The database includes mechanical data for structure-properties relationships and mechanical modeling of elastic impact protection foams from a variety of imaging (micro-computed tomography, digital image correlation) and force-sensing instruments (dynamic mechanical analysis, universal test system) under a wide range of experimental conditions and modes. The data repository includes directories for: dynamic mechanical analysis raw data, results, and analysis tools; intermediate rate (servo-hydraulic UTS based) raw data including 2D digital image correlation (DIC) images, results, and analysis tools; quasi-static rate (electro-mechanical UTS based) raw data including 2D digital image correlation (DIC), results, and analysis tools; micro-computed tomography data including raw volume images, filtered images, binarized images, other results, and analysis tools; and, instrumented drop tower data including backface force, high speed video, and results and analyzed data, Fourier Transform Infrared (FTIR) spectra, and differential scanning calorimetry (DSC) data.For more information see the readme and data documentation in each respective directory. A paper describing data collection, analysis, and database documentation is available here: https://doi.org/10.1038/s41597-023-02092-4. A repository containing example usage code is available at: https://github.com/materials-data-facility/foam_db. File formats for data include .txt, .xls, .tri, .tprc, .rcp, .py, .m, .csv, .mat, .vtk, .spa, .exp, .stl, and .tif.

This repository contains data generated to support and ECTC 2025 conference manuscript titled "Advanced Metrology Suite for Linking Residual Stress to Fundamental Properties of Thermoset Packaging Materials". It contains differential scanning calorimetry (DSC), rheology, digital image correlation (DIC), vapor uptake, and stress bench data on and example commercially available encapsulant epoxy material. The goal of the study and data is to (a) demonstrate these techniques, and (b) better understand the cure kinetics, liquid-to-solid transition, and residual stresses in for this material system. More complete descriptions of the methods and finding are available in the associated manuscript.The dataset contain about 2.5 GB of data, most of which by size is DIC images in .7z compressed folders. Most data is provided in .csv, .xslx, and .mat files. Resultant figures are included for reference in .png, .tiff or similar formats.

This repository contains data generated to support and ECTC 2025 conference manuscript titled "Advanced Metrology Suite for Linking Residual Stress to Fundamental Properties of Thermoset Packaging Materials". It contains differential scanning calorimetry (DSC), rheology, digital image correlation (DIC), vapor uptake, and stress bench data on and example commercially available encapsulant epoxy material. The goal of the study and data is to (a) demonstrate these techniques, and (b) better understand the cure kinetics, liquid-to-solid transition, and residual stresses in for this material system. More complete descriptions of the methods and finding are available in the associated manuscript.The dataset contain about 2.5 GB of data, most of which by size is DIC images in .7z compressed folders. Most data is provided in .csv, .xslx, and .mat files. Resultant figures are included for reference in .png, .tiff or similar formats.

The following data files include residual elastic strain, residual stress, and part deflection results associated with the 2022 Additive Manufacturing Benchmark test series (AM Bench 2022) AMB2022-01 benchmark on laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects. The AM builds were performed on the NIST Additive Manufacturing Metrology Testbed (AMMT). The residual elastic strains were measured using synchrotron X-ray diffraction at the Cornell High Energy Synchrotron Source (CHESS) and neutron diffraction at the Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR). Residual stresses were characterized using the contour method by UC Davis and Hill Engineering. Part deflection after partial cutting of the build part off the build plate was measured at NIST. Detailed descriptions of the build process parameters, scan pattern, heat treatment, and descriptions of all of the AMB2022-01 measurements are provided on the AMB2022-01 challenge description webpage (https://www.nist.gov/ambench/amb2022-01-benchmark-measurements-and-challenge-problems). Due to the time-sensitive nature of the AM Bench challenge problems, those measurements and analyses were prioritized. The challenges that this data publication address are:Residual elastic strain (CHAL-AMB2022-01-RS): Residual elastic strain components at select locations internal to the bridge structure, corresponding to synchrotron X-ray diffraction measurements. Part deflection (CHAL-AMB2022-01-PD): Deflection of the as-built (no heat treatment) bridge structure after it is partially separated from the build plate.Additional datasets that are not required for the challenges will be added soon. For updates, please check back here or at www.nist.gov/ambench.

