U.S. flag

An official website of the United States government

Dot gov

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Https

Secure .gov websites use HTTPS
A lock () or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Breadcrumb

  1. Home

Data for Intrinsic DAC calculations

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.

About this Dataset

Updated: 2025-04-06
Metadata Last Updated: 2024-12-13 00:00:00
Date Created: N/A
Data Provided by:
Dataset Owner: N/A

Access this data

Contact dataset owner Access URL
Landing Page URL
Table representation of structured data
Title Data for Intrinsic DAC calculations
Description 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.
Modified 2024-12-13 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords Direct Air Capture , Machine Learning , Thermodynamics , Solid Sorbents , MOFs
{
    "identifier": "ark:\/88434\/mds2-3687",
    "accessLevel": "public",
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Austin McDannald"
    },
    "programCode": [
        "006:045"
    ],
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-3687",
    "title": "Data for Intrinsic DAC calculations",
    "description": "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.",
    "language": [
        "en"
    ],
    "distribution": [
        {
            "accessURL": "https:\/\/doi.org\/10.5281\/zenodo.14452152",
            "description": "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.",
            "title": "Data for Intrinsic DAC calculations"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-3687\/README.txt",
            "mediaType": "text\/plain"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-3687\/README.txt.sha256",
            "mediaType": "text\/plain"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-3687\/DAC_data.tar.gz",
            "mediaType": "application\/gzip"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-3687\/DAC_data.tar.gz.sha256",
            "mediaType": "text\/plain"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-3687\/IntrinsicDACCycle-0.0.2.tar.gz",
            "mediaType": "application\/gzip"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-3687\/IntrinsicDACCycle-0.0.2.tar.gz.sha256",
            "mediaType": "text\/plain"
        }
    ],
    "bureauCode": [
        "006:55"
    ],
    "modified": "2024-12-13 00:00:00",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "theme": [
        "Materials:Modeling and computational material science"
    ],
    "keyword": [
        "Direct Air Capture",
        "Machine Learning",
        "Thermodynamics",
        "Solid Sorbents",
        "MOFs"
    ]
}