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    • pKa Data-driven Insights to Multiple Linear Regression Hydrolysis QSARs: Applicability to Perfluorinated Alkyl Esters

    Metadata Updated: August 4, 2025

    Limited data is available for physicochemical properties and environmental fate parameters of PFAS chemicals, which are widely distributed in the environment and highly persistent. This work assesses available models for estimation of hydrolysis rates and pKa values for their predictive performance for PFAS chemicals.

    This dataset is associated with the following publication: Lazare, J., C. Stevens, E. Weber, and L. Shields. p Ka Data-Driven Insights into Multiple Linear Regression Hydrolysis QSARs: Applicability to Perfluorinated Alkyl Esters. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 59(23): 11745-11755, (2025).

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    References

    https://doi.org/10.1021/acs.est.4c11596

    Dates

    Metadata Created Date August 4, 2025
    Metadata Updated Date August 4, 2025

    Metadata Source

    Harvested from EPA ScienceHub

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date August 4, 2025
    Metadata Updated Date August 4, 2025
    Publisher U.S. EPA Office of Research and Development (ORD)
    Maintainer
    Identifier https://doi.org/10.23719/1531665
    Data Last Modified 2025-05-16
    Public Access Level public
    Bureau Code 020:00
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Harvest Object Id 1bf925cd-5569-4fd2-898d-faf5691429df
    Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
    Harvest Source Title EPA ScienceHub
    License https://pasteur.epa.gov/license/sciencehub-license.html
    Program Code 020:000
    Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
    Related Documents https://doi.org/10.1021/acs.est.4c11596
    Source Datajson Identifier True
    Source Hash 81fb565ca11141ce2f013b12d6993f5e65bfcc1a7acdac133fe3220f0e76e207
    Source Schema Version 1.1

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