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Selectivity and Related Measures for nth-Order Data
N J Messick1, J H Kalivas, P M Lang
1Department of Chemistry, Idaho State University, Pocatello, Idaho 83209.
Analytical Chemistry
|May 31, 2011
Summary
This study introduces new mathematical tools to create figures of merit for nth-order analytical instruments. These tools enable better assessment of selectivity, net analyte signal, and sensitivity for complex analytical data.
Area of Science:
- Analytical Chemistry
- Chemometrics
- Instrumental Analysis
Background:
- Figures of merit are crucial for evaluating analytical instrument suitability.
- Existing figures of merit are limited to first-order instruments and data.
- A gap exists in evaluating higher-order (second-order and nth-order) instruments and data.
Purpose of the Study:
- To develop practical mathematical tools for creating figures of merit for nth-order instrumentation.
- To define and develop measures for selectivity, net analyte signal, and sensitivity for nth-order data.
- To address the lack of established figures of merit for complex analytical data.
Main Methods:
- Development of mathematical tools for nth-order figures of merit.
- Focus on a local selectivity measure for second-order instrumentation.
- Validation using simulated and real second-order data from GC-FTIR and LC-PDA.
Main Results:
- Successful development of practical mathematical tools for nth-order figures of merit.
- Demonstration of a local selectivity measure for second-order data.
- Validation of the proposed measures using chromatographic and spectroscopic data.
Conclusions:
- The developed mathematical tools provide practical means to establish figures of merit for nth-order instruments.
- These new measures enhance the evaluation of analytical methods dealing with complex, multi-variable data.
- The study lays the groundwork for broader application of higher-order figures of merit in analytical science.
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