This data publication contains the raw and derived data (e.g., extracted peak areas, peak intensities, area ratios, etc.) from microdrop UV-Vis spectroscopy, handheld Raman spectroscopy, liquid chromatography with UV detection, and ambient ionization (direct analysis in real time [DART]) triple quadrupole mass spectrometry analyses of compounded and personalized pain management medicines.

Spatter particles from nickel superalloy 625 were captured and measured during the printing of a 25 mm x 10 mm rectangular pad in commercial laser powder bed fusion (PBF-LB) machine. Particles were captured with a glue-coated sticky plate that covered the entire powder bed, holding any landed particles at their original landing sites for ex-situ measurement in an optical microscope. Large-area images of the sticky plates were processed with a convolutional neural network (CNN) to automatically identify spatter particles.

The data are associated with figures in R. Giang, R. Tao,*, E. Moukhina, A. L. Forster, T. J. Cho, P. Centellas, S. Romberg, Z. Tsinas, C. Soles, Predicting Cure Evolution and Thermal Endurance of a Highly Filled Epoxy Underfill for Advanced Packaging, Journal of Polymer Science 2026, https://doi.org/10.1002/pola.70283

Design files and data for NIST Standard Reference Material (SRM) 2169, Scale and Distortion Standard for Forensic Topographic Surface Measurement. The designs for the SRM chip
and the post are provided in [FreeCAD](freecad.org) format, and in STEP format. A fabrication drawing is included for the SRM post.

Electron tomography tilt series data, reconstruction, and data processing code for three-dimensional imaging of a gate-all-around (GAA) transistor layer extracted from a commercially available chip.

This data was collected on July 21, 2025.

This dataset contains data to support the publication, "Understanding Reporting Variability in Fire Debris Data Interpretation through an Interlaboratory Study".

Included in this dataset is:
- Full set of processed data from the interlaboratory study
- Information on instrumental methods used to collect spectral data
- Copies of the interlaboratory study instruction sheet and survey form
- Raw datafiles for all unknown samples, neat ignitable liquids, and control samples

The CHIPS Metrology Ontology originated from a pragmatic desire to understand how the various research entities under the CHIPS Metrology described by the Seven Grand challenges (https://doi.org/10.6028/nist.chips.1000), are related to each other. The named classes within this ontology came from the data management plans and adjacent documents associated with the projects within the Severn Grand Challenges. The class hierarchy was mainly assembled by June Lau.

This dataset supports the manuscript “Does aging alter the strain-rate response of PPTA body armor fibers? A paired single-filament investigation”. The study examined two related questions: whether the relationship between quasi-static (QS) and high strain rate (HSR) tensile properties of poly(p-phenylene terephthalamide) (PPTA) fibers is preserved during accelerated aging and whether QS-based tensile inputs remain reliable for predicting ballistic-performance degradation.

Efficient use of fibers in composite materials requires a precise understanding of the factors governing their mechanical performance. Among these, the size effect, or the dependence of fiber tensile strength on size, remains not fully characterized. The conventional two-parameter Weibull model often fails to capture this dependence accurately. In this study, Weibull models incorporating fiber length, surface area, and volume were applied to three high-performance fibers: LCP-1, Aramid-1, and Amide-1.

TOVA is a topic modeling platform with a plug-in architecture, supporting training and inference via CLI and web interface.