{"title":"计算线性聚合物集合中纠缠的算法","authors":"Pramod Kumar Patel, Sumit Basu","doi":"10.1002/mats.202400035","DOIUrl":null,"url":null,"abstract":"<p>The entanglement length plays a key role in deciding many important properties of thermoplastics. A number of computational techniques exist for the determination of entanglement length. In Ahmad et al.,<sup>[1]</sup> a method is proposed that treats a macromolecular chain as a 1D open curve and identifies entanglements by computing the linking number between two such interacting curves. If the curves wind around each other, a topological entanglement is detected. However, the entanglement length that is measured in experiments is assumed to be between rheological entanglements, which are clusters of such topological entanglements that collectively anchor the interacting chains strongly. In this article, the method of clustering topological entanglements into rheological ones is further elaborated and the robustness of the method is assessed. It is shown that this method estimates an entanglement length that depends on the forcefield chosen and is reasonably constant for chain lengths longer than the entanglement length. For shorter chain lengths, the method returns an infinite value of entanglement length indicating that the sample is unentangled. Moreover, in spite of using a geometry-based algorithm for clustering topological entanglements, the estimated entanglement length retains known empirical connections with physical attributes associated with the ensemble.</p>","PeriodicalId":18157,"journal":{"name":"Macromolecular Theory and Simulations","volume":"33 6","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Algorithm for Computing Entanglements in an Ensemble of Linear Polymers\",\"authors\":\"Pramod Kumar Patel, Sumit Basu\",\"doi\":\"10.1002/mats.202400035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The entanglement length plays a key role in deciding many important properties of thermoplastics. A number of computational techniques exist for the determination of entanglement length. In Ahmad et al.,<sup>[1]</sup> a method is proposed that treats a macromolecular chain as a 1D open curve and identifies entanglements by computing the linking number between two such interacting curves. If the curves wind around each other, a topological entanglement is detected. However, the entanglement length that is measured in experiments is assumed to be between rheological entanglements, which are clusters of such topological entanglements that collectively anchor the interacting chains strongly. In this article, the method of clustering topological entanglements into rheological ones is further elaborated and the robustness of the method is assessed. It is shown that this method estimates an entanglement length that depends on the forcefield chosen and is reasonably constant for chain lengths longer than the entanglement length. For shorter chain lengths, the method returns an infinite value of entanglement length indicating that the sample is unentangled. Moreover, in spite of using a geometry-based algorithm for clustering topological entanglements, the estimated entanglement length retains known empirical connections with physical attributes associated with the ensemble.</p>\",\"PeriodicalId\":18157,\"journal\":{\"name\":\"Macromolecular Theory and Simulations\",\"volume\":\"33 6\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Macromolecular Theory and Simulations\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/mats.202400035\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"POLYMER SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Macromolecular Theory and Simulations","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mats.202400035","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"POLYMER SCIENCE","Score":null,"Total":0}
An Algorithm for Computing Entanglements in an Ensemble of Linear Polymers
The entanglement length plays a key role in deciding many important properties of thermoplastics. A number of computational techniques exist for the determination of entanglement length. In Ahmad et al.,[1] a method is proposed that treats a macromolecular chain as a 1D open curve and identifies entanglements by computing the linking number between two such interacting curves. If the curves wind around each other, a topological entanglement is detected. However, the entanglement length that is measured in experiments is assumed to be between rheological entanglements, which are clusters of such topological entanglements that collectively anchor the interacting chains strongly. In this article, the method of clustering topological entanglements into rheological ones is further elaborated and the robustness of the method is assessed. It is shown that this method estimates an entanglement length that depends on the forcefield chosen and is reasonably constant for chain lengths longer than the entanglement length. For shorter chain lengths, the method returns an infinite value of entanglement length indicating that the sample is unentangled. Moreover, in spite of using a geometry-based algorithm for clustering topological entanglements, the estimated entanglement length retains known empirical connections with physical attributes associated with the ensemble.
期刊介绍:
Macromolecular Theory and Simulations is the only high-quality polymer science journal dedicated exclusively to theory and simulations, covering all aspects from macromolecular theory to advanced computer simulation techniques.