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43 results for “Calorimetry”
Maximum temperature data from thermal safety assessment of type 21700 lithium-ion batteries with NMC, NCA and LFP cathodes by means of Accelerating Rate Calorimetry (ARC)
<p>Data of safety investigation and thermal abuse behavior of commercial type 21700 LIB cells is provided.</p> <p>It has been acquired with Accelerating Rate Calorimetry (ARC), using a Thermal Hazard Technology type ES ARC.</p> <p>Moreover, thermal abuse was done by means of the so-called Heat-Wait-Seek (HWS) test, at different states of charge (SOC) from 0 to 100.</p> <p>Different cathode chemistries are compared (NMC, NCA and LFP), as well as for NCA chemistry, the high energy (HE) and high power (HP) cell design.</p> <p>For each cell, data includes the maximum temperature measured during thermal abuse at the surface on the center of the cell. Additionally, the mean value and standard deviation for each cell type and state of charge is provided.</p> <p>This data is supporting this article in the journal Batteries:</p> <p><a href="https://doi.org/10.3390/batteries9050237">https://doi.org/10.3390/batteries9050237</a></p> <p>Additional supporting material to this article are the exothermal data for thermal abuse, that are published here:</p> <p><a href="https://doi.org/10.5281/zenodo.7707929">https://doi.org/10.5281/zenodo.7707929</a></p> <p> </p>
Proccessed data for Trend Validation of Metabolic Models Against Measurements Using Indirect Calorimetry
<p>A cleaned data set used to validate metabolism models in a muscuskeletal modeling software.<br> The dataset contains 240 rows and 18 columns. </p> <p>Labels:</p> <ul> <li>AnyMet = Metabolic output by the modelling software. Calculated as the mean energy cost per repetition [J] .</li> <li>VynMet = Metabolic output by the indirect calorimetry system (Vyntus CPX). Calculated as the mean energy cost per repetition [J].</li> <li>rest_energy = total energy cost during rest [J]. Measured with Indirect caliometry</li> <li>rest_time = total time of rest [min]</li> <li>Work = Energy cost times the displacement per rep [J].</li> <li>watt = Work divided by total duration of a repetition [J/s]</li> <li>extension time = duration of the extension part of the movement [s]</li> <li>flexion time = duration of the flexion part of the movement [s]</li> <li>bw = bodyweight [kg]</li> <li>height [m]</li> <li>CV = coefficient of variation for the measured rest_energy. </li> <li>model = model type used for AnyMet. </li> <li>Subject </li> <li>Contraction = Contraction type performed</li> <li>intensity = Intensity to overcome created by the dynamometer. </li> <li>mech_watt_kg = mechcanical watt, watt divided by bodyweight</li> <li>any_met_watt_kg = watt pr kg: (AnyMet / bw) / (extension time + flexion time)</li> <li>vyn_met_watt_kg = watt pr kg: (VynMet / bw) / (extension time + flexion time)<br> <br> There is also a zip file containing the raw data from the dynanometer and the Vyntus PGE system.</li> </ul>
Crystallinity and perfection in ethylene vitrimers probed by combined calorimetry, scattering, and time-domain NMR
<p>This Dataset comprises the raw data contained in the figures of our journal article in <em>Frontiers in Soft Matter </em>(DOI: 10.3389/frsfm.2023.1208777)<em>. </em>We provide a preprint of the article for reference to the figures and their captions, necessary to use the data. For copyright details and licensing we refer to the original article and the publisher. Here is the abstract of the article:</p> <p>The kinetics of crystallization and crystal-crystal transformations in ethylene vitrimers are studied by time-domain NMR. These vitrimers previously exhibited polymorphic transition of crystal structures, which are shown here to be distinguishable by NMR via their dipolar line widths based upon different proton densities and fast internal motions. The conditions under which the polymorphs are formed and interconvert are identified via time-resolved NMR experiments, with a focus on recrystallization after full and partial melting. DSC experiments are used to clarify an unexpected superheating effect, which challenges the determination of actual melting points. We further identify a strong memory effect in isothermal (re)crystallization. Implications of the dynamic nature of the vitrimers in relation to the kinetics of crystallization are discussed. We find that internal perfecting of crystals, enabled by the vitrimeric exchange process, can have a large effect on the DSC-detected melting enthalpy without change in overall crystallinity.</p>
