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Related Experiment Videos

Skin protection, Viton, and solubility parameters.

J L Perkins, M C Ridge, A B Holcombe

    American Industrial Hygiene Association Journal
    |December 1, 1986
    PubMed
    Summary

    This study calculates the three-dimensional solubility parameter (3-DSP) for Viton polymer. While not fully quantitative, 3-DSP aids in qualitatively predicting solvent permeation through polymers.

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    Area of Science:

    • Materials Science
    • Polymer Chemistry
    • Physical Chemistry

    Background:

    • Permeation of solvents through polymers is governed by diffusion and solubility.
    • The three-dimensional solubility parameter (3-DSP) is a physical-chemical constant used to predict solubility.
    • Accurate prediction of permeation is crucial for material selection in various applications.

    Purpose of the Study:

    • To calculate the 3-DSP for the polymer Viton.
    • To generate new permeation data for Viton with 14 different solvents.
    • To apply the 3-DSP model for predicting permeation parameters in polymer-solvent systems.

    Main Methods:

    • Calculation of the three-dimensional solubility parameter (3-DSP) for Viton.
    • Experimental determination of permeation data for Viton against 14 solvents.
    • Regression analysis correlating 3-DSP differences with permeation metrics (breakthrough time, permeation rate).

    Main Results:

    • The 3-DSP values for Viton were determined: dispersion = 17.0, polar = 10.6, and hydrogen bonding = 6.1 (J/cc)1/2.
    • Correlation coefficients of 0.65 and 0.69 were achieved for regressions involving breakthrough time and permeation rate, respectively.
    • Significant variance in regression analyses indicates limitations for precise quantitative prediction.

    Conclusions:

    • The three-dimensional solubility parameter (3-DSP) provides a basis for qualitative prediction of polymer suitability for specific solvents.
    • While quantitative prediction of permeation parameters is limited, the 3-DSP model offers valuable insights into polymer-solvent interactions.
    • Further refinement of the model may enhance its predictive capabilities for material science applications.

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