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Size-Dependent Energy and Adhesion of Pd Nanoparticles on Graphene on Ni(111) by Pd Vapor Adsorption Calorimetry
Carbon-supported late transition-metal nanoparticles are promising catalysts and electrocatalysts for wide-ranging applications. However, experimental investigations of the bonding energetics of metal nanoparticles on carbon supports are very limited. Here, in this work, we report heats of adsorption of Pd vapor deposited onto single-layer graphene(0001) supported on Ni(111) at 100 and 300 K as Pd grows particles of well-defined size in the range from three atom clusters to 6 nm diameter. Sizes were determined from He + low-energy ion scattering (LEIS). In this size range, the differential heat of Pd adsorption increases from 228 kJ/mol to within 10 kJ/mol of the heat of sublimation of bulk Pd (377 kJ/mol). The chemical potential of metal atoms in these nanoparticles as a function of average particle size was determined from these results. The adhesion energy at the Pd/graphene(0001)/Ni(111) interface was extracted from these data and found to be 3.5 J/m 2 for the largest Pd particles. For the three metal elements that have now been studied (Pd, Ni, and Ag), we found an increase in metal/graphene(0001)/Ni(111) adhesion energy with metal carbophilicity, which we defined here as the heat of C atom adsorption on that metal’s (111) surface estimated from published density functional theory calculations.
Strip-based Scintillation Detector for Dual-readout High-granularity Calorimetry
New calorimeter technology is being developed for future collider experiments. We are developing a calorimeter that integrates two technologies, a high-granularity calorimeter and a dual-readout calorimeter, and has high time resolution at a picosecond level. The proposed calorimeter is a sampling calorimeter based on scintillation and Cherenkov detectors with high-granularity readout. The Cherenkov detector has a picosecond level time resolution. For the high-granularity scintillation detector, scintillator strips of 300mm × 30mm ×3mm-thick are aligned horizontally and vertically to realize an effective 30mm-square-cell segmentation. Prototype strips with different designs and scintillator materials were tested to compare the performance.
Studies of time resolution, light yield, and crosstalk using SiPM-on-tile calorimetry for the future Electron-Ion Collider
We recently proposed a high-granularity calorimeter insert for the Electron-Ion Collider (EIC) that is based on plastic scintillator tiles readout with silicon photomultipliers. In this work, we concretize its design by characterizing its building blocks with measurements of light yield, optical crosstalk, and timing resolutions using cosmic-rays, an LED, and a beta source. We also compared two approaches for the optical isolation of cells: "megatiles" with grooved boundaries between cells, and a 3D-printed plastic frame hosting individual cells. Further, we found that the latter suppresses optical crosstalk to negligible levels while providing an easier assembly method. Overall, these performance studies can help inform calorimeter design and realistic simulations of 5D showers (time, energy, position) for the EIC and other experiments.
Angular dependent measurement of electron-ion recombination in liquid argon for ionization calorimetry in the ICARUS liquid argon time projection chamber
This paper reports on a measurement of electron-ion recombination in liquid argon in the ICARUS liquid argon time projection chamber (LArTPC). A clear dependence of recombination on the angle of the ionizing particle track relative to the drift electric field is observed. An ellipsoid modified box (EMB) model of recombination describes the data across all measured angles. These measurements are used for the calorimetric energy scale calibration of the ICARUS TPC, which is also presented. The impact of the EMB model is studied on calorimetric particle identification, as well as muon and proton energy measurements. Accounting for the angular dependence in EMB recombination improves the accuracy and precision of these measurements.
Calorimetry with deep learning: particle simulation and reconstruction for collider physics
Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of single isolated particles produced in high-energy physics collisions. We train neural networks on single-particle shower data at the calorimeter-cell level, and show significant improvements for simulation and reconstruction when using these networks compared to methods which rely on currently-used state-of-the-art algorithms. We define two models: an end-to-end reconstruction network which performs simultaneous particle identification and energy regression of particles when given calorimeter shower data, and a generative network which can provide reasonable modeling of calorimeter showers for different particle types at specified angles and energies. We investigate the optimization of our models with hyperparameter scans. Furthermore, we demonstrate the applicability of the reconstruction model to shower inputs from other detector geometries, specifically ATLAS-like and CMS-like geometries. These networks can serve as fast and computationally light methods for particle shower simulation and reconstruction for current and future experiments at particle colliders.
Differential Scanning Calorimetry (DSC) of frontal ring-opening metathesis polymerization (FROMP) of DCPD/ENB/DHF with phosphine inhibitors
This dataset contains DSC cure kinetic and post-cure results for frontal polymerization experiments of dicyclopentadiene (DCPD)/5-ethylidene-2-norbornene (ENB) resins with 2,3-dihydrofuran comonomers with different phosphine inhibitors.
Status of hadronic calorimetry in GEANT4
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Differential Scanning Calorimetry(DSC) Calibration and Measurement
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Demonstrating Calorimetry and Particle Discrimination at MeV Energy Scales with Ambient Backgrounds in the MicroBooNE LArTPC
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Differential Scanning Calorimetry Calibration and Heat Capacity
The differential scanning calorimeter (DSC) 404 F3 is a machine that heats up to 1500 degrees Celsius, and collects/evaluates thermal properties such as heat capacity, crystallization, glass transition, and more. The first part of the project is based around calibrating the DSC 404 F3 using the given procedures and manuals. This ensures that the DSC 404 F3 is working properly and does not have any issues moving forward. After the calibration is complete, the second part is to start testing. There will be tests conducted on known metals, such as steel and aluminum, in which there is data to compare it to. If the data collected is not accurate compared to its known values, further troubleshooting will need to ensue to ensure that the following process does not give wrong readings. Then, testing will begin for High Entropy Alloys(HEA) and the interesting issue with these is that there is no data to compare these to. The goal of finding the values of the HEA is to find a compatible alloy that we can use in future projects.
A Measurement of the Ambient Radon Rate and MeV-Scale Calorimetry in the MicroBooNE LArTPC
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Accelerating Rate Calorimetry Investigations of Thermal Runaway in Multiple Formats and Capacities.
Abstract not provided.
Differential Scanning Calorimetry Calibration and Heat Capacity
The Differential Scanning Calorimeter(DSC) is used to find multiple properties ofmaterials such as heat capacity, melting points, crystallization, and more. Fermilabowns the NETZSCH DSC 404 F3 Pegasus to test novel material for a high poweredtargetry components. The DSC heats up to 1500 C, uses a platinum furnace, and Al 2 O 3 crucibles. In order for the DSC to produce consistent and correct data,calibration of the machine was necessary. Testing with the given calibration kit ofknown metals. Once calibrated, testing on novel materials for their specific heatcapacity ensues.