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A Synthetic Methodology for Preparing Impregnated and Grafted Amine-Based Silica-Composites for Carbon Capture
Data provided by National Institute of Standards and Technology
The database includes thermal data analysis for silica-composites that conclude the loading amount of amine adsorbents of each composite as well as each specimen's ability to adsorb CO2. The data repository includes raw data files for: thermogravimetric analysis (TGA) weight loss and CO2 adsorption traces, and Fourier Transform Infrared Spectroscopy (FTIR) spectra?s. For more information see the readme and data documentation. A complete manuscript describing data collection, analysis, and database documentation is to be published. File formats for data include: .txt and .csv.
Tags: FTIR,thermal analysis,DSC,TGA,optical microscopy,Advanced Materials,direct air capture materials,
Modified: 2024-02-22
Views: 0
Per- and polyfluoroalkyl substances (PFAS) Interferents List
Data provided by National Institute of Standards and Technology
A table of known interferences for per- and polyfluoroalkyl substances using mass spectrometry.
Tags: per- and polyfluoroalkyl substances,PFAS,mass spectrometry,analytical chemistry,high-resolution mass spectrometry,HRMS,LC-MS/MS,
Modified: 2024-02-22
Views: 0
Database Infrastructure for Mass Spectrometry - Per- and Polyfluoroalkyl Substances
Data provided by National Institute of Standards and Technology
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.
Tags: per- and polyfluoroalkyl substances,PFAS,database,mass spectrometry,SQLite,emerging contaminants,high resolution mass spectrometry,non-targeted analysis,NTA,HRMS,
Modified: 2024-02-22
Views: 0
Noise Datasets for Evaluating Deep Generative Models
Data provided by National Institute of Standards and Technology
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.
Tags: generative adversarial network,machine learning,time series,band-limited noise,power law noise,shot noise,impulsive noise,colored noise,fractional Gaussian noise,fractional Brownian motion,
Modified: 2024-02-22
Views: 0
4D-STEM characterization results from a thermal annealing series of poly(3[2-(2-methoxyethoxy)ethoxy]-methylthiophene-2,5-diyl) organic electrochemical transistor films
Data provided by National Institute of Standards and Technology
This repository contains two types of datasets: 4D-STEM data collected from a thermal annealing series of P3MEEMT films. 4D-STEM data:Dose series: Collected from P3MEEMT film annealed at 115 C. Each HDF5 file was generated from the raw data using the fpdpy software package to reshape and embed metadata. No other preprocessing was performed. Annealing series: Collected from P3MEEMT films annealed at 75 C, 115 C, 145 C, and 175 C. Each temperature contains two sets of 4D-STEM data collected at low and high magnification.
Tags: Advanced Materials,Organic Semiconductors,4D-STEM,OECT,TEM,GIWAXS,
Modified: 2024-02-22
Views: 0
Microplastic and nanoplastic chemical characterization by thermal desorption and pyrolysis mass spectrometry with unsupervised machine learning
Data provided by National Institute of Standards and Technology
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.
Tags: Microplastic,Nanoplastics,environment,mass spectrometry,GC-MS,Chemical Characterization,machine learning,
Modified: 2024-02-22
Views: 0
ns-3 ORAN Module
Data provided by National Institute of Standards and Technology
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.
Tags: Artificial Intelligence,machine learning,Open RAN,RAN Intelligent Controller,
Modified: 2024-02-22
Views: 0
Towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) MIg analyZeR (mizr) Package
Data provided by National Institute of Standards and Technology
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.
Tags: analysis software,Artificial Intelligence,machine learning,design of experiments,
Modified: 2024-02-22
Views: 0
A Data-Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U-nets and Generative Adversarial Networks
Data provided by National Institute of Standards and Technology
Digital light processing (DLP) vat photopolymerization (VP) additive manufacturing (AM) uses patterned UV light to selectively cure a liquid photopolymer into a solid layer. Subsequent layers are printed on to preceding layers to eventually form a desired 3 dimensional (3D) part. This data set characterizes the 3D geometry of a single layer of voxels (volume pixels) printed with photomasks assigned random intensity levels at every pixel. The masks are computer generated, then printed onto a glass cover slide.
Tags: 3D printing,additive manufacturing,machine learning,generative adversarial network,Photopolymer,
Modified: 2024-02-22
Views: 0
FCpy: Feldman-Cousins Confidence Interval Calculator
Data provided by National Institute of Standards and Technology
Python scripts and Python+Qt graphical user interface for calculating Feldman-Cousins confidence intervals for low-count Poisson processes in the presence of a known background and for Gaussian processes with a physical lower limit of 0.
Tags: python,SIMS,statistics,mass spectrometry,Confidence Interval,CI,Feldman,Cousins,Poisson,Gaussian,
Modified: 2024-02-22
Views: 0