{"title":"聚合物网络中空间和拓扑缺陷的相互作用","authors":"B. Ruşen Argun, and , Antonia Statt*, ","doi":"10.1021/acsengineeringau.3c00072","DOIUrl":null,"url":null,"abstract":"<p >Polymer networks are widely used in applications, and the formation of a network and its gel point can be predicted. However, the effects of spatial and topological heterogeneity on the resulting network structure and ultimately the mechanical properties, are less understood. To address this challenge, we generate in silico random networks of cross-linked polymer chains with controlled spatial and topological defects. While all fully reacted networks investigated in this study have the same number of end-functionalized polymer strands and cross-linkers, we vary the degree of spatial and topological heterogeneities systematically. We find that spatially heterogeneous cross-linker distributions result in a reduction in the network’s primary loops with increased spatial heterogeneity, the opposite trend as observed in homogeneous networks. By performing molecular dynamics simulations, we investigated the mechanical properties of the networks. Even though spatially heterogeneous networks have more elastically active strands and cross-linkers, they break at lower extensions than the homogeneous networks and sustain slightly lower maximum stresses. Their shear moduli are higher, i.e., stiffer, than theoretically predicted, and higher than their homogeneous gel counterparts. Our results highlight that topological loop defects and spatial heterogeneities result in significantly different network structures and, ultimately, different mechanical properties.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"351–358"},"PeriodicalIF":4.3000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00072","citationCount":"0","resultStr":"{\"title\":\"Interplay of Spatial and Topological Defects in Polymer Networks\",\"authors\":\"B. Ruşen Argun, and , Antonia Statt*, \",\"doi\":\"10.1021/acsengineeringau.3c00072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Polymer networks are widely used in applications, and the formation of a network and its gel point can be predicted. However, the effects of spatial and topological heterogeneity on the resulting network structure and ultimately the mechanical properties, are less understood. To address this challenge, we generate in silico random networks of cross-linked polymer chains with controlled spatial and topological defects. While all fully reacted networks investigated in this study have the same number of end-functionalized polymer strands and cross-linkers, we vary the degree of spatial and topological heterogeneities systematically. We find that spatially heterogeneous cross-linker distributions result in a reduction in the network’s primary loops with increased spatial heterogeneity, the opposite trend as observed in homogeneous networks. By performing molecular dynamics simulations, we investigated the mechanical properties of the networks. Even though spatially heterogeneous networks have more elastically active strands and cross-linkers, they break at lower extensions than the homogeneous networks and sustain slightly lower maximum stresses. Their shear moduli are higher, i.e., stiffer, than theoretically predicted, and higher than their homogeneous gel counterparts. Our results highlight that topological loop defects and spatial heterogeneities result in significantly different network structures and, ultimately, different mechanical properties.</p>\",\"PeriodicalId\":29804,\"journal\":{\"name\":\"ACS Engineering Au\",\"volume\":\"4 3\",\"pages\":\"351–358\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-02-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00072\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Engineering Au\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acsengineeringau.3c00072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Engineering Au","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsengineeringau.3c00072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Interplay of Spatial and Topological Defects in Polymer Networks
Polymer networks are widely used in applications, and the formation of a network and its gel point can be predicted. However, the effects of spatial and topological heterogeneity on the resulting network structure and ultimately the mechanical properties, are less understood. To address this challenge, we generate in silico random networks of cross-linked polymer chains with controlled spatial and topological defects. While all fully reacted networks investigated in this study have the same number of end-functionalized polymer strands and cross-linkers, we vary the degree of spatial and topological heterogeneities systematically. We find that spatially heterogeneous cross-linker distributions result in a reduction in the network’s primary loops with increased spatial heterogeneity, the opposite trend as observed in homogeneous networks. By performing molecular dynamics simulations, we investigated the mechanical properties of the networks. Even though spatially heterogeneous networks have more elastically active strands and cross-linkers, they break at lower extensions than the homogeneous networks and sustain slightly lower maximum stresses. Their shear moduli are higher, i.e., stiffer, than theoretically predicted, and higher than their homogeneous gel counterparts. Our results highlight that topological loop defects and spatial heterogeneities result in significantly different network structures and, ultimately, different mechanical properties.
期刊介绍:
)ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)