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Thermo Fisher introduces semi-quantification analysis for ICP-OES

To simplify inductively coupled plasma – optical emission spectroscopy (ICP-OES), Thermo Fisher Scientific has introduced a semi-quantitative analysis tool that allows for the identification of unknown samples, to help make the world a cleaner and safer place. With the new SemiQuant feature on the Thermo Scientific™ Qtegra™ Intelligent Scientific Data Solution (ISDS) Software and the Thermo Scientific™ iCAP™ PRO Series ICP-OES, researchers can leverage Artificial Intelligence (AI) technology and neural networks to provide an efficient workflow for composition analysis.

The semi-quantitative approach involves determining the relative concentrations of elements in a sample rather than obtaining precise quantitative measurement. It is often used for rapid screening of samples or for identifying elemental composition trends rather than obtaining exact concentrations.

The semi-quantification implementation within the Qtegra ISDS Software does not require the user to analyze any standards or blanks prior to conducting the semi-quantification analysis. This approach makes use of AI and neural networks to provide an efficient workflow for non-targeted elemental screening using ICP-OES.

Key applications:

  • Laboratories who perform trace elemental analysis (metals and elements) using ICP-OES
  • Screening of food samples for unregulated elements


  • Smarter workflows: requires no standard analysis and uses AI technology and neural networks to provide an efficient workflow.
  • Rapid insights: leveraging the advantages of SemiQuant during method development streamlines the optimization process, improves method performance, and enhances the quality of analytical results. All SemiQuant results are obtained without the need to run any calibration solutions.
  • Versatile analysis from preliminary screening to sample prep and performance assessment:
    • Helps identify the presence of major and minor elements in samples, providing insights into the scope of the method and potential interferences.
    • Assesses the effectiveness of various sample preparation techniques, allowing users to optimize sample preparation protocols for subsequent quantitative analysis.
    • Provides an initial assessment of method performance and allows users to evaluate the robustness and reliability of the method.
    • Detects elements that can cause interferences on wavelength selected for quantitative analysis.

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