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Spatial Separation of Molecular Conformers and Clusters
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Design of radionuclide separations based on MD simulations.

I Giménez1, G Sormani2, A Rodríguez3

  • 1Departament d'Enginyeria química i química Analítica, Universitat de Barcelona, Marti i Franqués, 1-11, ES-08028, Barcelona, Spain.

Analytica Chimica Acta
|April 27, 2025
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Summary

Molecular dynamics (MD) simulations accelerate the development of selective materials for radionuclide separation. MD accurately predicts extractant-radionuclide affinity, reducing experimental trials for new separation resins.

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Nuclear Chemistry

Background:

  • Developing selective materials for radionuclide separation is time-consuming and expensive.
  • Traditional methods involve extensive chemical separations and optimization.
  • Molecular dynamics (MD) simulations offer a way to streamline this process.

Purpose of the Study:

  • To explore MD simulations for accelerating the identification of optimal separation conditions.
  • To predict extractant-radionuclide affinity, reducing experimental efforts.
  • To validate MD simulation predictions with experimental data.

Main Methods:

  • MD simulations were used to study the separation of Sr²⁺ and Pb²⁺ using 18-crown-6.
  • Various working media were investigated, including different acids and potassium thiocyanate.
  • Experimental validation involved measuring distribution weight ratios (Dw) with immobilized crown ether.

Main Results:

  • MD simulation predictions showed a strong correlation with experimental data.
  • Acetic acid was identified as a medium favoring stable Sr²⁺ complexation over Pb²⁺.
  • The effectiveness of MD simulations in predicting selectivity was confirmed.

Conclusions:

  • MD simulations are a reliable tool for predicting extractant selectivity in radionuclide separation.
  • This approach enables faster development of advanced materials for radionuclide separation.
  • MD simulations reduce the time and resources required for experimental optimization.