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Vladislav A Blatov1,2,3, Andrey A Golov4,5, Changhao Yang6

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This study introduces a universal network model for solid-state transformations, enabling prediction of new material phases by analyzing chemical bond changes and topological rearrangements.

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Area of Science:

  • Solid-state chemistry and materials science.
  • Chemical physics and condensed matter physics.

Background:

  • Solid-state transformations involve significant changes in chemical bonds and substance topology.
  • Current modeling methods overlook topological transformations, limiting understanding and prediction of chemical reactions and phase transitions.
  • Atomic-level understanding is crucial for designing new materials.

Purpose of the Study:

  • To propose a universal model for solid-state transformations based on network representation.
  • To demonstrate that this network model can rationalize the configuration space of solid systems.
  • To enable the prediction of new material phases and clarify transition pathways.

Main Methods:

  • Developing a universal model using network representation for extended structures.
  • Treating solid-state reorganization as network transformations.
  • Applying the model to various systems including elementary substances, ionic compounds, and molecular crystals.

Main Results:

  • The proposed network model rationalizes the configuration space of solid systems.
  • The approach enables the prediction of new, related phases.
  • New phases and transition pathways were discovered in example systems.

Conclusions:

  • A universal network model provides a new perspective on solid-state transformations.
  • This approach enhances the predictive power for chemical reactions and phase transitions in solids.
  • The model facilitates the discovery of novel material phases and clarifies complex transition mechanisms.