Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
163
datasets available to search
ShareScore release 0.9.0
Dataset results
163 results for “fillers”
Damage Monitoring of Structural Resins Loaded with Carbon Fillers: Experimental and Theoretical Study
<p>Dynamic Mechanical Analysis, Electro-Mechanical Measurement, Simulation model, Dynamic Light Scattering, FTIR spectroscopy</p> <p>Thermogravimetric analysis, Differential Scanning Calorimetry, Electro-Temperature Measurement, </p> <p>Thermal Image Camera , Water sorption measurement, Transmission Electron Microscopy, Stress Strain</p>
Supplementary Information and EBSD data for 'Intermetallic phase layers in cold metal transfer aluminium-steel welds with an Al-Si-Mn filler alloy'
<p>Supplementary information and electron backscatter diffraction (EBSD) data for the article entitled 'Intermetallic phase layers in cold metal transfer aluminium-steel joints with an Al-Si-Mn filler alloy'. There are three EBSD datasets, I-III, named "I_EBSD.dat" - "III_EBSD.dat", each with corresponding calibration and background patterns, as well as secondary electron scanning electron microscopy images showing the scanned area and text files containing the acquisition parameters. The data analysis workflow has been published on GitHub, see References.</p>
Data and Analyses for Defining Filler Particles: A Phonetic Account of the Terminology, Form, and Grammatical Classification of Filled Pauses.
<p>Aggregated data and analyses for the article Belz, Malte (2023): Defining Filler Particles: A Phonetic Account of the Terminology,<br> Form, and Grammatical Classification of "Filled Pauses". Languages. <a href="https://www.mdpi.com/journal/languages/special_issues/Pauses_in_Speech">https://www.mdpi.com/journal/languages/special_issues/Pauses_in_Speech</a></p>
Investigation of Azo-COP-2 as a photo-responsive low-energy CO2 adsorbent and porous filler in mixed matrix membranes for CO2/N2 separation
<p>Dataset supporting publication. All raw data for figures is included in the Excel file, and the full high-resolution SEM images are included in this repository.</p> <p>A preprint of the manuscript is available from <a href="https://doi.org/10.26434/chemrxiv.7593902">https://doi.org/10.26434/chemrxiv.7593902</a> </p> <p>The published paper is: Siyao Li, Nicholaus Prasetya, and Bradley P Ladewig, <em>Ind. Eng. Chem. Res.</em>, Just Accepted Manuscript<br> DOI: <a href="https://doi.org/10.1021/acs.iecr.9b00762">https://doi.org/10.1021/acs.iecr.9b00762</a></p>
The utilization of micro-mesoporous carbon-based filler in the P84 hollow fiber membrane for gas separation
<p>This research carried out a unique micro-mesoporous carbon particle incorporation into P84 co-polyimide membrane for improved gas separation performance. The carbon filler was prepared using a hard template method from zeolite and called as zeolite templated carbon (ZTC). This research aims to study the loading amount of ZTC into P84 co-polyimide toward the gas separation performance. The ZTC was prepared using simple impregnation method of sucrose into hard template of zeolite Y. The SEM result showing a dispersed ZTC particle on the membrane surface and cross-section. The pore size distribution of ZTC revealed that the particle consists of two characteristics of micro and mesoporous region. It was noted that with only 0.5 wt% of ZTC addition, the permeability was boosted up from 4.68 to 7.06 and from 8.95 to 13.15 Barrer, for CO2 and H2 respectively as compared to the neat membrane. On the other hand, the optimum loading was at 1 wt%, where the membrane received thermal stability boost of 10% along with the 62.4 and 35% of selectivity boost of CO2/CH4 and H2/CH4, respectively. It was noticed that the position of the filler on the membrane surface was significantly affecting the gas transport mechanism of the membrane. Overall, te results demonstrated that the addition of ZTC with proper filler position has potential candidate to be applicable in the gas separation involving CO2 and H2.</p>
Châtelaudren Filler Shop 1 [France]
