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A BASIC-language program for dedicated energy-dispersive microanalysis of thin samples in TEM or STEM.

J C Russ

    Microscopica Acta. Supplement
    |January 1, 1978
    PubMed
    Summary
    This summary is machine-generated.

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    The QTHIN program aids in analyzing energy-dispersive X-ray spectra for elemental concentrations in thin samples. It handles complex data, including peak overlaps and absorption effects, for Transmission Electron Microscopy (TEM) and Scanning Transmission Electron Microscopy (STEM).

    Area of Science:

    • Materials Science
    • Analytical Chemistry
    • Microscopy

    Background:

    • Accurate elemental concentration determination is crucial in microanalysis.
    • Traditional methods struggle with complex samples and varying sample thicknesses.
    • Energy-dispersive X-ray spectroscopy (EDS) is a common microanalytical technique.

    Purpose of the Study:

    • To introduce QTHIN, a software program designed for processing energy-dispersive X-ray spectra.
    • To provide a robust method for computing elemental concentrations in thin and moderately thick samples.
    • To offer a flexible tool adaptable to various analytical needs and sample matrices.

    Main Methods:

    • QTHIN integrates established methods for energy-dispersive X-ray spectral processing.
    • It computes elemental concentrations, accounting for peak overlaps and absorption effects.

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  • The program is written in BASIC for user modification and adaptability.

    • Main Results:

    • QTHIN is suitable for routine analysis of complex samples with spectral peak overlaps.
    • The program effectively handles "not-so-thin" samples where absorption is significant.
    • It provides reliable concentration data for microanalysis in TEM and STEM.

    Conclusions:

    • QTHIN offers a versatile and effective solution for quantitative elemental analysis in electron microscopy.
    • The program's adaptability in BASIC allows for customization for diverse microanalysis applications.
    • It addresses limitations of previous methods, improving accuracy for a wider range of sample types.