Y V Shan, A Redermeier, R Kahlenberg, E Kozeschnik
{"title":"铝镁硅铝合金中富镁硅团块向 Mg5Si6 β″ 沉淀转化的模型","authors":"Y V Shan, A Redermeier, R Kahlenberg, E Kozeschnik","doi":"10.1088/1361-651x/ad6ea8","DOIUrl":null,"url":null,"abstract":"A model is developed that describes the kinetics of precipitate transformations in the course of natural and artificial aging of Al alloys containing Mg and Si additions. In our approach, the disordered Mg–Si-rich clusters, which form during natural aging in the highly supersaturated Al matrix, can directly transform into the monoclinic Mg<sub>5</sub>Si<sub>6</sub> (<italic toggle=\"yes\">β</italic>″), without prior dissolution of the clusters and independent nucleation of <italic toggle=\"yes\">β</italic>″ in the Al matrix. The transformation rate is evaluated with classical nucleation theory (CNT), assuming that the clusters represent an infinitely large matrix phase in which the <italic toggle=\"yes\">β</italic>″ precipitates can nucleate. The adapted CNT model is described, and the basic features of the precipitate transformation are discussed in a parameter study. The model can also account for the observation that, during natural aging, the parent clusters occur in a variety of Mg to Si ratios, all of which have a characteristic probability of either transforming into the <italic toggle=\"yes\">β</italic>″ phase or dissolving.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A model for the precipitate transformation of Mg–Si-rich clusters into Mg5Si6 β″ in Al–Mg–Si aluminum alloys\",\"authors\":\"Y V Shan, A Redermeier, R Kahlenberg, E Kozeschnik\",\"doi\":\"10.1088/1361-651x/ad6ea8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A model is developed that describes the kinetics of precipitate transformations in the course of natural and artificial aging of Al alloys containing Mg and Si additions. In our approach, the disordered Mg–Si-rich clusters, which form during natural aging in the highly supersaturated Al matrix, can directly transform into the monoclinic Mg<sub>5</sub>Si<sub>6</sub> (<italic toggle=\\\"yes\\\">β</italic>″), without prior dissolution of the clusters and independent nucleation of <italic toggle=\\\"yes\\\">β</italic>″ in the Al matrix. The transformation rate is evaluated with classical nucleation theory (CNT), assuming that the clusters represent an infinitely large matrix phase in which the <italic toggle=\\\"yes\\\">β</italic>″ precipitates can nucleate. The adapted CNT model is described, and the basic features of the precipitate transformation are discussed in a parameter study. The model can also account for the observation that, during natural aging, the parent clusters occur in a variety of Mg to Si ratios, all of which have a characteristic probability of either transforming into the <italic toggle=\\\"yes\\\">β</italic>″ phase or dissolving.\",\"PeriodicalId\":18648,\"journal\":{\"name\":\"Modelling and Simulation in Materials Science and Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Modelling and Simulation in Materials Science and Engineering\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-651x/ad6ea8\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Modelling and Simulation in Materials Science and Engineering","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1088/1361-651x/ad6ea8","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
A model for the precipitate transformation of Mg–Si-rich clusters into Mg5Si6 β″ in Al–Mg–Si aluminum alloys
A model is developed that describes the kinetics of precipitate transformations in the course of natural and artificial aging of Al alloys containing Mg and Si additions. In our approach, the disordered Mg–Si-rich clusters, which form during natural aging in the highly supersaturated Al matrix, can directly transform into the monoclinic Mg5Si6 (β″), without prior dissolution of the clusters and independent nucleation of β″ in the Al matrix. The transformation rate is evaluated with classical nucleation theory (CNT), assuming that the clusters represent an infinitely large matrix phase in which the β″ precipitates can nucleate. The adapted CNT model is described, and the basic features of the precipitate transformation are discussed in a parameter study. The model can also account for the observation that, during natural aging, the parent clusters occur in a variety of Mg to Si ratios, all of which have a characteristic probability of either transforming into the β″ phase or dissolving.
期刊介绍:
Serving the multidisciplinary materials community, the journal aims to publish new research work that advances the understanding and prediction of material behaviour at scales from atomistic to macroscopic through modelling and simulation.
Subject coverage:
Modelling and/or simulation across materials science that emphasizes fundamental materials issues advancing the understanding and prediction of material behaviour. Interdisciplinary research that tackles challenging and complex materials problems where the governing phenomena may span different scales of materials behaviour, with an emphasis on the development of quantitative approaches to explain and predict experimental observations. Material processing that advances the fundamental materials science and engineering underpinning the connection between processing and properties. Covering all classes of materials, and mechanical, microstructural, electronic, chemical, biological, and optical properties.