Custom low-poly asset made with Blender and Gimp for the Cities: Skylines video game. Available on the Steam Workshop here: https://steamcommunity.com/sharedfiles/filedetails/?id=1628025264 Source: Objaverse 1.0 / Sketchfab
Functional miscibility and thermomechanical properties enhancement of substituted phthalic acetylated modified chitin filler in biopolymer composite
<p>The miscibility between hydrophobic and hydrophilic biopolymers has been of significant challenge. This study used a novel simplified chitin modification method to produce phthalic - chitin using phthalic anhydride in a substitution reaction. The FT-IR functional group analysis was used to confirm the substitution reaction. The modified chitin was used as compatibiliser in PLA/starch biocomposite to enhance its properties. The biocomposite was prepared using melt extrusion and compression moulding technique. The biocomposite's morphological, thermomechanical, and water absorption properties were characterised using scanning electron microscope, tensile test, dynamic mechanical analysis, thermogravimetry analysis, differential scanning calorimetry, thickness swelling, and water absorption test. The FT-IR study shows a successful substitution reaction of the amine hydrogen ion present in the chitin as opposed to substituting the hydrogen ion in the hydroxide group. The tensile and impact properties of biocomposite incorporated with modified chitin showed better results compared with other samples. The SEM images showed uniform miscibility of the modified biocomposite. The dynamic mechanical analysis showed improved modulus value with the incorporation of modified chitin. The thermal properties showed improved thermal stability of the modified biocomposite. Furthermore, the percentage of water absorbed by biocomposite with modified chitin is reduced compared to the PLA/starch biocomposite. The produced biodegradable ternary blend can be used as a substitute for plastics in industrial applications.</p>
Evaluating the impact of filler size and filler content on the stiffness, strength, and toughness of polymer nanocomposites using coarse-grained molecular dynamics: dataset
<div><strong>Abstract:</strong></div> <div>(from [1])</div> <div>Their great versatility makes polymer nanocomposites an important class of engineering materials. In order to gain detailed insights into the nanoscale mechanisms underlying their macroscopic mechanical properties, molecular dynamics (MD) simulations are a valuable tool to complement experimental studies. In this work, we modify the analytical potential functions of an efficient bead-spring model representing a generic polymer nanocomposite to account for the breaking of covalent bonds. We perform uniaxial tensile simulations of double-notched specimens and validate the model using experimental trends for overall stiffness, strength, and toughness. First, we study the effects of sample size, notch geometry, strain rate, temperature, and molar mass for the pure thermoplastic matrix material. Second, we analyze the influence of filler size and filler content on the mechanical behavior of the polymer nanocomposite. With this study, we show that in both the development of new materials and the optimization of established materials, it is possible to gain important preliminary insights into the effects of pertinent material characteristics with a simple MD setup, which can then be further refined by increasing the complexity of the material description and the boundary conditions. </div> <div> </div> <div> </div> <div><strong>Contact:</strong></div> <div>Felix Weber</div> <div>Institute of Applied Mechanics</div> <div>Friedrich-Alexander-Universität Erlangen-Nürnberg</div> <div>Egerlandstr. 5</div> <div>91058 Erlangen</div> <div>Germany</div> <div> </div> <div> </div> <div><strong>Software:</strong></div> <div>All simulations were performed with LAMMPS [2,3] (version 23 June 2022, patch_23Jun2022_update3) </div> <div> </div> <div>Compiler: GNU C++ 11.2.0 with OpenMP not enabled</div> <div>C++ standard: C++11</div> <div> </div> <div>Active compile time flags:</div> <div>-DLAMMPS_GZIP</div> <div>-DLAMMPS_SMALLBIG</div> <div> </div> <div>Installed packages:</div> <div>BPM CLASS2 DPD-BASIC EXTRA-DUMP EXTRA-FIX EXTRA-MOLECULE INTEL KSPACE MANYBODY </div> <div>MC MISC MOLECULE MOLFILE MPIIO NETCDF OPT </div> <div> </div> <div>Moreover, we employ a self-avoiding random walker [4,5] implemented in MATLAB [6] for the initial positioning of the polymer chains and nanoparticles.