Dataset/Development of a novel calorimetry setup based on metallic paramagnetic temperature sensors
<p>Dataset related to the publication "Development of a novel calorimetry setup based on metallic paramagnetic temperature sensors" submitted to Review of Scientific Instruments.</p>
Isothermal calorimetry data of seawater-mixed cement pastes produced with binary and ternary blended binder composition with fly ash, slag, metakaolin, and limestone
<p>The following file consists of data and its metadata from the published article Rathnarajan et al., (2024) Comprehensive evaluation of early-age hydration and compressive strength development in seawater-mixed binary and ternary cementitious systems published in Archives of Civil and Mechanical Engineering. </p> <p>Metadata file: metadata_calorimetry.xlsx consists of the details of file name, operator of equipment, test starting to completion time, number of hours, and notation of the mix-IDs according to the paper. </p> <p>In 11 data files in xlsx format, the heat flow and cumulative heat generated up to 7 days for the various binder combinations produced with CEM I, fly ash, metakaolin, slag, and limestone are presented. Along with that normalized heat flow and normalized cumulative heat with respec to time up to 7 days were included. The following are the data file names in .xlsx format included along with this zip file. </p> <p>P1-P8.xlsx<br>P9-P14.xlsx<br>P15-P18.xlsx<br>P19-P24.xlsx<br>P25-28.xlsx<br>P29-30-43-46.xlsx<br>P33_34-P39-41.xlsx<br>P47-P52.xlsx<br>P53-P58.xlsx<br>P59-P64.xlsx<br>P65-P70.xlsx</p> <p>The following files can be accessed with the pacakge Microsoft excel and data can be used for further analysis. </p>
Isothermal Titration Calorimetry Data - Intramolecular autoinhibition regulates the selectivity of PRPF40A tandem WW domains for proline-rich motifs
<p>This is the repository of all ITC data related to the paper:</p> <p><strong><span>Intramolecular autoinhibition regulates the selectivity of PRPF40A tandem WW domains for proline-rich motifs</span></strong></p> <p><span>Santiago Martínez-Lumbreras<sup>1,2,*</sup>, Lena K. Träger<sup>2</sup>, Miriam M. Mulorz<sup>3</sup>, Marco Payr<sup>2</sup>, Varvara Dikaya<sup>2</sup>, Clara Hipp<sup>1,2</sup>, Julian König<sup>3</sup> and Michael Sattler<sup>1,2,*</sup></span><strong><span> </span></strong></p> <p><sup><span>1</span></sup><span> <span> </span>Helmholtz Munich, Molecular Targets and Therapeutics Center, Institute of Structural Biology, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany</span></p> <p><sup><span>2</span></sup><span><span> </span>Technical University of Munich, TUM School of Natural Sciences, Department of Bioscience, Bavarian NMR Center, Lichtenbergstrasse 4, 85747 Garching, Germany</span></p> <p><sup><span>3</span></sup><span> Institute of Molecular Biology (IMB) gGmbH, Ackermannweg 4, 55128 Mainz, </span><span>Germany</span></p> <p><span>* Correspondence should be addressed to: </span></p> <p><span>Santiago Martínez Lumbreras <a href="mailto:santiago.martinez@tum.de">santiago.martinez@tum.de</a> or</span></p> <p><span>Michael Sattler </span><span><a href="mailto:michael.sattler@helmholtz-munich.de"><span>michael.sattler@helmholtz-munich.de</span></a></span></p>
The global energy balance of the ASDEX Upgrade tokamak determined with the revised cooling water calorimetry
<p>Provided data includes data sets required for running the AUG calorimetry. The database consists of the flow rate, time correction and the distance between the temperature measuring points of inlet and outlet cooling water of each cooling unit. </p>
Exothermal data from thermal safety assessment of type 21700 lithium-ion batteries with NMC, NCA and LFP cathodes by means of Accelerating Rate Calorimetry (ARC)
