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50 results for “Graphitization”
Data accompanying: Impacts into a porous graphite: an investigation on crater formation and ejecta distribution
<p>Reconstructed X-ray tomographies and python analysis scripts for the publication "Impacts into a porous graphite: an investigation on crater formation and ejecta distribution"</p> <p> </p> <p>Uses the spam python toolkit, which can probably be replaced by scipy.ndimage.center_of_mass if needed.</p>
Dataset of electronic Raman scattering in rhombohedral graphite
<p>The dataset contains the raw data, used to generate the figures of our paper (Carbon 2024 and arxiv: 2401.17779).</p> <p>Each folder contains the raw data in text files as well as the python Jupyter notebooks used to analyse the data and generate the figures.</p> <p>To work with the data, open the Jupyter notebooks (*.ipynb files). The notebooks can be previewed by opening the html exported format of each notebook.</p>
Dataset on the Laser-induced graphitization of polydopamine on titania nanotubes
<p>The following dataset contains various research data that is the basis for the research article: <br>"Laser-induced graphitization of polydopamine on titania nanotubes".</p><p>This dataset contains the following folders corresponding to the techniques and procedures used in the paper:<br>- DFT (.hdf5 libraries containing quantum chemistry results described in the paper including atomic coordinates and density of states data)<br>- Electropolymerization (.txt files containing cyclic voltammetry curves of electropolymerization)<br>- IMPS_IMVS (a library of folders containing .raw and .dat files used in IMPS = Intensity Modulated Photocurrent Spectroscopy and IMVS = Intensity Modulated Photovoltage Spectroscopy measurements)<br>- Nanoindentation (.xlsx files containing nanoindentation data)<br>- Photocurrent_maps (.dat files used to build photocurrent maps)<br>- Photoelectrochemical_sensing (.dat files of photoelectrochemical sensing experiments)<br>- Photoelectrochemistry (.opju libraries containing massive amounts of electrochemical and photoelectrochemical results described in the paper including EIS = Electrochemical Impedance Spectroscopy, CV = Cyclic Voltammetry, CA = Chronoamperometry, Raman spectroscopy) <br>- ReaxFF (.hdf5 libraries containing reactive molecular dynamics results)<br>- SEM (.tiff SEM images)<br>- Supplementary_fsTNT_PDA (a library of folders containing various supplementary data on loosely-spaced nanotubes including Raman, SEM, electrochemistry, and photoelectrochemistry data)<br>- UV-vis (.csv files from diffuse reflectance spectroscopy measurements)<br>- XPS (.xlsx files from X-Ray Photoelectron spectroscopy measurements)<br> </p>
Presolar Grain Database - Graphite
<p>The Presolar Grain Database (PGD) contains the vast majority of isotope data (published and unpublished) on presolar grains and was first released as a collection of spreadsheets in 2009. It has been a helpful tool used by many researchers in cosmochemistry and astrophysics. However, over the years, accumulated errors compromised major parts of the PGD. Here, we provide a fresh start, with the PGD for graphite grains rebuilt from the ground up.</p> <p>The PGD is provided here in two formats: (1) as Microsoft Excel (.xlsx) file, containing the main database as one large spreadsheet and additional information on extra spreadsheets, (2) as comma-separated ASCII (.csv) file containing the main database.</p> <p>The PGD is also available for silicon carbide (SiC) grains at the DOI <a title="10.5281/zenodo.8187219" href="../doi/10.5281/zenodo.8187219">https://zenodo.org/doi/10.5281/zenodo.8187219</a>.</p>
Flexible Graphite−Poly(Lactic Acid) Composite Films as Large-Area Conductive Electrodes for Energy Applications
<p>Raw data of energy storage part -author Kalyan Ghosh </p>
Less than one weight percent of graphite on the surface of Mercury
<p>These are BD600 Global map, LRM global distribution map, python codes for radiative transfer modeling, and source codes and data for Figures.</p>
Finite element mesh of fusion energy heat exchange component: hybrid CAD/IBSim model including a graphite foam interlayer
<p>Image-Based Simulation (IBSim) mesh:<br> A finite element mesh of a conceptual design for a fusion energy heat exchange component (monoblock). The mesh is a hybrid from a computer aided design (CAD) drawing for the pipe and armour and IBSim for the interlayer. The IBSim interlayer is generated directly from a 3D volumetric image of a graphite foam block (KFoam). The 3D image was generated with an X-ray tomography scan performed by Dr Llion Evans with Manchester X-ray Imaging Facility equipment, which was funded in part by the EPSRC (grants EP/F007906/1, EP/F001452/1 and EP/I02249X/1). Conversion of the data to FE mesh was achieved using ScanIP, part of the Simpleware suite of programmes, version 7 (Synopsys Inc., Mountain View, CA, USA).