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Certified values of iodine in CRMs of food matrices in mg/kg units. The uncertainties are expanded uncertainties at approximately 95% confidence.
Data provided by National Institute of Standards and Technology
A comparison of the expanded uncertainty for certified values of iodine in food matrix CRMs. The CRMS were found by searching The European Virtual Institute for Speciation Analysis (EVISA) database using the terms "Iodine" and "Certified" in the Material category. The uncertainties are expanded uncertainties at approximately 95% confidence.
Tags: food,nutrition,dietary supplements,Standard Reference materials,reference materials,SRM,RM,Food and Nutrition,
Modified: 2024-02-22
Views: 0
JARVIS: Joint Automated Repository for Various Integrated Simulations
Data provided by National Institute of Standards and Technology
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.
Tags: Density functional theory,classical interatomic potential,force-field,python,JARVIS,MGI,MDCS,RESTAPI,automation,
Modified: 2024-02-22
Views: 0
FEASST: Free Energy and Advanced Sampling Simulation Toolkit
Data provided by National Institute of Standards and Technology
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.
Tags: monte carlo,molecular simulation,free energy,flat histogram,C++,python,
Modified: 2024-02-22
Views: 0
Source of the Refl1d program for modeling and analyzing neutron and X-ray reflectometry data, with the addition of distributed roughness capability.
Data provided by National Institute of Standards and Technology
Source of the Refl1d program for modeling and analyzing neutron and X-ray reflectometry data, with the addition of distributed roughness capability.
Tags: neutron scattering,reflectometry,polarized,Bayesian,roughness,python,
Modified: 2024-02-22
Views: 0
QFlow 2.0: Quantum dot data for machine learning
Data provided by National Institute of Standards and Technology
Using a modified Thomas-Fermi approximation, we model a reference semiconductor system comprising a quasi-1D nanowire with a series of five depletion gates whose voltages determine the number of quantum dots (QDs), the charges on each of the QDs, as well as the conductance through the wire. The original dataset, QFlow lite, consists of 1 001 idealized simulated measurements with gate configurations sampling over different realizations of the same type of device.
Tags: machine learning,quantum dots,simulated data,
Modified: 2024-02-22
Views: 0
pyPRISM: A Computational Tool for Liquid State Theory Calculations of Macromolecular Materials
Data provided by National Institute of Standards and Technology
Polymer Reference Interaction Site Model (PRISM) theory describes the equilibrium spatial-correlations of liquid-like polymer systems including melts, blends, solutions, block copolymers, ionomers, liquid crystal forming polymers and nanocomposites. Using PRISM theory, one can calculate thermodynamic (e.g., second virial coefficients, Flory-Huggins interaction parameters, potentials of mean force) and structural (eg., pair correlation functions, structure factors) information for these macromolecular materials.
Tags: polymer,theory,liquid-state theory,python,polymer nanocomposite,polymer solution,X-ray scattering,neutron scattering,software,tool,computation,
Modified: 2024-02-22
Views: 0
Nestor: a toolkit for quantifying tacit maintenance knowledge, for investigatory analysis in smart manufacturing
Data provided by National Institute of Standards and Technology
There is often a large amount of maintenance data already available for use in Smart Manufacturing systems, but in a currently-unusable form: service tickets and maintenance work orders (MWOs). Nestor is a toolkit for using Natural Language Processing (NLP) with efficient user-interaction to perform structured data extraction with minimal annotation time-cost.
Tags: information,communication,maintenance,tribal knowledge,event sequences,training,machine learning,data cleaning,prognostics,diagnostics,visualization,decision guidance,CMMS,scheduling,investigations,nestor,smart manufacturing,manufacturing operations,manufacturing performance,
Modified: 2024-02-22
Views: 0
pyLLE: a Fast and User Friendly Lugiato-Lefever Equation Solver
Data provided by National Institute of Standards and Technology
We present the development of pyLLE, a freely accessible Lugiato-Lefever equation solver programmed in Python and Julia and optimized for the simulation of microresonator frequency combs. Examples illustrating its operation and performance are presented.
Tags: photonics,optics,frequency combs,python,julia,
Modified: 2024-02-22
Views: 0
REMI: Resource for Materials Informatics
Data provided by National Institute of Standards and Technology
The REsource for Materials Informatics (REMI) will host a diverse collection of scripting notebooks (Jupyter, Matlab LiveScripts, etc.) for collecting, pre-processing, analyzing, and visualizing materials data. Notebooks are curated using tags aligned to Materials Science and Data Science topics. REMI emerged from the realization that both experts and novices wanted examples of using machine learning for science. Meanwhile, lots of experts are developing digital notebooks (e.g. Jupyter) to demonstrate step-by-step data collection, pre-processing, analysis and visualization.
Tags: machine learning,data analysis,data processing,materials science,materials genome initiative,
Modified: 2024-02-22
Views: 0
Dark solitons in BECs dataset 2.0
Data provided by National Institute of Standards and Technology
Atomic Bose-Einstein condensates (BECs) are widely investigated systems that exhibit quantum phenomena on a macroscopic scale. For example, they can be manipulated to contain solitonic excitations including conventional solitons, vortices, and many more. Broadly speaking, solitonic excitations are solitary waves that retain their size and shape and often propagate at a constant speed. They are present in many systems, at scales ranging from microscopic, to terrestrial and even astronomical.
Tags: machine learning,Bose-Einstein condensates,dark solitons,
Modified: 2024-02-22
Views: 0