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X-ray Fluorescence Spectroscopy Unstandardized Sample Quantitative Analysis Technique

Introduction to Unstandardized Sample Analysis Method

X-ray Fluorescence Spectroscopy (XRF) unstandardized sample analysis technique is a new technology introduced in the 1990s. Its purpose is to perform quantitative analysis on various samples without the need for calibrated samples.

Basic approach: The instrument manufacturer measures calibrated samples, stores intensity and calibration curve data, and then transfers this data to the user’s XRF analysis system. The instrument drift is corrected using reference samples provided with the software. Therefore, unstandardized sample analysis does not mean the absence of standard samples; rather, it shifts the calibration curve drawing work from the user to the instrument manufacturer, allowing users to correct count intensity differences between their instrument and the manufacturer’s instrument.

Advantages: It incorporates the manufacturer’s standards, experience, and knowledge, including measurement conditions, automatic spectral line identification, background subtraction, overlap correction, matrix correction, etc. It can analyze seventy-plus elements from B to U in various samples ranging from trace amounts to 100%. While its broad applicability is advantageous, it also imposes limitations on analysis accuracy, making unstandardized sample software also known as semi-quantitative software.

Historical Review of Unstandardized Sample Analysis Method
Development of Bruker (Siemens) Unstandardized Sample Analysis Software
  1. Birks on Siemens XRF, NRLXRF Basic Parameter Method Program
  2. 1989, SSQ Semi-Quantitative Analysis Software
  3. 1996, Spectra plus Unstandardized Sample Analysis Software
  4. 2006, QuantExpress Unstandardized Sample Quantitative Analysis Software
Characteristics of QuantExpress Unstandardized Sample Analysis Software
  1. Corrects matrix effects using changes in alpha coefficients based on Fundamental Parameters (FP)
  2. Open-source software that allows adjusting sensitivity factors for precise analysis of various sample types.
  3. Acquires spectral line signals using both scanning and fixed-point measurement modes, achieving detection limits in unstandardized sample analysis at the PPM level.
  4. Seamless integration of unstandardized sample analysis and calibration curve analysis methods
Basic Algorithm of Unstandardized Sample Analysis Method
Sensitivity Factors for Spectral Lines
  1. Sensitivity factor of a spectral line (cps/%) represents the relationship between the signal of a specific characteristic spectral line and the element content. Sensitivity factors can be obtained by measuring a pure elemental sample or calculating from measured standard net intensity, considering the enhanced absorption effect between elements.
  2. Sensitivity factors are sample-independent and determined solely by the measurement channel, also known as the “spectrometer sensitivity” for that spectral line.
Factors Affecting Sensitivity Factors
  1. Major influencing factor: Sample preparation. Software sensitivity factors are based on ideal sample preparation: uniform, without particle effects.
  2. Ideal sample preparation includes melting, non-segregating metals, and liquid samples.
  3. Granular samples should be finely ground as much as possible.
  4. In recent years, researchers have found significant differences in fluorescence yield and line fraction values for elements in different compounds.
  5. Solution: Re-calculate sensitivity factors using similar standard samples.
  6. QuantExpress software is open-source, allowing users to create unstandardized sample analysis spectral lines for specific samples.
Reliability of Measurement Signals (Scanning Mode or Fixed-Point Measurement Mode)

Why scanning mode is usually adopted: Chemical states can affect peak drift.

Issues with scanning measurements: Counting statistical errors.

  1. Precision of major element measurements in scanning mode is about 1%.
  2. Typical LLD (Lower Limit of Detection) for unstandardized sample analysis is 100 ppm.
  3. How to improve data quality in unstandardized sample analysis
  • Extend measurement time.
  • Combine fixed-point and scanning modes.

Combining fixed-point and scanning measurements in unstandardized sample analysis can achieve detection limits at the PPM level.

Combination of Unstandardized Sample Analysis Method and Quantitative Analysis Method

① Users can create “more accurate” unstandardized sample analysis spectral lines suitable for specific sample conditions and combine them with other generic unstandardized sample spectral lines. User’s unstandardized sample spectral lines + Generic unstandardized sample spectral lines

② Introduce unstandardized sample spectral lines into quantitative calibration curves. Suitable for cases lacking sufficient standard samples. Quantitative calibration curve + Unstandardized sample analysis method

A single analysis method can include: Unstandardized sample analysis method and quantitative analysis method.

Red Elements: Quantitative analysis calibration curves established using standard samples.
Green Elements: Unstandardized sample analysis spectral lines.

Estimation of Analysis Error in Unstandardized Sample Analysis Method
  1. Liquid and melt sample methods may yield results similar to conventional quantitative analysis when unknown elements that XRF cannot analyze are absent.
  2. For non-segregating metals with no apparent segregation, results similar to conventional quantitative analysis may be obtained.
  3. For samples with significant particle effects and mineral effects, errors in major element content may have a relative error of 10%.
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