</p> <p>The FE mesh data uses the EnSight Gold file format and may be visualised using Paraview (<a href="https://www.paraview.org">https://www.<strong>paraview</strong>.org</a>).</p> <p>The CT data used for the mesh is available as a separate dataset:</p> <p>This data was used originally for the following publications (please cite if re-using the data):<br> Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Improving modelling of complex geometries in novel materials using 3D imaging”, Proceedings of NEA International Workshop on Structural Materials for Innovative Nuclear Systems, Manchester, UK, July 2016. <a href="https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf">https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf</a></p>
X-ray tomography image data of a graphite foam block (KFoam) and tortuosity analysis
<p>X-ray tomography (CT) image data of a graphite foam block (KFoam). The 3D image was generated with an X-ray tomography scan performed by Dr Llion Evans with Manchester X-ray Imaging Facility equipment, which was funded in part by the EPSRC (grants EP/F007906/1, EP/F001452/1 and EP/I02249X/1).</p> <p>The dataset includes: raw radiographs; scan & reconstruction parameter settings file; reconstructed 3D volume. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). The volume image data (NMT_15_229_LLME_DivInterlayer.raw) is in binary format and has the following characteristics: 1586 x 1567 x 1588; 8-bit; little-endian byte order.</p> <p>The second .zip file is a 200 x 200 x 200 subset of this dataset. This was used to perform a tortuosity analysis on the foam. This dataset includes three sets of tiff images; tomographic slices; binarised slices; skeletonised slices. It also includes an excel file with the results of the tortuosity analysis performed with ImageJ.</p> <p>This data was used originally for the following publications (please cite if re-using the data):</p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Improving modelling of complex geometries in novel materials using 3D imaging”, Proceedings of NEA International Workshop on Structural Materials for Innovative Nuclear Systems, Manchester, UK, July 2016. <a href="https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf">https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf</a></p>
Data from: "Lithium-ion battery degradation: measuring rapid loss of active silicon in silicon-graphite composite electrodes"
<p>Dataset from the publication "Lithium-ion battery degradation: measuring rapid loss of active silicon in silicon-graphite composite electrodes". Full experimental details can be found in the related publication in ACS Applied Energy Materials: <a href="https://doi.org/10.1021/acsaem.2c02047">https://doi.org/10.1021/acsaem.2c02047</a></p> <p>Commercial 21700 cylindrical cells (LG M50T, LG GBM50T2170) were cycle aged under 3 different temperatures [10, 25, 40] °C and 2 SoC ranges [0-30, 0-100]%, with multiple cells tested under each condition. Cells were base-cooled at set temperatures using bespoke test rigs (see pubilcation for details). All electrochemical data were recorded using a Biologic BCS-815 battery cycler.</p> <p> </p> <p><strong>Break-in cycles:</strong></p> <p>Prior to any ageing or performance checks, all cells were subject to 5 full charge-discharge cycles as part of the break-in procedure. This consisted of a 0.2C charge to 4.2 V with CV-hold till C/100, and 0.2C discharge to 2.5 V (repeated for 5 cycles). Cells were rested under open circuit conditions for 2 hours after each charge and 4 hours after each discharge. These break-in cycles were performed at 25°C for all cells.</p> <p> </p> <p><strong>Ageing Conditions:</strong></p> <table align="center"> <caption>Ageing Conditions</caption> <thead> <tr> <th scope="col">Expt</th> <th scope="col">SoC Range</th> <th scope="col">C-rate</th> <th scope="col">Temperature</th> <th scope="col"># of cells</th> <th scope="col">Cell IDs</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>0-30%</td> <td>0.3C / 1D</td> <td>10°C</td> <td>3</td> <td>A, B, J</td> </tr> <tr> <td>1</td> <td>0-30%</td> <td>0.3C / 1D</td> <td>25°C</td> <td>3</td> <td>D, E, F</td> </tr> <tr> <td>1</td> <td>0-30%</td> <td>0.3C / 1D</td> <td>40°C</td> <td>3</td> <td>K, L, M</td> </tr> <tr> <td>5</td> <td>0-100%</td> <td>0.3C / 1D</td> <td>10°C</td> <td>3</td> <td>A, B, C</td> </tr> <tr> <td>5</td> <td>0-100%</td> <td>0.3C / 1D</td> <td>25°C</td> <td>2</td> <td>D, E</td> </tr> <tr> <td>5</td> <td>0-100%</td> <td>0.3C / 1D</td> <td>40°C</td> <td>3</td> <td>F, G, H</td> </tr> </tbody> </table> <p>For cells aged in the 0-30% SoC range, each ageing set consisted of 256 cycles over the 0-30% SoC range (discharge to 2.5 V, charge by passing 1500 mA h (== 0.3*nominal capacity)). C-rates were 0.3C for charge, and 1C for discharge.</p> <p>For cells aged in the 0-100% SoC range, each ageing set consisted of 78 cycles over the full SoC range (discharge to 2.5 V, charge to 4.2 V with CV hold till C/100). C-rates were 0.3C for charge, and 1C for discharge.