Yoshi W. Marien, Maofan Zhou, Mariya Edeleva, Dagmar R. D'hooge
{"title":"升级事件驱动蒙特卡洛模拟,实现基于分子的形态控制,用于电池和传感器应用","authors":"Yoshi W. Marien, Maofan Zhou, Mariya Edeleva, Dagmar R. D'hooge","doi":"10.1002/appl.202400048","DOIUrl":null,"url":null,"abstract":"<p>Multiphase polymeric materials and applications play a prominent role in our society. One of the key challenges is the design and modification of their macromolecules so that the composition and structuring of the phases as well as the interactions between them can be controlled from the molecular scale onwards. In the present contribution, it is highlighted that more recently developed event driven (kinetic) Monte Carlo models provide an interesting framework to grasp molecular variations over various length scales. The strength lies in the tracking of individual molecules per phase of interest so that interphase transfer events can be sampled based on the distributed nature of the (macro)molecules present. Hence, the micro-scale of local concentrations and temperatures can be connected to the meso-scale defining interphase transport and morphological variations, with an additional connection to the macro- or application scale within reach by adding macro-scale transfer events to the overall sampling scheme. Starting from a benchmark coupled matrix based Monte Carlo (CMMC) study on the multiphase formation of engineering composites which explicitly acknowledges the type of (macro)molecules present in each phase, it is showcased that the CMMC framework can support the general field of energy and electronics applications. This is highlighted through (i) a case study devoted to the design of polymer electrolytes for batteries, and (ii) a case study on blend design for the regulated stretching of piezoresistive sensors.</p>","PeriodicalId":100109,"journal":{"name":"Applied Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/appl.202400048","citationCount":"0","resultStr":"{\"title\":\"Upgrading event driven Monte Carlo simulations for molecule-based morphological control for battery and sensor applications\",\"authors\":\"Yoshi W. Marien, Maofan Zhou, Mariya Edeleva, Dagmar R. D'hooge\",\"doi\":\"10.1002/appl.202400048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Multiphase polymeric materials and applications play a prominent role in our society. One of the key challenges is the design and modification of their macromolecules so that the composition and structuring of the phases as well as the interactions between them can be controlled from the molecular scale onwards. In the present contribution, it is highlighted that more recently developed event driven (kinetic) Monte Carlo models provide an interesting framework to grasp molecular variations over various length scales. The strength lies in the tracking of individual molecules per phase of interest so that interphase transfer events can be sampled based on the distributed nature of the (macro)molecules present. Hence, the micro-scale of local concentrations and temperatures can be connected to the meso-scale defining interphase transport and morphological variations, with an additional connection to the macro- or application scale within reach by adding macro-scale transfer events to the overall sampling scheme. Starting from a benchmark coupled matrix based Monte Carlo (CMMC) study on the multiphase formation of engineering composites which explicitly acknowledges the type of (macro)molecules present in each phase, it is showcased that the CMMC framework can support the general field of energy and electronics applications. This is highlighted through (i) a case study devoted to the design of polymer electrolytes for batteries, and (ii) a case study on blend design for the regulated stretching of piezoresistive sensors.</p>\",\"PeriodicalId\":100109,\"journal\":{\"name\":\"Applied Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/appl.202400048\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/appl.202400048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Research","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/appl.202400048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Upgrading event driven Monte Carlo simulations for molecule-based morphological control for battery and sensor applications
Multiphase polymeric materials and applications play a prominent role in our society. One of the key challenges is the design and modification of their macromolecules so that the composition and structuring of the phases as well as the interactions between them can be controlled from the molecular scale onwards. In the present contribution, it is highlighted that more recently developed event driven (kinetic) Monte Carlo models provide an interesting framework to grasp molecular variations over various length scales. The strength lies in the tracking of individual molecules per phase of interest so that interphase transfer events can be sampled based on the distributed nature of the (macro)molecules present. Hence, the micro-scale of local concentrations and temperatures can be connected to the meso-scale defining interphase transport and morphological variations, with an additional connection to the macro- or application scale within reach by adding macro-scale transfer events to the overall sampling scheme. Starting from a benchmark coupled matrix based Monte Carlo (CMMC) study on the multiphase formation of engineering composites which explicitly acknowledges the type of (macro)molecules present in each phase, it is showcased that the CMMC framework can support the general field of energy and electronics applications. This is highlighted through (i) a case study devoted to the design of polymer electrolytes for batteries, and (ii) a case study on blend design for the regulated stretching of piezoresistive sensors.