As monoclonal antibodies have become a vital resource in medicine, knowledge of their complex molecular structures has increased in importance. Thousands of Fab and Fc fragments are described in the Protein Data Bank. Whole antibodies have been imaged by EM methods and in a few cases, crystallized. The central hinge lacks a unique stable conformation and its dynamic properties are important to antibody function.

MediScore (https://github.com/usnistgov/MediScore) is a NIST developed Medifor scoring and evaluation toolkit for Open Media Forensic Evaluation (OpenMFC).

The MaCFP Condensed Phase Subgroup has been designed to enable the fire research community to make significant progress towards establishing a common framework for the selection of experiments and the methodologies used to analyze these experiments when developing pyrolysis models.

Values are computed for the dilute-gas diffusivity of water isotopologues in N2, CO2, and their mixture at a composition representing the atmosphere of Mars, for standard conditions of 101.325 kPa and water mole fraction approaching zero. Values are similarly computed for the diffusivity of methane isotopologues in N2, representing the atmosphere of Titan. Calculations employ state-of-the-art intermolecular potentials and classical trajectory calculations as described in the paper by R. Hellmann and A.H.

This dataset is an inventory of existing quantitative resilience frameworks, indicators, and measures that have been evaluated and entered into a database according to a standardized methodology. The inventory is a broad inventory of existing resilience indicators (whether proposed or applied) and key information for each indicator. The indicators span all systems likely to be included in the assessment methodology, including physical systems (e.g., buildings and infrastructure), social and economic systems, and natural systems (e.g., natural environment).

Supplementary files to accompany the the paper "Super-Ancillary Equations for Cubic Equations of State" of Ian Bell and Ulrich Deiters in Ind. Eng. Chem. Res. Abstract: Calculation of thermodynamic phase equilibrium is error-prone and can fail both near the critical point and at very low temperatures due to the limited precision available in double precision arithmetic. Most importantly, these calculations frequently represent a computational bottleneck.

This dataset contains raw mechanical data (strain, stress and strain rate curves and initial temperatures) for compression experiments performed on annealed 1045 steel using the NIST Kolsky Bar apparatus and a servohydraulic test machine that were used to generate fit coefficients for the plasticity model described in the NIST publication entitled: "A Dynamic Plasticity Model for Rapidly-Heated 1045 Steel up to 1000 °C" with authors S. P. Mates and S.-Y. Li.

In embedded 3D printing, a nozzle is embedded into a support bath and extrudes filaments or droplets into the bath. Using OpenFOAM, we simulated the extrusion of filaments and droplets into a moving bath. This dataset focuses on the effect of Newtonian viscosity and Herschel-Bulkley plateau (pre-yielded) viscosity on the extrusion of single lines. OpenFOAM is an open source computational fluid dynamics solver. This work used a combination of OpenFOAM v1912 and OpenFOAM 8 on desktop computers. OpenFOAM input files were generated using Python 3.7.

A list of structures (and other identifiers) of possible per- and polyfluoroalkyl substances (PFAS). The data provided in the PFAS Suspect List has been aggregated from public sources and users, including peer-reviewed literature, patent literature, and public websites. Therefore, the quality and accuracy of the compound names, structures, and other properties have not been validated. The National Institute of Standards & Technology does not endorse or provide any assessment of confidence with the information provided.

Round 5 Test DatasetThis is the test data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform text sentiment classification on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.