</p> <p> </p> <p><strong>Reference Performance Tests (RPTs):</strong></p> <p>All cells were characterised at beginning of life (BoL) and after each ageing set using a reference performance test (RPT). The RPT was always performed at 25°C. Two different RPT procedures were used: a longer procedure which was performed after each even-numbered ageing set, and a shorter procedure which was used after each odd-numbered ageing set. Both procedures are detailed below. A CC-CV charge at 0.3C to 4.2 V, 4.2 V till C/100 was performed between each step of the procedures.</p> <p>Long RPT procedure:</p> <ol> <li>C/10 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).</li> <li>C/2 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).</li> <li>GITT discharge at 0.5C; 25 pulses with each pulse passing 200 mA h of charge, with 1 hour rest between pulses; lower cut-off voltage of 2.5 V (but continued test for all pulses).</li> <li>GITT discharge at 0.5C; 5 pulses with each pulse passing 1000 mA h of charge, with 1 hour rest between pulses; lower cut-off voltage of 2.5 V (but continued test for all pulses).</li> </ol> <p>Short RPT procedure:</p> <ol> <li>C/10 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).</li> <li>Hybrid CC-pulse test with average current of C/2. A baseline DC current of C/2 was applied with an HPPC-type profile superimposed on top. This was done for discharge and charge (with voltage limits of 2.5 V and 4.2 V).</li> <li>Hybrid CC-pulse test with average current of 1C. A baseline DC current of 1C was applied with an HPPC-type profile superimposed on top. This was done for discharge only (with a voltage limit of 2.5 V).</li> </ol> <p> </p> <p><strong>Extracted Data - Main </strong></p> <p>One csv file exists for each cell being tested, summarising the important data extracted from the ageing cycles and the RPTs. This includes:</p> <p>Ageing Set: numbered 0 (BoL) to x, where x is the number of ageing sets the cell has been subject to.</p> <p>Ageing Cycles: number of ageing cycles the cell has been subject to. *this is <strong>not </strong>equivalent full cycles.</p> <p>Ageing Set Start Date/ End date: The date that each ageing set began/ ended.</p> <p>Days of Degradation: Number of days between the date of the first ageing set beginning and the current ageing set ending.</p> <p>Age Set Average Temperature: average recorded surface temperature of the cell during cycle ageing. Temperature was recorded approximately 1/2 way up the length of the cell (i.e. between positive and negative caps) using a K-type thermocouple. Units: °C.</p> <p>Charge Throughput: total accumulated charge recorded during all cycles during ageing (i.e. sum of charge and discharge). This is the cummulative total since BoL (not including RPTs). Units: Ah.</p> <p>Energy Throughput: as with "charge throughput", but for energy. Units: Wh.</p> <p>C/10 Capacity: the capacity recorded during the C/10 discharge test of each RPT. Units: mAh.</p> <p>C/2 Capacity: the capacity recorded during the C/2 discharge test of each even-numbered RPT. Units: mAh.</p> <p>0.1s Resistance: The resistance calculated from the 25-pulse GITT test of each even-numbered RPT. This value is taken from the 12th pulse of the procedure (which corresponds to ~52% SoC at BoL). The resistance is calculated by dividing the voltage drop by the current at a timecale of 0.1 seconds after the current pulse is applied (the fastest timescale possible under the 10 Hz recording condition). Units: Ohms.</p> <p> </p> <p><strong>Extracted Data - Degradation Modes:</strong></p> <p>Degradation Mode Analysis (DMA) was also performed on the C/10 discharge data at each RPT. This analysis uses an optimisation function to determine the capacities and offset of the positive and negative electrodes by calculating a full cell voltage vs capacity curve using 1/2 cell data and comparing against the experimentally measured voltage vs capacity data from the C/10 discharge.</p> <p>The results of this analysis are saved in the DMA folder, with 4 csv files for each cell, which contain data for all RPTs. The 4 files contain:</p> <p>Fitting parameters: output from the DMA optimisation function; 5 parameters which detail the upper/lower lithitation fractions of each electrode and the capacity fraction of graphite in the negative electrode.</p> <p>Capacity and offset data: calculated based on the fitting parameters above alongside the measured C/10 discharge capacity.</p> <p>DM data: Quantities of LLI, LAM-PE, LAM-NE, LAM-NE-Gr, and LAM-NE-Si calculated from the change in capacities/offset of each electrode since BoL.</p> <p>RMSE data: the root-mean-square error of the optimisation function calculated from the residual between the measured and calculated voltage vs capacity profiles.