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Large Decrease in the Melting Point of Benzoquinones via High-n Eutectic Mixing Predicted by a Regular Solution

Antonio Baclig1, Devi Ganapathi1, Victoria Ng1

  • 1Department of Materials Science & Engineering, Stanford University, Stanford, California 94305, United States.

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|June 29, 2023
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Summary
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Mixing many components, even with neutral interactions, can significantly lower melting points by increasing entropy. This strategy is promising for developing advanced battery electrolytes and cryopreservatives.

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Area of Science:

  • Materials Science
  • Physical Chemistry
  • Electrochemistry

Background:

  • Decreasing mixture melting points (Tm) is crucial for applications like cryopreservation and battery electrolytes.
  • Current methods often rely on favorable enthalpic interactions (e.g., deep eutectic solvents).
  • A complementary strategy utilizing increased entropy of mixing is explored.

Purpose of the Study:

  • To demonstrate a novel method for decreasing melting points by increasing the number of components (n) and thus the entropy of mixing.
  • To investigate the potential of this approach for creating high energy density flow battery electrolytes using redox-active molecules.
  • To develop and apply thermodynamic models for predicting eutectic behavior in high-n mixtures.

Main Methods:

  • Reformulation and application of fundamental thermodynamic equations for high-n eutectic mixtures.
  • Differential scanning calorimetry (DSC) to measure melting points and enthalpies of mixing.
  • Systematic investigation of binary mixtures and a multi-component system of benzoquinone derivatives.

Main Results:

  • 1,4-benzoquinone derivatives exhibit eutectic mixing, decreasing Tm despite slightly positive enthalpies of mixing (0-5 kJ/mol).
  • A mixture of seven benzoquinone derivatives achieved a significant Tm decrease to -6 °C.
  • The regular solution model provided better predictions than the ideal solution model for these mixtures.

Conclusions:

  • Mixing a high number of components is an effective strategy to lower melting points by maximizing entropy, complementing enthalpy-driven approaches.
  • This entropy-tuning method is highly relevant for designing advanced energy storage materials.
  • Thermodynamic modeling, particularly the regular solution model, is valuable for predicting eutectic properties in complex organic mixtures.