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104 results for “Thermal conductivity”

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zenodo40/100

IODP Expedition 374 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroAug 2019View details →
zenodo40/100

IODP Expedition 352 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroSep 2015View details →
zenodo40/100

IODP Expedition 351 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroAug 2015View details →
zenodo40/100

Effect of iron content on thermal conductivity of ferropericlase: implications for planetary mantle dynamics

<p>Dataset for the article &quot;Effect of iron content on thermal conductivity of ferropericlase: implications for planetary mantle dynamics&quot;.</p> <p>by Youyue Zhang, Takashi Yoshino, Masahiro Osako, submitted to Journal of Geophysical Research: Solid Earth.</p>

opencc-by-4.0May 2022View details →
zenodo40/100

Appendix A. Supplementary material for: Water-like thermal conductivity of ionanofluids containing high aspect ratio multi-walled carbon nanotubes and 1-ethyl-3-methylimidazolium-based ionic liquids with cyano-functionalized anions

<p><span>Experimental data in numerical form for INFs composed of CNTs and [Emim]-based ILs with cyano-functionalized anions: density (Table S1), viscosity (Tables S2&ndash;S5), thermal conductivity (Tables S6, S7), and ANOVA analysis (Table S8).</span></p>

opencc-by-4.0Jun 2024View details →
zenodo40/100

Thin film Tin Selenide (SnSe) Thermoelectric Generators Exhibiting Ultra-Low Thermal Conductivity

<p>Raw data from plots in &quot;Thin film Tin Selenide (SnSe) Thermoelectric Generators Exhibiting Ultra-Low Thermal Conductivity&quot;</p>

opencc-by-4.0Feb 2018View details →
zenodo40/100

Rock thermal conductivity and thermal inertia measurements under martian atmospheric pressures - Data

<p>Dataset accompanying the paper "Rock thermal conductivity and thermal inertia measurements under martian atmospheric pressures" published in Icarus in September 2024.&nbsp;</p> <p>Files included:&nbsp;</p> <p>Individual photos of the rocks in this study's sample suite; photos of laboratory equipment and setup; raw emissivity spectral data, emissivity specta plotted; thermal inertia data collected with the MTPS sensor; thermal conductivity data collected with the TPS sensor; itemized calculations of thermophysical data error; sample mineral abundance data; sample major/trace element measurement data; and detailed sample porosity data.&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2024View details →
zenodo40/100

IODP Expedition 350 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroMay 2015View details →
zenodo40/100

IODP Expedition 376 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroJul 2019View details →
zenodo40/100

IODP Expedition 385 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroSep 2021View details →
zenodo40/100

IODP Expedition 396 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroApr 2023View details →
zenodo40/100

IODP Expedition 354 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroSep 2016View details →
zenodo40/100

Data and code for "Tuning the lattice thermal conductivity in van-der-Waals structures through rotational (dis)ordering"

<p>This record contains neuroevolution potential (NEP) models for C, BN, and MoS<sub>2</sub> that have been constructed to model the potential energy surfaces of these materials in the presence of interlayer rotations. It also contains databases with the results from density functional theory calculations that were used for constructing the NEP models.</p> <p><strong>Databases</strong><br> The <code>*.db</code> files are databases with the results from density functional theory (DFT) calculations. These are sqlite databases in ase format, see <a href="https://wiki.fysik.dtu.dk/ase/tutorials/tut06_database/database.html">here</a> for more information. The <code>demo-database-access.py</code> script illustrates the most basic access.</p> <p><strong>Models</strong><br> The neuroevolution potential (NEP) models described in the publication can be found in the <code>nep-*.txt</code> files. They can be used in conjunction with the <a href="https://gpumd.org">GPUMD package</a>. The <a href="https://calorine.materialsmodeling.org">calorine package</a> provides a Python interface to GPUMD.</p> <p><strong>Primitive structures</strong><br> Several primitive structures in extended xyz format can be found in the <code>*.xyz</code> files. These structures have been relaxed using the NEP models included here. The <code>demo-for-using-structures-and-models.py</code> script illustrates how to access the structures and models.</p>

opencc-by-4.0Apr 2023View details →
zenodo40/100

IODP Expedition 369 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroMay 2019View details →
zenodo40/100

Measurements on reference materials for SThM measurand versus thermal conductivity calibration curve

<p>This sheet presents the results of measurements carried out on calibration samples using the SThM technique as part of the NanoWires project. The thermal conductivity of the samples was previously characterised using a traceable technique. Measurement results are given with associated standard uncertainty. The thermal conductivity range studied was between 0.187 and 117 W.m<sup>-1</sup>.K<sup>-1</sup>.&nbsp; These measurements were used to construct the thermal conductivity calibration curve for a&nbsp;SThM probe.</p> <p>The 19ENG05 NanoWires project has received funding from the EMPIR programme co-financed by the Participating States and from the European Union&rsquo;s Horizon 2020 research and innovation programme.</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

