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<p>Traditional complexing agents are highly effective but environmentally persistent, leading to a growing interest in biodegradable alternatives. However, many of these alternatives remain insufficiently characterised. In this study, capillary electrophoresis was employed to characterise four complexing agents: two conventional ligands, ethylenediaminetetraacetic acid and hydroxyethylidenediphosphonic acid, and two biodegradable substitutes, iminodisuccinic acid and ethylenediaminedisuccinic acid. The thermodynamic dissociation constants (p<i>K</i><sub>a</sub>) and limiting ionic mobilities were determined by measuring effective mobilities across a series of background electrolytes with varying pH and constant ionic strength. The resulting p<i>K</i><sub>a</sub>&#xa0;values and limiting mobilities were integrated into the PeakMaster software database to evaluate their predictive reliability. Computational simulations were validated against experimental separations using both indirect UV and contactless conductivity detection. Experiments utilising contactless conductivity detection at alkaline pH (8.4 and 8.6) showed higher consistency with the theoretical model.</p> Graphical abstract <p></p>

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Characterisation of complexing agents for the prediction of their separation in capillary electrophoresis

  • 期刊论文

  • 发表日期：

    2026年8月4日

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  • Renata Píplová,
  • Stephan Liebsch,
  • Tomáš Křížek

摘要

Traditional complexing agents are highly effective but environmentally persistent, leading to a growing interest in biodegradable alternatives. However, many of these alternatives remain insufficiently characterised. In this study, capillary electrophoresis was employed to characterise four complexing agents: two conventional ligands, ethylenediaminetetraacetic acid and hydroxyethylidenediphosphonic acid, and two biodegradable substitutes, iminodisuccinic acid and ethylenediaminedisuccinic acid. The thermodynamic dissociation constants (pKa) and limiting ionic mobilities were determined by measuring effective mobilities across a series of background electrolytes with varying pH and constant ionic strength. The resulting pKa values and limiting mobilities were integrated into the PeakMaster software database to evaluate their predictive reliability. Computational simulations were validated against experimental separations using both indirect UV and contactless conductivity detection. Experiments utilising contactless conductivity detection at alkaline pH (8.4 and 8.6) showed higher consistency with the theoretical model.

Graphical abstract