Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models.,Acta Crystallographica Section A: Foundations and Advances

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Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models.
Acta Crystallographica Section A: Foundations and Advances ( IF 1.9 ) Pub Date : 2020-04-28 , DOI: 10.1107/s2053273320002028
Long Yang ₁ , Pavol Juhás ₂ , Maxwell W Terban ₃ , Matthew G Tucker ₄ , Simon J L Billinge ₁

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A new approach is presented to obtain candidate structures from atomic pair distribution function (PDF) data in a highly automated way. It fetches, from web-based structural databases, all the structures meeting the experimenter's search criteria and performs structure refinements on them without human intervention. It supports both X-ray and neutron PDFs. Tests on various material systems show the effectiveness and robustness of the algorithm in finding the correct atomic crystal structure. It works on crystalline and nanocrystalline materials including complex oxide nanoparticles and nanowires, low-symmetry and locally distorted structures, and complicated doped and magnetic materials. This approach could greatly reduce the traditional structure searching work and enable the possibility of high-throughput real-time auto-analysis PDF experiments in the future.

中文翻译：

结构挖掘：通过自动拟合大量模型的原子对分布函数来筛选结构模型。

提出了一种新方法，以高度自动化的方式从原子对分布函数（PDF）数据中获取候选结构。它从基于网络的结构数据库中获取满足实验者搜索标准的所有结构，并在无需人工干预的情况下对它们进行结构细化。它支持 X 射线 PDF 和中子 PDF。对各种材料系统的测试表明了该算法在寻找正确原子晶体结构方面的有效性和鲁棒性。它适用于晶体和纳米晶体材料，包括复杂的氧化物纳米粒子和纳米线、低对称性和局部扭曲结构以及复杂的掺杂和磁性材料。这种方法可以大大减少传统的结构搜索工作，并为未来高通量实时自动分析PDF实验提供了可能。

更新日期：2020-04-28

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