</div> <div> </div> <div> </div> <div><strong>License:</strong></div> <div>Creative Commons Attribution 4.0 International</div> <div> </div> <div> </div> <div><strong>Context:</strong></div> <div>This dataset contains the results presented in [1] and the necessary data to obtain those.</div> <div> </div> <div> </div> <div><strong>Content:</strong></div> <div>Throughout this data set, LAMMPS lj units are used. The files to reproduce our simulations and their results are structured as follows:</div> <div>- 01_neat: Neat polymer systems</div> <div> - 01_EQU: Equilibration simulations</div> <div> - 02_UT: Uniaxial tensile simulations, including the notch insertion (token "initcrack")</div> <div> - 1.1: Simulations for different sample sizes/numbers of chains (token "chains") at constant molar mass/number of beads per chain</div> <div> - 1.3: Simulations for different widths of the Dirichlet boundary (token "diri")</div> <div> - 2.1: Simulations for different critical bond lengths (token "bondcrit")</div> <div> - 2.2: Simulations for different bond breaking probabilities (token "bondcprob")</div> <div> - 3.1: Simulations for different crack widths (token "crackwidth")</div> <div> - 3.2: Simulations for different crack lengths (token "crackdepth")</div> <div> - 4: Simulations for different strain rates (token "strainrate")</div> <div> - 5: Simulations for different temperatures (token "tem")</div> <div> - 6: Simulations for different molar masses/numbers of beads per chain (token "chain-len")</div> <div>- 02_PNC: Polymer nanocomposite (PNC) systems </div> <div> - 01_EQU: Equilibration simulations</div> <div> - 02_UT: Uniaxial tensile simulations for different filler radii (token "rF") and filler contents/numbers (token "nF"), including the notch insertion (token "initcrack")</div> <div>- parameter_study: Postprocessing of the MD results </div> <div> - parameter_study.xlsx: Overview of the simulations with their respective parameters and statistical analysis of stiffness, strength, and toughness from filtered stress-strain curves (Savitzky-Golay filter applying a linear polynomial and frame length 21)</div> <div> - .csv files of the single sheets of parameter_study.xlsx:</div> <div> - samples.csv: Individual specimens</div> <div> - averages.csv: Statistical analysis of the different samples corresponding to one batch</div> <div> </div> <div>Each simulation directory contains:</div> <div>- LAMMPS input script (*.in) of the simulation</div> <div>- input.prm: Input parameters of the simulation (read by the input script)</div> <div>- LAMMPS data file (*.data, molecular style) of the investigated sample</div> <div>- LAMMPS_out: Resulting LAMMPS data files, log files and simulation results in tabulated form</div> <div> - additional files for the tensile tests: </div> <div> - brokenbonds.dat: Fix print output for fix brokenbondsprint (step time brokenbondsPerStep brokenbondsSum)</div> <div> - stressstrain.dat: Time-averaged data for fix dumpOpt (step v_strain_xx v_OBSstrain_xx v_Piola_xx) with the local strain at the crack tip v_OBSstrain_xx</div> <div> - thermo_out.Dat: Thermodynamic output in condensed tabulated form</div> <div> - thermo_out_SG.Dat: Thermodynamic output in condensed tabulated form, filtered by a Savitzky-Golay filter (linear polynomial, frame length 21)</div> <div> - thermo_out_STD.Dat: Standard deviation between the filtered and unfiltered data</div> <div>- job.out: Simulation log file</div> <div>- meta.info: Meta data of the simulation run</div> <div> </div> <div>Naming convention:</div> <div>- 01_neat: GTPm-[number of chains]_chains-[number of beads per chain]_chain_len-[temperature]_tem-[parameter value]_[parameter]-[sample]</div> <div> - [parameter]: Parameter studied, i.e. diri/bondcrit/bondcprob/crackwidth/crackdepth/strainrate/tem (see above)</div> <div> - [parameter value]: Value of the parameter studied</div> <div> - [sample]: