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Graph Theoretical Description of Phase Transitions in Complex Multiscale Phases with Supramolecular Assemblies.
Yang, Ruochen; Bernardino, Kalil; Xiao, Xiongye; Gomes, Weverson R; Mattoso, Davi A; Kotov, Nicholas A; Bogdan, Paul; de Moura, André F.
Afiliación
  • Yang R; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
  • Bernardino K; Center of Complex Particle Systems (COMPASS), Ann Arbor, MI, 48109-2102, USA.
  • Xiao X; Department of Chemistry, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil.
  • Gomes WR; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
  • Mattoso DA; Center of Complex Particle Systems (COMPASS), Ann Arbor, MI, 48109-2102, USA.
  • Kotov NA; Department of Chemistry, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil.
  • Bogdan P; Department of Chemistry, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil.
  • de Moura AF; Center of Complex Particle Systems (COMPASS), Ann Arbor, MI, 48109-2102, USA.
Adv Sci (Weinh) ; : e2402464, 2024 Jul 01.
Article en En | MEDLINE | ID: mdl-38952077
ABSTRACT
Phase transitions are typically quantified using order parameters, such as crystal lattice distances and radial distribution functions, which can identify subtle changes in crystalline materials or high-contrast phases with large structural differences. However, the identification of phases with high complexity, multiscale organization and of complex patterns during the structural fluctuations preceding phase transitions, which are essential for understanding the system pathways between phases, is challenging for those traditional analyses. Here, it is shown that for two model systems- thermotropic liquid crystals and a lyotropic water/surfactant mixtures-graph theoretical (GT) descriptors can successfully identify complex phases combining molecular and nanoscale levels of organization that are hard to characterize with traditional methodologies. Furthermore, the GT descriptors also reveal the pathways between the different phases. Specifically, centrality parameters and node-based fractal dimension quantify the system behavior preceding the transitions, capturing fluctuation-induced breakup of aggregates and their long-range cooperative interactions. GT parameterization can be generalized for a wide range of chemical systems and be instrumental for the growth mechanisms of complex nanostructures.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Sci (Weinh) Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania
Texto completo
Añadir a Mi BVS
Imprimir
XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Sci (Weinh) Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania