In embedded 3D printing, a nozzle is embedded into a support bath and extrudes filaments or droplets into the bath. This repository includes Python code for analyzing and managing images and videos of the printing process during extrusion of single filaments. The zip file contains the state of the code when the associated paper was submitted. The link to the GitHub page goes to version 1.0.0, which is the same as the code attached here. From there, you can also access the current state of the code.Associated with: L. Friedrich, R. Gunther, J.

The absolute laser absorption was measured simultaneously with X-ray imaging during laser melting of Ti-6Al-4V solid metal. The data included here are the time-resolved absolute absorbed power and the Xray images acquired at the same time, along with timing data for synchronization. Also included is information about the experimental configuration including applied laser power, laser beam spatial profile, and the experimental setup. A text document is included that describes all files.

Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants

This data set contains files included in the detailed instructional demonstration paper submitted to Integrating Materials and Manufacturing Innovation. The detailed instructional demonstration paper includes documentation detailing how to configure and carry out a repeatable Rietveld Refinement with the software MAUD. The data set provides: diffraction data from two different neutron diffraction measurements, crystallographic information files, and configuration files for the refinement process.

SolidWorks Part file (CAD file) for a CoCr "lattice" structure additively manufactured in a laser bed powder fusion (LPBF) system at NIST.

The NIST/ARPA-E Database of Novel and Emerging Adsorbent Materials is a free, web-based catalog of adsorbent materials and measured adsorption properties of numerous materials obtained from article entries from the scientific literature. Search fields for the database include adsorbent material, adsorbate gas, experimental conditions (pressure, temperature), and bibliographic information (author, title, journal), and results from queries are provided as a list of articles matching the search parameters.

This dataset includes a Microsoft Excel spreadsheet (*.xlsx file) provided as supplemental material for the NIST Technical Note (TN-2099) publication titled "Quasi-Static Position Calibration of the Galvanometer Scanner on the Additive Manufacturing Metrology Testbed". The file contains two tabs, titled "Pre-Compensation" and "Post-Compensation", which provides example measurement data and calculations pertaining to the calibration procedures described in the publication.

Supplementary Data for the paper "Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powders" by E.J. Garboczi and N. Hrabe. Contains all the data and programs described in this paper to generate the results discussed in the paper. Also contains all the results that are generated by the data and programs, with which the user can compare to check their results.

Materials discovery and development necessarily begins with the preparation and identification of product phase(s). Crystalline compounds can be identified by their characteristic diffraction patterns using X-rays, neutrons, and or electrons. An estimated 20,000 X-ray diffractometers and a comparable number of electron microscopes are used daily in materials research and development laboratories for this purpose.

These measurements were performed as part of the 2018 Additive Manufacturing Benchmark Test Series (AM-Bench). This dataset and the associated experiments are part of a continuing series of controlled benchmark tests, in conjunction with a conference series, with two initial goals, 1) to allow modelers of Additive Manufacturing processes to test their simulations against rigorous, highly controlled additive manufacturing benchmark test data, and 2) to encourage additive manufacturing practitioners to develop novel mitigation strategies for challenging build scenarios.