Sample ID</div> <div>- 02_PNC: GTPm_rF-[filler radius]_nF-[number of fillers]_[sample]</div> <div> - [sample]: Sample ID</div> <div> </div> <div>Output quantities (columns of *.Dat files):</div> <div>- Step: time step</div> <div>- Time: time</div> <div>- TotEng: total energy</div> <div>- PotEng: potential energy</div> <div>- KinEng: kinetic energy</div> <div>- E_pair: pair energy</div> <div>- E_bond: bond energy</div> <div>- E_angle: angle energy</div> <div>- E_dihed: dihedral energy</div> <div>- Temp: temperature</div> <div>- Press: hydrostatic pressure</div> <div>- Pxx: xx component of pressure tensor</div> <div>- Pyy: yy component of pressure tensor</div> <div>- Pzz: zz component of pressure tensor</div> <div>- Pxy: xy component of pressure tensor</div> <div>- Pxz: xz component of pressure tensor</div> <div>- Pyz: yz component of pressure tensor</div> <div>- Volume: volume of simulation box</div> <div>- Lx: box length in x direction</div> <div>- Ly: box length in y direction</div> <div>- Lz: box length in z direction</div> <div>- Density: mass density</div> <div>- c_RG: radius of gyration</div> <div>- c_RG[1]: squared radius of gyration tensor (xx component)</div> <div>- c_RG[2]: squared radius of gyration tensor (yy component)</div> <div>- c_RG[3]: squared radius of gyration tensor (zz component)</div> <div>- c_RG[4]: squared radius of gyration tensor (xy component)</div> <div>- c_RG[5]: squared radius of gyration tensor (xz component)</div> <div>- c_RG[6]: squared radius of gyration tensor (yz component)</div> <div>- c_bondave[1]: bond energy averaged over all atoms</div> <div>- c_bondave[2]: bond distance averaged over all atoms</div> <div>- c_bondave[3]: squared bond distance averaged over all atoms</div> <div>- c_angleave[1]: angle energy averaged over all atoms</div> <div>- c_angleave[2]: angle averaged over all atoms degree</div> <div>- c_angleave[3]: cosine of angle</div> <div>- c_angleave[4]: squared cosine of angle</div> <div>- c_MSD[1]: mean squared displacement x-direction</div> <div>- c_MSD[2]: mean squared displacement y-direction</div> <div>- c_MSD[3]: mean squared displacement z-direction</div> <div>- c_MSD[4]: total mean squared displacement</div> <div>- c_COM[1]: x coordinate of center of mass</div> <div>- c_COM[2]: y coordinate of center of mass</div> <div>- c_COM[3]: z coordinate of center of mass</div> <div>- v_strain_xx: xx component of engineering strain tensor </div> <div>- v_strain_yy: yy component of engineering strain tensor </div> <div>- v_strain_zz: zz component of engineering strain tensor </div> <div>- v_vMisesequivstress: von Mises equivalent stress</div> <div>- v_Piola_xx: xx component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_yy: yy component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_zz: zz component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_xy: xy component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_xz: xz component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_yz: yz component of the virial stress tensor normalized by the initial volume</div> <div>- v_strain_xy: xy component of engineering strain tensor </div> <div>- v_strain_xz: xz component of engineering strain tensor </div> <div>- v_strain_yz: yz component of engineering strain tensor </div> <div> </div> <div> </div> <div><strong>References:</strong></div> <div>[1] F. Weber, V. Dötschel, P. Steinmann, S. Pfaller, M. Ries, "Evaluating the impact of filler size and filler content on the stiffness, strength, and toughness of polymer nanocomposites using coarse-grained molecular dynamics", Engineering Fracture Mechanics, vol. 307, p. 110270, 2024.</div> <div>[2] S. Plimpton, "Fast parallel algorithms for short-range molecular dynamics", Journal of computational physics, vol. 117, no. 1, pp. 1-19, 1995.</div> <div>[3] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, S. J. Plimpton, "LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales", Computer Physics Communications, vol. 271, p. 108171, 2022.</div> <div>[4] V. Dötschel, S. Pfaller, and M. Ries, "Studying the mechanical behavior of a generic thermoplastic by means of a fast coarse-grained molecular dynamics model", Polymers and Polymer Composites, vol. 31, pp. 1–11, 2023.