</p> <p> </p> <p><strong>Timeseries data from RPTs:</strong></p> <p>Timeseries datafiles from the Biologic battery cycler which have been exported to csv and sliced for each step of each RPT procedure to help with future use of the data. Files contain [time, voltage, current, charge, temperature] data.</p> <p> </p> <p><strong>Jupyter Notebook:</strong></p> <p>A jupyter notebook has been included to aid futher use of this data. The notebook shows how to load the data into pandas DataFrame objects and provides a couple of example plots to view the datasets.</p> <p> </p> <p><strong>Notes:</strong></p> <p>A faulty electrical connection to cell A of Expt 5 (i.e. one of the cells being aged at 0-100% SoC at 10°C) during RPT4 led to erroneous results for that performance check (as evidenced in the 0.1s resistance value). The faulty electrical connection was fixed prior to subsequent cycling but the RPT was not repeated. We have kept the data collected during this RPT as part of the dataset, so caution should be used when using this specific portion.</p>
Surface Coordination Chemistry of Graphitic Carbon Nitride from Ag Molecular Probes
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Thermal diffusivity of isotropic graphite from 23 °C to 3000 °C
<p>This dataset contains thermal diffusivity values determined from 23 °C to 3000 °C by seven laboratories on a batch of specimens machined in the same block of isotropic graphite. </p>
Spectral emissivity of isotropic graphite from 1290 K to 2300 K
<p>This dataset contains spectral emissivity values determined from 1290 K to 2300 K by two laboratories on a batch of specimens machined in the same block of isotropic graphite.</p>
Specific heat of isotropic graphite from 1000 °C to 2800 °C
<p>This dataset contains specific heat values determined from 1000 °C to 2800 °C by three laboratories on a batch of specimens machined in the same block of isotropic graphite.</p>
Analysis table of optimal preparation conditions of expanded graphite
<p><span>The environmentally friendly preparation of sulfur-free expanded graphite (EG) remains a great challenge. A large amount of strong acids and strong oxidants were used in the preparation of expandable graphite, resulting in environmental pollution problems. Herein, a novel and green preparation method for sulfur-free expanded graphite (EG) has been developed. Sulfur-free EG was fabricated using natural flake graphite (NFG), sodium perchlorate (NaClO<sub>4</sub>), and oxalic acid (C<sub>2</sub>H<sub>2</sub>O<sub>4</sub>) as raw materials. The electrochemical oxidation method was applied to prepare sulfur-free expandable graphite, and microwave irradiation technology was adopted to prepare sulfur-free EG. The optimum weight ratio was as follows: NFG:NaClO<sub>4</sub>:C<sub>2</sub>H<sub>2</sub>O<sub>4</sub> = 1.5:10:2. The anodic oxidation occurred under a constant current density of 47 mA/cm<sup>2</sup>, and the intercalation reaction lasted for 60 min at ambient temperature. The largest expanded volume (EV) of sulfur-free EG was 290 mL/g. The FTIR spectrum proved that the ClO4<sup>−</sup> and COO<sup>−</sup> groups had entered the graphite layers. The SEM images showed that the graphite layers were completely opened, and the pore structure was clearly observed. The sulfur-free EG prepared by the method does not cause environmental pollution and has broad application prospects.</span></p>
Laboratory graphite flask
late 18th century, Germany Jagiellonian University Museum Collegium Maius Inventory number: 5088; 1283/V https://muzea.malopolska.pl/en/objects-list/2806 Source: Objaverse 1.0 / Sketchfab
Boron elemental and isotopic determination via the BF diatomic molecule using high-resolution continuum source graphite furnace molecular absorption spectrometry
<p>This dataset contains the raw data corresponding to the figures of the publication DOI: 10.1039/d3ja00420a</p>
Dataset from the paper entitled "Linking Lattice Strain and Fractal Dimensions to Non-Monotonic Volume Changes in Irradiated Nuclear Graphite"
<p>Dataset from the paper entitled "Linking Lattice Strain and Fractal Dimensions to Non-Monotonic Volume Changes in Irradiated Nuclear Graphite". The dataset includes the small angle X-ray scattering measurements, the wide-angle X-ray scattering measurements, and the fitting parameters. Please see the included Readme file for more detail on the organization. </p>
Dataset for Structure compatibility of graphite and phases formed from aluminum or magnesium phyllosilicates
<p>Dataset for contribution "Structure compatibility of graphite and phases formed from aluminum or magnesium phyllosilicates" from international conference NANOCON 2024.</p>
Data for "Graphite and multi-layer graphene from a low molecular weight carbon source"
<p>Collection of original data for article "Graphite and multi-layer graphene from a low molecular weight carbon source"</p>
Analysis table of optimal preparation conditions of expanded graphite
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