SEDCORR is an open-source Python module designed to correct for the systematic energy deficits in atom probe mass spectra of electrically insulating samples. The assumption of the algorithm is that the mass spectrum for a dataset is conserved throughout the dataset and that any changes to the peak positions arise from an unknown slowly-fluctuating accelerating voltage. For computational speed, the unknown accelerating voltage is determined using a template matching FFT-based cross correlation method.

This report describes the test equipment, process, analysis, and data file formats for the Numisheet 2020 tensile and tension/compression testing of the four materials associated with the Numisheet 2020 conference benchmarks. The four materials include two steel alloys, DP980 for Benchmark 1 and DP1180 for Benchmark 2, and two 6000 series aluminum alloys, AA6xxx-T4 for Benchmark 1 and AA6xxx-T81 for Benchmark 2, that will be referred to here as BM1-DP980, BM2-DP1180, BM1-6xxx-T4, and BM2-6xxx-T81, respectively.

SCATMECH is a library of object-oriented C++ computer codes originally developed for disseminating models for polarized light scattering from surfaces and aerosols and for diffraction from gratings. The pySCATMECH package has been developed as an interface to the SCATMECH library, simplifying use of the codes and allowing for more rapid development of software for these applications.

Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model - analogous to a fitting function - Bayesian inference uses each measurement 'data point' to refine model parameters. Using this information, the software suggests measurement settings that are likely to efficiently reduce uncertainties. A TCP socket interface allows the software to be used from experimental control software written in other programming languages.

This Standard Reference Material (SRM) is in the form of chips sized between 0.50 and 1.18 mm sieve openings (35 and 16 mesh). It is intended for use primarily in chemical methods of analysis. Similar material for use in spectrometric methods of analysis is available as SRM 1297. This data is public in the Certificate of Analysis for this material.

Between 1922 and 1940, the National Bureau of Standards (NBS) conducted a long-term investigation into the corrosion of bare steel and iron, pipes buried underground at 47 sites representing different soil types in the United States. Following the passage of the 2004 Pipeline Safety Improvement Act, the Department of Transportation's Office of Pipeline Safety requested that NIST review and reanalyze the data from the NBS study using modern statistical analysis tools. For this analysis, NIST compiled an updated database from the data in the publications by K. H. Logan (i.e.

The National Institute of Standards and Technology, as part of its report on the collapse of the World Trade Center, characterized many important steels recovered from the buildings to provide stress-strain models to analyze the impact, fires, and resulting collapse. Those tests represent a large additional data set that can be used for modeling the response of steel structures to fire.

JARVIS (Joint Automated Repository for Various Integrated Simulations) is a repository designed to automate materials discovery using classical force-field, density functional theory, machine learning calculations and experiments.

The Force-field section of JARVIS (JARVIS-FF) consists of thousands of automated LAMMPS based force-field calculations on DFT geometries. Some of the properties included in JARVIS-FF are energetics, elastic constants, surface energies, defect formations energies and phonon frequencies of materials.

The Free Energy and Advanced Sampling Simulation Toolkit (FEASST) is a free, open-source, modular program to conduct molecular and particle-based simulations with flat-histogram Monte Carlo and molecular dynamics methods. It is a software written in C++ and python which is made publicly available to aid in reproducibility. It is also provided as a service to the scientific community in which there are few , if any, Monte Carlo programs that support flat histogram methods and advanced sampling algorithms. This software is expected to be updated frequently with new methods.

Source of the Refl1d program for modeling and analyzing neutron and X-ray reflectometry data, with the addition of distributed roughness capability.