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Phase classification using neural networks: application to supercooled, polymorphic core-softened mixtures.

V F Hernandes1, M S Marques2, José Rafael Bordin3

  • 1Programa de Pós-Graduação em Física, Departamento de Física, Instituto de Física e Matemática, Universidade Federal de Pelotas, Caixa Postal 354, 96001-970, Pelotas-RS, Brazil.

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A neural network effectively predicted solid, fluid, and amorphous phases in soft matter systems. This approach aids in understanding polymorphic fluid behavior and the impact of solutes on phase transitions.

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Area of Science:

  • Physical Chemistry
  • Soft Matter Physics
  • Computational Chemistry

Background:

  • Characterizing phases in soft matter systems, especially polymorphic fluids like water, presents significant challenges.
  • Polymorphic fluids can exhibit multiple liquid and glassy phases, and a liquid-liquid critical point.
  • Understanding these complex phase behaviors is crucial for various physical chemical problems.

Purpose of the Study:

  • To apply a neural network algorithm to analyze the phase behavior of core-softened fluids.
  • To investigate mixtures of continuous-shouldered well (CSW) fluids and core-softened alcohols.
  • To enhance methods for studying phase transitions in complex fluid mixtures.

Main Methods:

  • Utilized a neural network algorithm for phase behavior analysis.
  • Applied and expanded bond-orientational order parameter methods to mixtures.
  • Incorporated longer-range coordination shells into the analysis.

Main Results:

  • The trained neural network accurately predicted crystalline solid, fluid, and amorphous phases for pure CSW and CSW-alcohol mixtures.
  • Achieved high efficiency in phase prediction.
  • Phase population information helped distinguish continuous from discontinuous phase transitions.

Conclusions:

  • The neural network approach successfully characterizes phase behavior in complex soft matter systems.
  • Findings provide insights into the spread of metastable amorphous regions within stable fluid phases.
  • This work advances the understanding of supercooled polymorphic fluids and solute effects on phase behavior.