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通过受限晶体结构预测直接洞察界面的结构-性质关系。

Direct insight into the structure-property relation of interfaces from constrained crystal structure prediction.

作者信息

Sun Lin, Marques Miguel A L, Botti Silvana

机构信息

Institut für Festkörpertheorie und -optik, Friedrich-Schiller-Universität Jena, Jena, Germany.

Institut für Physik, Martin-Luther-Universität Halle-Wittenberg, Halle, Germany.

出版信息

Nat Commun. 2021 Feb 5;12(1):811. doi: 10.1038/s41467-020-20855-0.

DOI:10.1038/s41467-020-20855-0
PMID:33547276
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7864966/
Abstract

A major issue that prevents a full understanding of heterogeneous materials is the lack of systematic first-principles methods to consistently predict energetics and electronic properties of reconstructed interfaces. In this work we address this problem with an efficient and accurate computational scheme. We extend the minima-hopping method implementing constraints crafted for two-dimensional atomic relaxation and enabling variations of the atomic density close to the interface. A combination of density-functional and accurate density-functional tight-binding calculations supply energy and forces to structure prediction. We demonstrate the power of this method by applying it to extract structure-property relations for a large and varied family of symmetric and asymmetric tilt boundaries in polycrystalline silicon. We find a rich polymorphism in the interface reconstructions, with recurring bonding patterns that we classify in increasing energetic order. Finally, a clear relation between bonding patterns and electrically active grain boundary states is unveiled and discussed.

摘要

阻碍全面理解异质材料的一个主要问题是缺乏系统的第一性原理方法来一致地预测重构界面的能量学和电子性质。在这项工作中,我们用一种高效且准确的计算方案解决了这个问题。我们扩展了最小跳跃法,实现了为二维原子弛豫精心设计的约束,并允许靠近界面处原子密度的变化。密度泛函和精确的密度泛函紧束缚计算相结合,为结构预测提供能量和力。我们通过将该方法应用于提取多晶硅中大量不同的对称和非对称倾斜边界的结构-性质关系,展示了该方法的强大之处。我们在界面重构中发现了丰富的多态性,具有反复出现的键合模式,我们按能量增加的顺序对其进行了分类。最后,揭示并讨论了键合模式与电活性晶界态之间的明确关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/04ab637c5051/41467_2020_20855_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/b5b9c778fb31/41467_2020_20855_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/8a41efc05982/41467_2020_20855_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/1a984990b99f/41467_2020_20855_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/646cba7278bc/41467_2020_20855_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/6bef0b217f59/41467_2020_20855_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/bfe783e1f020/41467_2020_20855_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/4a889f7c3546/41467_2020_20855_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/04ab637c5051/41467_2020_20855_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/b5b9c778fb31/41467_2020_20855_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/8a41efc05982/41467_2020_20855_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/1a984990b99f/41467_2020_20855_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/646cba7278bc/41467_2020_20855_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/6bef0b217f59/41467_2020_20855_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/bfe783e1f020/41467_2020_20855_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/4a889f7c3546/41467_2020_20855_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bba/7864966/04ab637c5051/41467_2020_20855_Fig8_HTML.jpg

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