The files within this record represent the data shown in the Nature Electronics article, "A Traveling-Wave Parametric Amplifier and Converter".

Dynamic Polymer Annotated Library (DPAL)

DPAL is an annotated library of peer-reviewed research that aims to: (1) Fill a knowledge gap in the materials science field (2) Re-design a common medical field practice (the systematic literature search) to be more applicable and universal to materials design questions.

The data presents the genome sequencing and assembly of Escherichia coli NIST0056. This study utilized E. coli as a model organism to introduce a highly efficient DNA extraction protocol that employs Adaptive Focused Acoustics® (AFA) technology. This method achieves an optimal balance between cell lysis and DNA integrity. Additionally, it takes genome copy numbers into consideration to estimate DNA extraction efficiency. With E. coli, this protocol has achieved nearly 100% cell lysis, establishing a new benchmark for performance.

This data publication provides raw data, processed data, dataframes, and representative scripts to support our recent work on NMR spectroscopy of aqueous alkali fluoride solutions. The repository contains both experimental NMR spectroscopy data and multiscale modeling data for 23Na and 19F in sodium fluoride (NaF) solutions, as well as 19F data for other Group I alkali metal fluorides (LiF, KF, RbF, and CsF).

Magnetometry data for micropatterned magnetic nanoparticle (MNP) composites. The data contains the applied "Magnetic Flux Density" (T) and "Measured Magnetic Moment" (Am2) for 3 sample orientations (a-axis, b-axis, c-axis). The dataset also contains the "Corrected Magnetic Moment" (Am2) for each orientation, which has been corrected for para- and dia- magnetic background signal.

This zip file contains experimental data, refined configurations, and other necessary input to RMCProfile used in structural refinements reported in the paper "Emergent topological polarization textures in relaxor ferroelectrics" by M. Eremenko, V. Krayzman, S. Gorfman, A. Bosak, H. Y. Playford, P. A. Chater, B. Ravel, W. J. Laws, F. Ye, A. Minelli, B.-X. Wang, Z-G. Ye, M. G. Tucker, I. Levin.

NIST Generative AI (GenAI) is a new evaluation program administered by the NIST Information Technology Laboratory to assess generative AI technologies developed by the research community from around the world. NIST GenAI is an umbrella program that supports various evaluations for research and measurement science in Generative AI by providing a platform for Test and Evaluation. One component of GenAI is NIST GenAI Code, which currently evaluates: Can AI generate code for testing software reliably? This item is the open-source scoring code software used to score NIST GenAI Code submissions.

HOTA-ReID is a modified version of the Higher Order Tracking Accuracy (HOTA) metric specifically designed to support Re-Identification (ReID) problems while providing significant performance improvements through parallel processing acceleration.

The data were generated as part of the BL2 Beam Neutron Lifetime experiment running on the NG-C beamline at the NIST NCNR. These data specifically address the question of charge exchange between the trapped proton and residual molecular hydrogen in the proton trap. Event mode data (energies and times) for the relevant experimental parameters are included, as well as supporting simulations. Also included are some residual gas analyzer data and some data that were acquired during an earlier version of the beam neutron lifetime experiment.

These data are results from the dynamic laser coupling of scanned single tracks on bare nickel alloy 718 associated with AM-Bench 2022. In this work, “laser coupling” is the portion of applied laser power that is not reflected from the material. The laser coupling (P_lc) value is determined by measuring the reflected laser power (P_rho), dividing that value by the applied laser power (P_app), and subtracting it from unity (making the value unitless, with a range from 0 to 1), i.e., P_lc = 1 – P_rho/P_app.