M-BLANK: a program for the fitting of X-ray fluorescence spectra

Area of Science:

• Elemental analysis
• X-ray fluorescence microscopy
• Biophysical techniques

Background:

• X-ray fluorescence (XRF) microscopy is crucial for elemental mapping.
• Accurate elemental quantitation requires precise data fitting.
• Current fitting methods often involve per-pixel baseline removal.

Purpose of the Study:

• To evaluate the impact of per-pixel baseline removal on XRF data quantitation.
• To propose an improved method for baseline correction in XRF analysis.
• To demonstrate the effectiveness of the proposed method using biological samples.

Main Methods:

• Acquisition of X-ray fluorescence data from yeast and glial cells using X-ray microprobe and nanoprobe.
• Application of per-pixel baseline removal in data fitting.
• Development and application of an average blank spectrum subtraction method.
• Comparative analysis of quantitation results from both methods.

Main Results:

• Per-pixel baseline removal introduces significant, systematic errors in elemental quantitation.
• The average blank spectrum subtraction method yields substantially improved data accuracy.
• Quantitation of elemental maps in biological samples (yeast, glial cells) is more reliable with the proposed method.

Conclusions:

• Per-pixel baseline correction is an inadequate method for XRF data analysis.
• Average blank spectrum subtraction offers a more robust approach for accurate elemental mapping.
• This improved method enhances the reliability of quantitative elemental analysis in biological and potentially other research areas.