A hybrid computational-experimental approach for automated crystal structure solution
A hybrid computational-experimental approach for automated crystal structure solution
复制标题
DOI：
10.1038/nmat3490
复制
发表时间：
2013-02-01
期刊：
影响因子：
41.2
通讯作者：
Wolverton, C.
中科院分区：
文献类型：
--
作者：
Meredig, Bryce;Wolverton, C.
从衍射实验中求解晶体结构是材料科学、化学、物理学和地质学中最基本的任务之一。不幸的是，许多因素使得该过程劳动密集且容易出错。实验条件，如高压（1）或结构亚稳态（2），往往使表征复杂化。此外，许多现代感兴趣的材料，如电池（3）和储氢介质（4），含有轻元素，如Li和H，它们只能微弱地散射X射线。最后，结构优化通常需要大量的人工输入和直觉，因为它们依赖于对目标结构的良好的初始猜测。为了解决这些挑战，我们展示了一种新的混合方法，第一性原理辅助结构解决方案（FPASS），它结合了实验衍射数据，统计对称信息和基于第一性原理的算法优化，以自动解决晶体结构。我们展示了FPASS的广泛实用性，以澄清四个重要的晶体结构辩论：储氢候选人MgNH和NH3 BH 3; Li 2 O2，相关的锂空气电池;和高压硅烷，SiH 4。
Crystal structure solution from diffraction experiments is one of the most fundamental tasks in materials science, chemistry, physics and geology. Unfortunately, numerous factors render this process labour intensive and error prone. Experimental conditions, such as high pressure(1) or structural metastability(2), often complicate characterization. Furthermore, many materials of great modern interest, such as batteries(3) and hydrogen storage media(4), contain light elements such as Li and H that only weakly scatter X-rays. Finally, structural refinements generally require significant human input and intuition, as they rely on good initial guesses for the target structure. To address these many challenges, we demonstrate a new hybrid approach, first-principles-assisted structure solution (FPASS), which combines experimental diffraction data, statistical symmetry information and first-principles-based algorithmic optimization to automatically solve crystal structures. We demonstrate the broad utility of FPASS to clarify four important crystal structure debates: the hydrogen storage candidates MgNH and NH3BH3; Li2O2, relevant to Li-air batteries; and high-pressure silane, SiH4.