Results of calculations and simulations for the Intrinsic Direct Air Capture analysis of Metal Organic Framwork (MOF) sorbents.Includes Grand Canonical Monte Carlo (GCMC) simulations, predictions of the Specific Heat Capacities (CV), and Intrinsic Direct Air Capture (DAC) calculations for MOF sorbents.

This data publication contains the raw, extracted, and derived (e.g., peak areas) mass spectrometry data for illicit drug and mixture samples. These samples were analyzed by wipe-based collection or solvent-extraction, thermal desorption, and a transportable high-resolution time-of-flight mass spectrometer. Data were collected with both an in-line dielectric barrier discharge ionization source and an acetone-dopoant assisted vacuum ultraviolet (VUV) photoionization source.

Supporting information for the NIST Internal Report entitled: Per- and Polyfluoroalkyl Substances - Non-Targeted Analysis Interlaboratory Study Final Report. The files include four comma-separated value (CSV) text files, three of the CSV text files contain summary tables of all per and polyfluoroalkyl substances (PFAS) detected in the three test samples from the interlaboratory report (sample_a_table.csv, sample_b_table.csv, sample_c_table.csv) including the individual laboratory reported identities and their associated identification confidence levels.

The National Institute of Standards and Technology and the International Centre for Diffraction Data co-hosted a workshop on 17-18 October 2023 to identify and prioritize the goals, challenges, and opportunities for critical and emerging technology needs within industry, with an emphasis on leveraging artificial intelligence, data-driven methodologies, and high-throughput and automated workflows for accelerating x-ray-based structural analysis for materials development and manufacturing.

A table of known interferences for per- and polyfluoroalkyl substances using mass spectrometry.

Data here contain and describe an open-source structured query language (SQLite) portable database containing high resolution mass spectrometry data (MS1 and MS2) for per- and polyfluorinated alykl substances (PFAS) and associated metadata regarding their measurement techniques, quality assurance metrics, and the samples from which they were produced. These data are stored in a format adhering to the Database Infrastructure for Mass Spectrometry (DIMSpec) project. That project produces and uses databases like this one, providing a complete toolkit for non-targeted analysis.

Synthetic training and test datasets for experiments on deep generative modeling of noise time series. Consists of data for the following noise types: 1) band-limited thermal noise, i.e., bandpass filtered white Gaussian noise, 2) power law noise, including fractional Gaussian noise (FGN), fractional Brownian motion (FBM), and fractionally differenced white noise (FDWN), 3) generalized shot noise, 4) impulsive noise, including Bernoulli-Gaussian (BG) and symmetric alpha stable (SAS) distributions.

This data publication contains the mass spectrometry chemical characterization of microplastic and nanoplastic chemical analysis. The data from this study includes mass spectra of pure, mixed, and weathered microplastics and nanoplastics at high and low fragmentation, extracted ion chronograms, Kendrick mass defect plots, code, and the derived and processed data. The data analysis code (MATLAB 2022a*) used for unsupervised learning of cluster and compositional relationships is also included.

This module for ns-3 implements the classes required to model a network architecture based on the O-RAN Alliance's specifications. These models include a Radio Access Network (RAN) Intelligent Controller (RIC) that is functionally equivalent to O-RAN's Near-Real Time (Near-RT) RIC, and reporting modules that attach to simulation nodes and serve as communication endpoints with the RIC in a similar fashion as the E2 Terminators in O-RAN.

Our work towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) aims to provide plots, tools, methods, and strategies to extract insights out of various machine learning (ML) and Artificial Intelligence (AI) data.Included in this software is the MIg analyZeR (mizr) R software package that produces various plots.