites with short carbon fibers have been prepared by the independently developed liquid-solid extrusion following the vacuum infiltration (LSEVI) technique. The in-plane TCs of the composites reaches 72.16 W·(m·K)−1, a 50.3% enhancement compared to the matrix. The microstructures of the carbon fibers and magnesium matrix before and after the fabrication processing are characterized using optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Raman spectroscopy (RS). The composites display attractive thermal properties and this work provides an efficient approach to prepare short fiber-related thermal conductive metal matrix composites with a refined thermal management capacity.

Structural Modeling and Thermal Conductivity of Graphite Film Reinforced Aluminum Matrix Laminated Composites

Abstract: Excellent thermal conductivities of thermal management materials are expected to ensure the timely heat dissipation in lots of engineering applications and electronic devices. High in-plane thermal conductivity of laminated composites has become increasing significant for high energy and power density electronic devices. In this study, the continuous graphite film/aluminum (Gr film/Al) laminated composites were fabricated by vacuum hot pressing. In-plane and out-of-plane thermal conductivity of Gr film/Al laminated composites are tested. Two-dimensional structural models of Gr film/Al laminated composites are established, in which volume fraction, interfacial property, punching zone and orientation angle of Gr films can be controlled according to their actual composite microstructures. The effects of volume fraction and interfacial property on the thermal conductivity of Gr film/Al laminated composites are investigated. Two ways to reduce anisotropy of thermal conductivity are introduction of punching zones and control of Gr orientation, which are verified to be effective. On basis of the analysis above, a good understanding can be brought out for extensive thermal management applications of Gr/Al composites.

The impact of hydrothermal alteration on the physiochemical characteristics of reservoir rocks: the case of the Los Humeros geothermal field (Mexico)

Hydrothermal alteration is a common process in active geothermal systems and can significantly change the physiochemical properties of rocks. To improve reservoir assessment and modeling of high-temperature geothermal resources linked to active volcanic settings, a detailed understanding of the reservoir is needed. The Los Humeros Volcanic Complex, hosting the third largest exploited geothermal field in Mexico, represents a natural laboratory to investigate the impact of hydrothermal processes on the rock properties through andesitic reservoir cores and outcropping analogs. Complementary petrographic and chemical analyses were used to characterize the intensities and facies of hydrothermal alteration. The alteration varies from argillic and propylitic facies characterized by no significant changes of the REE budget indicating an inert behavior to silicic facies and skarn instead showing highly variable REE contents. Unaltered outcrop samples predominantly feature low matrix permeabilities (< 10–17 m2) as well as low to intermediate matrix porosities (< 5–15%), thermal conductivities (0.89–1.49 W m−1 K−1), thermal diffusivities (~ 0.83 10–6 m2 s−1), and sonic wave velocities (VP: ~ 2800–4100 m s−1, VS: ~ 1600–2400 m s−1). Average magnetic susceptibility and specific heat capacity range between 2.4–7.0 10–3 SI and 752–772 J kg−1 K−1, respectively. In contrast, the hydrothermally altered reservoir samples show enhanced porosities (~ 7–23%), permeabilities (10–17–10–14 m2), and thermal properties (> 1.67 W m−1 K−1; > 0.91 10–6 m2 s−1), but a significant loss of magnetic susceptibility (10–3–10–6 SI). In particular, this latter characteristic appears to be a suitable indicator during geophysical survey for the identification of hydrothermalized domains and possible pathways for fluids. The lack of clear trends between alteration facies, alteration intensity, and chemical indices in the studied samples is interpreted as the response to multiple and/or repeated hydrothermal events. Finally, the proposed integrated field-based approach shows the capability to unravel the complexity of geothermal reservoir rocks in active volcanic settings.

Heat transfer performance of the solid microencapsulated fuel in light water reactors