IODP Expedition 382 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroMay 2021View details →
zenodo40/100

IODP Expedition 392 Thermal conductivity

<p>Thermal conductivity was measured using the heated needle method in either full-space needle configuration (soft/saturated sediments) or half-space needle configuration (harder materials) of a TeKa Berlin TK-04 thermal conductivity meter. Heat is applied to the sample and then thermal equilibrium is sought. The heating and equilibration curve is reduced to derive the thermal conductivity value. Raw data are stored if a user wishes to do off-line or postexpedition reduction.</p>

opencc-zeroAug 2023View details →
zenodo36/100

How dopants limit the ultrahigh thermal conductivity of boron arsenide: a first principles study

<p>The dataset contains the necessary information&nbsp;to reproduce the phonon-defect scattering rates and the phonon thermal conductivity of cubic boron arsenide (BAs) upon doping, via the almaBTE software.</p> <p>Input files contain:</p> <p>1) Interatomic force constants for the pristine BAs, required to extract the phonon band structure and the intrinsic scattering processes;</p> <p>2) Unit cell POSCAR;</p> <p>3) Interatomic force constants for the C, Ge and Si impurities, required to compute the phonon-defect scattering rates beyond the mass-only approximation.</p> <p>Output files contain:</p> <p>1) Phonon-defect scattering rates (mass-only approximation, bond-only approximation, total) for charged and neutral impurities;</p> <p>2) Thermal conductivity at 300 K as function of the impurity concentration.</p> <p>&nbsp;</p>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Thermal conductivity analysis of polymer-derived nano-composite via image-base structure reconstruction, computational homogenization and machine learning

<p>This dataset includes supplementary data and utilities for validating simulation results and training machine learning models as outlined in the publication titled "Thermal Conductivity Analysis of Polymer-Derived Nanocomposite via Image-Based Structure Reconstruction, Computational Homogenization, and Machine Learning" (<a href="https://doi.org/10.1002/adem.202302021">Fathidoost, 2024</a>).</p> <p>This dataset containes the microstructure images (identified by particle diameters size \(D_1\) and \(D_2\) volume fraction \(V_\mathrm{f}\) and aspect ratio \(A_\mathrm{r}\)) (see Table 1) and their corresponding homogenized thermal conductivity. these images resemble the microstructure of the monolithic \(\mathrm{(Hf,Ta)C/SiC}\) ceramic following FAST sintering, the material system of this work (<a href="https://doi.org/10.1002/adem.202302021">Fathidoost, 2024</a>). White and black colors within the images represent distinct regions of the material system, &nbsp;respectively referring to former powder particles (FPPs) and sinter necks (SNs), which is explained in this work.</p> <p>Table 1. Parameterized descriptors extracted from the mesoscale SEM image analysis</p> <table> <tbody> <tr> <td>Param.</td> <td>Mean [unit]</td> <td>Std.</td> </tr> <tr> <td>\(D_{1}\)</td> <td>40, 50, 60 [&mu;m]</td> <td>20%</td> </tr> <tr> <td>\(D_{2}\)</td> <td>20, 25, 26, 30, 33, 40 [&mu;m]</td> <td>30%</td> </tr> <tr> <td>\(V_\mathrm{f}\)</td> <td>1.5, 2.0</td> <td>-</td> </tr> <tr> <td>\(A_\mathrm{r}\)</td> <td>35, 40, 45, 55, 60 [%]</td> <td>-</td> </tr> </tbody> </table> <p>This dataset contains:</p> <ul> <li><em>dataset.csv: </em>containing a summary of data including the names of microstructure images, their corresponding geometric details, as well as the first and third principal components of two-point statistics for all images, along with the effective thermal conductivity of the corresponding microstructures. Further details can be found in the associated publication.</li> <li><em>microstructures_images.zip</em>: containing binary cross-section images of the RVEs from synthetic microstructures。</li> <li><em>results.zip:</em> contains all the simulation results based on digitized diffuse-interface microstructures, which can be opened by the post-processing software, such as ParaView.</li> </ul>

opencc-by-4.0Nov 2023View details →
zenodo36/100

Exploring the thermal and ionic transport of Cu+ conducting argyrodite Cu7PSe6 (Computational data)

<p>This repository contains computational data for the manuscript titled &ldquo;Exploring the thermal and ionic transport of Cu+ conducting argyrodite Cu7PSe6&rdquo;. It consists of outputs and analysis scripts for bonding analysis through LOBSTER, harmonic phonon, and Gr&uuml;neisen parameters calculations using VASP and phonopy.&nbsp;</p>

opencc-by-4.0Apr 2024View details →

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