</div> <div>[5] M. Ries, V. Dötschel, J. Seibert, and S. Pfaller, A self-avoiding random walk algorithm (SARW) for generic thermoplastic polymers and nanocomposites, Zenodo, 2022, https://doi.org/10.5281/zenodo.6245699.</div> <div>[6] The MathWorks, Inc., "Matlab. the language of technical computing", https://de.mathworks.com/help/matlab/.</div> <div> </div> <div> </div> <div><strong>Funding:</strong></div> <div>The authors gratefully acknowledge funding by various sources:</div> <div>The overall research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 377472739/GRK 2423/2-2023. Sebastian Pfaller is furthermore funded by the DFG projects 396414850 (Individual Research Grant 'Identifikation von Interphaseneigenschaften in Nanokompositen') and 505866713 together with the Agence nationale de la recherché (ANR, French Research Agency) – ANR-22-CE92-0049 (Individuel Research Grant 'BIO ART'). In addition, scientific support and HPC resources have been provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) under the NHR project b136dc. NHR funding is provided by federal and Bavarian state authorities. NHR@FAU hardware is partially funded by the DFG project 440719683.</div>
TGA data for the manuscript "Synergistic fire-retardancy properties of melamine coated ammonium poly(phosphate) in combination with rod-like mineral filler attapulgite for polymer-modified bitumen roofing membranes"
<p>The file "SynergisticFireRetardencyPaper_data" containns the raw data and data tretment used in the manuscript<br> "Synergistic fire-retardancy properties of melamine coated ammonium poly(phosphate) in combination with rod-like mineral filler attapulgite for polymer-modified bitumen roofing membranes" for the the TGA part of the work.<br> The file "TGA_Data_and_Data_treatment.xls" contains the TGA raw data used in the manuscript and the recaluclation to a common temperature scale. The file "TGA_plots_20180611.opju" caontian the contruction of the plots shown in the paper.</p> <p> </p>
Safety, Effectiveness and Participant Satisfaction Study of a Dermal Filler (of RADIESSE® (+) Lidocaine) in the Treatment of Ageing Signs in the Face
ClinicalTrials.gov study NCT03650387. IPD Sharing: NO. Countries: 1. Publications: 1.
Radiesse® Injectable Dermal Filler for the Treatment of Nasolabial Folds in Persons of Color
ClinicalTrials.gov study NCT01012388. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Voluma Filler Agent For The Treatment of HIV-associated Facial Lipoatrophy
ClinicalTrials.gov study NCT02342223. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Gene Expression Study Between Two Dermal Injectables Hydroxylapatite Semi-permanent Filler
ClinicalTrials.gov study NCT05620043. IPD Sharing: NO. Countries: 1. Publications: 1.
Nanodiamond Modified Gutta Percha (NDGP) Composite for Non-surgical Root Canal Therapy (RCT) Filler Material
ClinicalTrials.gov study NCT02698163. IPD Sharing: NO. Countries: 1. Publications: 1.
Clinical Study for the Evaluation of the Safety and Effectiveness of Use of a Poly-L Lactic Acid Injectable Filler for the Aesthetic Treatment of Nasolabial Folds
ClinicalTrials.gov study NCT05215054. IPD Sharing: NO. Countries: 1. Publications: 2.
Evaluation of Pain With Lidocaine-Mixed Radiesse® Injectable Dermal Filler
ClinicalTrials.gov study NCT01012661. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Caries Prevention Effect of S-PRG Filler Incorporated in Denture Base Resins on Edentulous Elderly People
ClinicalTrials.gov study NCT02460562. IPD Sharing: YES. Countries: 1. Publications: 4.
Safety and Efficacy of Azzalure/Dysport, Restylane/Emervel Filler and Restylane Skinbooster Treatment
ClinicalTrials.gov study NCT02297516. IPD Sharing: Not stated. Countries: 3. Publications: 1.
Efficacy of Injected Local Anesthetic vs Topical Anesthetic in Cosmetic Injectable Fillers.
ClinicalTrials.gov study NCT02379221. IPD Sharing: NO. Countries: 1. Publications: 8.
The utilization of micro-mesoporous carbon-based filler in the P84 hollow fiber membrane for gas separation
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.