The following data files include residual elastic strain, residual stress, and part deflection results associated with the 2022 Additive Manufacturing Benchmark test series (AM Bench 2022) AMB2022-01 benchmark on laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN718 test objects. The AM builds were performed on the NIST Additive Manufacturing Metrology Testbed (AMMT). The residual elastic strains were measured using synchrotron X-ray diffraction at the Cornell High Energy Synchrotron Source (CHESS) and neutron diffraction at the Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR). Residual stresses were characterized using the contour method by UC Davis and Hill Engineering. Part deflection after partial cutting of the build part off the build plate was measured at NIST. Detailed descriptions of the build process parameters, scan pattern, heat treatment, and descriptions of all of the AMB2022-01 measurements are provided on the AMB2022-01 challenge description webpage (https://www.nist.gov/ambench/amb2022-01-benchmark-measurements-and-challenge-problems). Due to the time-sensitive nature of the AM Bench challenge problems, those measurements and analyses were prioritized. The challenges that this data publication address are:Residual elastic strain (CHAL-AMB2022-01-RS): Residual elastic strain components at select locations internal to the bridge structure, corresponding to synchrotron X-ray diffraction measurements. Part deflection (CHAL-AMB2022-01-PD): Deflection of the as-built (no heat treatment) bridge structure after it is partially separated from the build plate.Additional datasets that are not required for the challenges will be added soon. For updates, please check back here or at www.nist.gov/ambench.

The development of large residual elastic strains and stresses during laser powder-bed fusion (LPBF) additive manufacturing is one of the most significant barriers to widespread adoption. Accurate modeling of these strains and stresses is broadly recognized as an effective tool for mitigating these challenges, but rigorous validation data are needed. This data publication includes measurement data from diffraction-based characterizations of residual elastic strains in as-built (not heat treated) artifacts manufactured as part the the 2018 Additive Manufacturing Benchmark Series (AM Bench). Comprehensive details about AM Bench and the measurement data released in 2018 and 2022 may be found at .

The development of large residual elastic strains and stresses during laser powder-bed fusion (LPBF) additive manufacturing is one of the most significant barriers to widespread adoption. Accurate modeling of these strains and stresses is broadly recognized as an effective tool for mitigating these challenges, but rigorous validation data are needed. This data publication includes measurement data from diffraction-based characterizations of residual elastic strains in as-built (not heat treated) artifacts manufactured as part the the 2018 Additive Manufacturing Benchmark Series (AM Bench). Comprehensive details about AM Bench and the measurement data released in 2018 and 2022 may be found at .

This dataset contains information from investigating the effects of micro-computed tomographic imaging irradiation on vinyl nitrile foam and code for a finite element user material to model these effects. More details are available in the README.txt and data_summary.txt files in the main directory.Data in the repository includes exposure and dosage calibration files (.csv, .dat, .mat, .in, .png. .jpg), imaging data from optical microscopy (.tif, .zvi) and scanning electron microscopy with energy-dispersive spectroscopy (SEM EDS) (.tif, .png, .docx). Also included is characterization data from differential scanning calorimetry (DSC) with metadata (.tprc, .tseq), test data (.tri, .csv) and analysis metadata and data (.py, .m, .tri, .xls, .xlsx, .pdf), characterization results data via dynamic mechanical analysis (DMA) and stress relaxation (SR) with metadata (.tprc, .csv), test data (.tri, .csv) and analysis metadata and data (.py, .m, .tri, .xls, .xlsx, .pdf). Data from characterization via differential scanning calorimetry metadata (.tprc, .tseq), test data (.tri, .csv) and analysis metadata and data (.py, .m, .tri, .xls, .xlsx, .pdf). Data from characterization via Fourier transform infrared spectroscopy (FTIR) generates metadata (.spa, .csv, .exp), test data (.spa, .csv) and analysis metadata and data (.xls, .csv, .pdf), and data from Soxhlet extraction (.xlsx). Each test type includes textual descriptions (.txt) and/or photographs (typically .jpg) to aid in completeness, describe measurands and measurement uncertainties, and explain the file organization. A .zip file containing code for a calibrated finite element user material for mechanical model that includes radiation and temperature effects is also included in the main directory. Please contact the authors with any questions.This dataset consists of approximately 335 files that require ca. 605 MB of storage.