Solid Microencapsulated Fuel (SMF) is a kind of new accident-tolerant fuel (ATF) concept that disperses TRISO coated fuel particles directly into a type of matrix in the form of a solid rod. This paper aims to analyze the heat transfer performance of SMF based on a single pin, compared to the traditional fuel design in the 200 MW Nuclear Heating Reactor (NHR200-II). Two kinds of SMFs have been evaluated - fuel particles dispersed into a silicon carbide matrix and fuel particles dispersed into a zirconium matrix. The centerline temperature of the SMF rod at the beginning of life (BOL) was preliminarily calculated based on the effective thermal conductivity (ETC). The ETC was calculated by Maxwell, Chiew&Glandt, and d-EMT models, compared to the finite element models. The ETC of TRISO particle was also calculated before calculating that of the SMF rod because of its multilayer structure. To get a more realistic temperature distribution of SMF rod, a neutronic analysis was done by OpenMC by acquiring the power distribution of randomly distributed TRISO particles. Finally, a practical temperature distribution of SMF rod was achieved by the finite element model considering the random distribution of TRISO particles. This study showed that SMF has a better thermal transfer capacity than conventional fuel design and even fully ceramic microencapsulated (FCM) fuel because of its integral structure and higher matrix thermal conductivity. The helium gap in conventional fuel and FCM fuel would bring a temperature rise of nearly 150˚C in this case. The centerline temperature of SMF is much lower than the traditional fuel. A more refined temperature distribution of SMF rod based on the finite element model showed a lower maximum temperature than the ETC calculated. It also showed a less uniform temperature distribution because of the heat generation of fuel particles and the possible concentration of randomly distributed fuel particles.

Estimation of thermal conductivity of plutonic drill cuttings from their mineralogy: A case study for the FORGE Well 58–32, Milford, Utah

The thermal conductivity (TC) of rocks plays a significant role in geothermal-related research. The matrix TC (MTC) could be indirectly inferred from modal mineralogy as a parameter incorporated into mixing models instead of the time-consuming direct measurement of cuttings. This approach lacks robust references due to limited study. In this study, we analyzed 44 plutonic drill cuttings data covering from diorite to granite collected from the FORGE Well 58–32, Milford, Utah, including XRD, MTC, and porosity. We employed eight mixing models commonly used in thermal studies to estimate MTC based on mineral composition (determined by XRD). The MTC depends on the quartz content, and there is a positive linear correlation between them, with R2=0.988. For the mean TC of individual mineral phases, the estimation of MTC with outliers removed shows that the geometric mean model provides a better statistical fit to the measured MTC with a mean absolute relative error (MARE) and a root mean squared error (RMSE) of 6.0 ± 4.4% (2σ) and 0.21 W/(m•K), respectively. By selecting the best mixing model considering the cutting's rock types, the MARE, and RMSE between the estimated and measured MTCs are significantly minimized. Therefore, we suggest that in case of the volume of plutonic cuttings is inadequate to support direct measurement of TC, the MTC of plutonic cuttings could be estimated with an acceptable magnitude error by assessing their mineralogy and using the appropriate mixing model according to the rock types.

Determination of the effective thermal conductivity of particulate composites based on VO2 and SiO2

The effective thermal conductivity of composites made up of VO2 (SiO2) spherical particles randomly distributed and embedded in a SiO2 (VO2) matrix are numerically studied in a range of temperatures around the metal-insulator transition of VO2. This is done by means of three-dimensional finite element simulations for different concentrations and sizes of the particles as well as various interface thermal resistances. Our results are validated against the Mori-Tanaka analytical model. In addition, we develop a numerical method to calculate the heat storage capacity for composites with VO2 particles dispersed into a SiO2 matrix. It is shown that: i) The effective thermal conductivity of VO2/SiO2 composites increases with the VO2 particles' size, while the one of SiO2/VO2 composites is pretty much independent of the SiO2 particles' radius. ii) At the VO2 transition temperature (342.5 K), the effective thermal conductivity of VO2/SiO2 composites increases significantly at a rate of 2.7 × 10−3 Wm−1K−2, such that its value doubles up the SiO2 matrix thermal conductivity at the particle concentration of 40.2%. By contrast, the effective thermal conductivity of SiO2/VO2 composites decreases at a rate of 8.6 × 10−3 Wm−1K−2. iii) The effective thermal conductivity is strongly affected by the thermal resistance in VO2/SiO2 composites, by contrast the resistance effect does not play an important role for particle volume fractions of SiO2 up to 34.1% in SiO2/VO2 composites. The Mori-Tanaka model and our simulations predict the same trend of the effective thermal conductivity values of VO2/SiO2 composites. However, the analytical model fails when the matrix is made up of VO2 and the volumetric fraction of SiO2 exceeds 34.1%. The latent heat storage capacity of VO2/SiO2 composites increases with the VO2 particles’ concentration, such that at 40.2%, it takes the value of 24553 J kg−1 (486.7 cal mol−1), which is about half that of the pure VO2.