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From Linear to Nets: Multiconfiguration Polymer Structure Generation with PolyFlin.
Umar, Abd Kakhar; Limpikirati, Patanachai K; Luckanagul, Jittima Amie.
Afiliación
  • Umar AK; Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand.
  • Limpikirati PK; Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang 45363, Indonesia.
  • Luckanagul JA; Medical Informatics Laboratory, ETFLIN, Palu 94225, Indonesia.
J Chem Inf Model ; 63(21): 6717-6726, 2023 11 13.
Article en En | MEDLINE | ID: mdl-37851376
Molecular modeling and simulations are essential tools in polymer science and engineering, enabling researchers to predict and understand the properties of macromolecules, including their structure, dynamics, thermodynamics, and overall material characteristics. However, one of the key challenges in polymer simulation and modeling lies in the initial topology design, as existing programs often lack the capability to generate all types of polymer forms. In this study, we present PolyFlin, a powerful Python module that addresses this limitation by allowing the generation of a wide range of polymer structures, from simple homopolymers to complex copolymers, including grafts, cyclic, star, dendrimers, and nets. PolyFlin offers a versatile and efficient tool for exploring and creating diverse polymer architectures, facilitating advancements in various fields that require precise polymer modeling and simulation.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Polímeros Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Tailandia Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Polímeros Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Tailandia Pais de publicación: Estados Unidos