How the Double Internal Standard Method Revolutionized Chemical Analysis
Imagine needing to accurately measure a few drops of a specific substance in a huge swimming pool filled with various chemicals, where some drops might disappear without a trace during measurement while others might transform.
This is precisely the challenge scientists face in quantitative analysis of complex mixturesâfrom environmental pollution monitoring to pharmaceutical quality control. Russian scientists Igor Georgievich Zenkevich and Konstantin Mikhailovich Korolev proposed an ingenious solution to this problemâthe modified double internal standard method, which significantly improves the accuracy of chromatographic determinations 1 .
Measuring trace components in complex matrices with variable losses during sample preparation.
Using two internal standards to correct for analytical variables and improve accuracy.
Chromatography is a powerful analytical method that separates complex mixtures into individual components. The principle resembles a race where different molecules move through a special column filled with sorbent at different speeds. As a result, each molecule reaches the "finish line" (detector) at its own time, allowing identification and measurement.
However, the main challenge arises when transitioning from qualitative analysis ("what is this substance?") to quantitative ("how much of this substance exactly?"). Traditional quantification methods face problems:
Method | Accuracy | Loss Resistance | Complexity |
---|---|---|---|
External Standard | Low-Medium | Low | Low |
Standard Addition | Medium | Medium | Medium |
Single Internal Standard | High | Medium | Medium |
Double Internal Standard | Very High | High | High |
Table 1: Comparison of chromatographic quantitative analysis methods
The method proposed by Zenkevich and Korolev is based on introducing two internal standards into the analyzed sampleâsubstances similar in properties to the target analytes but absent in the original sample. These standards are homologs of the determined compoundsâsubstances from the same chemical class but with slightly different structures (e.g., differing in hydrocarbon chain length) 1 .
If two homologs behave similarly in all sample preparation stages, then by the difference between their behavior and the behavior of analytes, we can accurately calculate losses of the main determined substances and make appropriate corrections.
This approach resembles conducting a marathon with two pacemakers running at different speeds, allowing precise determination of each runner's capabilities regardless of external conditions.
Two internal standards added to the sample
Sample undergoes extraction and derivatization
Chromatographic separation and detection
Correction based on standard behavior
To demonstrate the method's capabilities, researchers prepared model samples by applying polar alkancarboxylic acids onto a polar sorbent Silipor 75. This model system simulated real complex matrices with pronounced sorption properties 1 .
Determined Acid | Added Amount, mg | Found Amount, mg | Relative Error, % |
---|---|---|---|
Acetic acid | 10.0 | 9.8 | -2.0 |
Propionic acid | 10.0 | 9.9 | -1.0 |
Butyric acid | 10.0 | 9.5 | -5.0 |
Valeric acid | 10.0 | 9.2 | -8.0 |
Table 2: Results of acid quantification using the double internal standard method
The research results showed that relative determination errors were only (-1)-(-8)%, significantly less than when using other quantification methods 1 . Importantly, accuracy remained high regardless of losses of components at all sample preparation stages.
The greatest error was observed for acids with higher molecular weight, related to their slightly different behavior in extraction and derivatization processes. However, even these errors remained within limits acceptable for most analytical tasks.
Every scientific method requires its own "toolkit." Here are the main "ingredients" researchers use when working with the double internal standard method:
Reagent/Material | Purpose | Features |
---|---|---|
Analyte homologs | Internal standards | Must be chemically similar to analytes but absent in the original sample |
Silipor 75 | Polar sorbent | Creates a model system with sorption properties |
Extraction solvents | Extracting analytes from matrix | Must effectively desorb substances without altering them |
Derivatization reagents | Converting analytes to derivatives | For gas chromatography, often create volatile derivatives (esters) |
Table 3: Key reagents and materials for the double internal standard method
High-purity homologs used as internal references for accurate quantification.
Advanced instrumentation for separation and detection of chemical compounds.
Tools and reagents for extracting, purifying, and derivatizing samples before analysis.
The double internal standard method finds applications across various fields of analytical chemistry:
Determination of pesticides, PAHs, and other pollutants in soil, water, and plant objects 1 .
Monitoring pharmaceutical drugs and their metabolites in biological fluids with high precision.
Quality control and authenticity verification of food products, detecting contaminants and additives.
Analysis of complex multicomponent drug formulations and quality assurance in manufacturing.
An important advantage of the method is its versatilityâit can be extended to any number of carbon atoms in standard molecules and applied even when homologs of determined analytes are already present in original samples 1 .
Despite impressive capabilities, the method has a single significant limitationâthe necessity for availability of comparison samples of target analytes 1 . In some cases, obtaining such standards can be challenging and expensive.
The work of Zenkevich and Korolev demonstrates that even in well-established scientific fields like chromatographic analysis, opportunities exist for significant improvement of accuracy and method reliability.
Their approach using the double internal standard represents an elegant solution to the complex problem of accounting for analyte losses at sample preparation stages. This method reminds us that sometimes the most effective solutions come not through complication but through cleverer use of already available tools and principles.