<p>Data of safety investigation and thermal abuse behavior of commercial type 21700 LIB cells is provided.</p> <p>It has been acquired with Accelerating Rate Calorimetry (ARC), using a Thermal Hazard Technology type ES ARC.</p> <p>Moreover, thermal abuse was done by means of the so-called Heat-Wait-Seek (HWS) test, at different states of charge (SOC) from 0 to 100.</p> <p>Different cathode chemistries are compared (NMC, NCA and LFP), as well as for NCA chemistry, the high energy (HE) and high power (HP) cell design.</p> <p>For each cell, data includes the exothermal behavior of the cells, which is recorded only when the cell is behaving exothermally in the ARC, above a threshold of 0.02 °C / min.</p> <p>Hence, in the files, time in minutes, temperature on the surface at the center of the cell in °C and the registered temperature rate in °C / min is provided. Cathode chemistry, as well as SOC, is indicated in the file name, each set of parameters has been tested at least twice with another cell, which is indicated with M and consecutive numbering of the test number.</p> <p>This data is supporting this article in the journal Batteries:</p> <p><a href="https://doi.org/10.3390/batteries9050237">https://doi.org/10.3390/batteries9050237</a></p> <p>Additional supporting material to this article are the maximum temperatures for thermal abuse, that are published here:</p> <p><a href="https://doi.org/10.5281/zenodo.7867730">https://doi.org/10.5281/zenodo.7867730</a></p> <p> </p> <p> </p>
Early Goal Nutrition Therapy Guided by Indirect Calorimetry and Nitrogen Balance Among Critically Ill Patients With Acute Kidney Injury (ENGINE Study)
ClinicalTrials.gov study NCT06238674. IPD Sharing: YES. Countries: 1. Publications: 3.
Indirect Calorimetry Versus Urea-creatinine Ratio to Evaluate Catabolism in Critically Ill Patients
ClinicalTrials.gov study NCT06244381. IPD Sharing: NO. Countries: 1. Publications: 6.
Energy Expenditure in ICU Patients Using Predictive Formulas and Various Body Weights Versus Indirect Calorimetry
ClinicalTrials.gov study NCT02552446. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Feeding With Indirect Calorimetry and Cycling in the Elderly
ClinicalTrials.gov study NCT03540732. IPD Sharing: UNDECIDED. Countries: 1. Publications: 10.
Inter-day Reliability of the Oral Glucose Tolerance Test Using Indirect Calorimetry
ClinicalTrials.gov study NCT04320433. IPD Sharing: NO. Countries: 1. Publications: 1.
Influence of Renal Replacement TherApy on Indirect Calorimetry
ClinicalTrials.gov study NCT04599569. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Plasma CO2 Removal Due to CRRT and Its Influence on Indirect Calorimetry
ClinicalTrials.gov study NCT03314363. IPD Sharing: NO. Countries: 1. Publications: 12.
Use of Indirect Calorimetry in Obesity
ClinicalTrials.gov study NCT03233568. IPD Sharing: NO. Countries: 1. Publications: 1.
Feasibility of Integrating Indirect Calorimetry (IC) Technology in Primary Care
ClinicalTrials.gov study NCT00750022. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Using Indirect Calorimetry for Liver Transplants Patients
ClinicalTrials.gov study NCT03622268. IPD Sharing: NO. Countries: 1. Publications: 4.
Calorimetry Guided Nutrition vs. Recommended Daily Intake in Weaning Chronically Ventilated Patients: Double Blind RCT.
ClinicalTrials.gov study NCT04825717. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Calorimetry of a Quantum Phase Slip
<p>Dataset:</p> <ol> <li>FIG2.B : Spectrum measurement at cryostat temperatures 50 mK and 400 mK</li> <li>FIG2.C : Calibration curve - Output Power vs. Temperature at zero voltage bias for two phase drops</li> <li>FIG2.D : Resonator response at zero voltage bias as a function of increasing applied magnetic flux, at three cryostat temperatures (50 mK, 200 mK, 400 mK)</li> <li>FIG2. E : Temperature dependence of the screening parameter β</li> <li>FIG3. A : Time-resolved electron temperature in the absorber, at different starting temperatures set by the cryostat bath</li> <li>FIG3. B : Return to equilibrium ∆T (t) at 100 mK, following a flux pulse.</li> <li>FIG3. C : Magnitude of the initial temperature rise ∆T_0 at t = 0 and the fit</li> </ol>
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OpenNeuro
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