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  • 标题:Disconnecting structure and dynamics in glassy thin films
  • 本地全文:下载
  • 作者:Daniel M. Sussman ; Samuel S. Schoenholz ; Ekin D. Cubuk
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2017
  • 卷号:114
  • 期号:40
  • 页码:10601-10605
  • DOI:10.1073/pnas.1703927114
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:Nanometrically thin glassy films depart strikingly from the behavior of their bulk counterparts. We investigate whether the dynamical differences between a bulk and thin film polymeric glass former can be understood by differences in local microscopic structure. Machine learning methods have shown that local structure can serve as the foundation for successful, predictive models of particle rearrangement dynamics in bulk systems. By contrast, in thin glassy films, we find that particles at the center of the film and those near the surface are structurally indistinguishable despite exhibiting very different dynamics. Next, we show that structure-independent processes, already present in bulk systems and demonstrably different from simple facilitated dynamics, are crucial for understanding glassy dynamics in thin films. Our analysis suggests a picture of glassy dynamics in which two dynamical processes coexist, with relative strengths that depend on the distance from an interface. One of these processes depends on local structure and is unchanged throughout most of the film, while the other is purely Arrhenius, does not depend on local structure, and is strongly enhanced near the free surface of a film.
  • 关键词:machine learning ; glass ; thin film
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