MURI/AUSMURI Project: Rationalization of Interphase Instabilities during Thermo-Mechanical Gyrations Typical

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  • Files in the data repository are organized in folders according to sample identifiers. Samples are named according to the following convention SP_00XX where “XX” are two numerals. Some sample identifiers additionally include a “b” at the end indicating a repeated test subsequent to a failed test. Each folder contains Comma Separated Values (CSV) files from the MTS (DAQ_Running_Time_Timed.txt) and Vic3D systems (SP_00XX_data.txt), a MATLAB scripts for data interpolation (Analysis_script.m), and the CSV file that is generated from running the MATLAB script (SP_00XX_MTS_V3D.csv). For stress calculations it is necessary to input cross-section information for each sample. Sample dimensions (as well as machining direction, material condition, and mechanical test) are included in a descriptive excel file in the root folder named "samples.xlsx". A set of folders (SP_0001b, SP_0003, SP_0005b, SP_0006b, SP_0007b, SP_0009, SP_0010, SP_0011, SP_0012) has one CSV file from MTS and one CSV file from Vic3D (the timing data from the Vic3D cameras was manually added to the strain data file). Folders associated with subsequent tests (SP_0070-SP0082) contain two CSV files from Vic3D (SP_00XX_data.txt, SP_00XX.txt): strain data and data acquisition timing. Regardless, MATLAB scripts in each folder correctly read and interpolate the data as needed. Folders SP_0068 and SP_0069 contain single files because interpolation of MTS and Vic3D data was done manually in Excel prior to development of analysis script.
    Data Types:
    • Dataset
    • File Set
  • Here we present an AM simulation data generated from Autodesk Netfabb Local Simulation, a non-linear finite element thermo-mechanical solver for additive manufacturing (AM) processes. The dataset contains two simulation trials based on Ti-6Al-4V material under various processing conditions. The simulation software generates fine-scale thermal data of laser scanning path and corresponding mechanical properties data across all time frames. Each dataset contain timestep folders and all related thermal and mechanical properties data can be found within timestep folders.
    Data Types:
    • Tabular Data
    • Dataset
  • Ti-10-2-3 Thermophysical Properties for Thermal Simulations with SYSWELD and FLOW-3D.
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    • Dataset
  • This dataset including the high-speed and high-spatial resolution IR data for single spot ti-6-4 melting. The high speed dataset was captured by Telops m3k high speed camera with 20kHz frame rate and 30um spatial resolution. The high spatial dataset was captured by Micro-Epsilon M1 IR camera with 1kHz frame rate and 8um spatial resolution. The details description is included inside the folder
    Data Types:
    • Other
    • Image
    • Tabular Data
    • Dataset
    • Text
  • Here, we are using three different EB PBF scan strategies: linear scan (LS), ordered spot scan (OS), and random spots scan (RS) to fuse the widely used Ti-6Al-4V powder (Ti64). The change in scan strategies and therefore the thermal gradients create variation in the defects within the microstructure of the material. Such variations can be analyzed using optical microscopy (OM). After standard metallography sample preparation, imaging was performed using an Olympus DSX510 optical microscope on 5x magnification to characterize the entire surface of each sample with sufficiently high image resolution. High magnification images of the entire surface with smaller field-of-view were first taken step-by-step and subsequently stitched together. Samples were then etched to reveal the underlying microstructure to compare to existing EBSD scans to compare the grain structure exhibited from using different techniques. Using image processing (MIPAR) software, AM build defects were identified, quantified, and exported to a coding language for further data analysis. The code translates the provided quantitative data and generates histograms for eccentricity (roundness of defects), orientation (with respect to the positive x-axis), and caliper diameter (size), site-specifically. This allows to analysis the spatial distribution of defects, e.g., difference between defects in the center of the build vs. edge defects in each sample.
    Data Types:
    • Dataset
  • The data provided are confocal fluorescence images of symmetric giant unilamellar vesicles (GUVs) and asymmetric giant unilamellar vesicles (aGUVs). We observed that a few percent of aGUVs (5-10%) prepared in our experiments show anti-alignment of domains between the inner and the outer leaflet (see Data in Brief report). This dataset shows fluorescence micrographs obtained using scanning fluorescence confocal microscopy. For the system chosen, DSPC/DOPC/POPC/chol, the fluorescence signal of (1-palmitoyl-2-(dipyrrometheneboron difluoride)undecanoyl-sn-glycero-3-phosphocholine) TopFluorPC (TFPC) and 1,1'-Dioctadecyl-3,3,3',3'- Tetramethylindodicarbocyanine Perchlorate (DiD) show anti-alignment of the brighter domains on aGUVs. We also compare the modulated phases observed in GUVs and aGUVs. For these datasets, we collected a z-stack of micrographs. Images were collected in a scanning microscope Nikon Eclipse C2+ (Nikon Instruments, Melville, NY).
    Data Types:
    • Other
    • Image
    • Tabular Data
    • Dataset
    • Document
  • Our data consists on microplastics (MPs) observations in mussel species in Scotland (UK) and from downfall dust on households in Edinburgh (UK) during the preparation of a meal. We deployed caged mussels (Mytilus edulis) in an urbanised estuary (Edinburgh, UK) to assess seasonal changes in plastic pollution, and collected mussels (Mytilus spp and subtidal Modiolus modiolus) from eight sampling stations around Scotland to enumerate MP types at different locations. MPs were extracted and quantified according to Catarino et al. (2017). Procedural blanks were used in every processing event, and data is also presented. We quantified to household dust fibres during a meal, using stationary passive samplers.
    Data Types:
    • Tabular Data
    • Dataset
  • Simple approach to describe Spinodal decomposition
    Data Types:
    • Video
    • Dataset
  • This dataset compiled county-level COVID-19 daily cases and cumulative cases data, demographic data (population density, labor force rate, unemployment rate, household median income, metro system or not, statewide stay-at-home order or not), environmental data (maximum and minimum temperature, maximum and minimum relative humidity, precipitation, surface downwelling solar radiation, wind speed), community mobility data (retail and recreation percent change from the baseline which was from January 3 to February 22, grocery and pharmacy percent change from baseline, parks percent change from baseline, transit stations percent change from baseline, workplaces percent change from baseline, residential percent change from baseline, and Mobility and Engagement Index (MEI)), and time-series variables (weekdays, weekends, or not) from different sources from February 15 to May 15, 2020. Moving averaging is also applied to continuous variables, including lag 1 day (the day before the present day) and moving averages of lag 1-7 day and lag 1-14 day.
    Data Types:
    • Tabular Data
    • Dataset
  • Supplementary tables associated with "Evidence for strain rate variation and an elevated transient geothermal gradient during shear zone evolution in the Cordillera Blanca, Peru" by Hughes et al. Includes tables: S1- Stereonet Values, S2: Sample Locations, S3: Thermometry Sampling, and S4: Macro Strain Rate Calculations
    Data Types:
    • Tabular Data
    • Dataset
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