Enabling materials informatics for 29Si solid-state NMR of crystalline materials

Enabling materials informatics for 29Si solid-state NMR of crystalline materials
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为晶体材料的 29Si 固态 NMR 提供材料信息学支持

DOI:
10.1038/s41524-020-0328-3
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发表时间:
2020
影响因子:
9.7
通讯作者:
Hayes, Sophia E.
Hayes, Sophia E.
中科院分区:
材料科学1区
文献类型:
--
作者:
Sun, He;Dwaraknath, Shyam;Ling, Handong;Qu, Xiaohui;Huck, Patrick;Persson, Kristin A.;Hayes, Sophia E.

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核磁共振(NMR)光谱是获得材料局部键合精确信息的有力工具,但如果没有经过良好审查的参考光谱数据集,则难以解释。预测核磁共振参数并将其与三维局部环境联系起来的能力对于理解更复杂的远程相互作用至关重要。新的计算方法通过生成固体的计算参考谱,揭示了29si固体核磁共振的结构信息。这样的预测对于鉴定新的含硅化合物是有用的,并作为确定非晶结构中存在的局部环境的起点。在这项研究中,我们使用42个硅位点作为基准集,将实验报告的29si固态核磁共振光谱与CASTEP-NMR和维也纳Ab - Initio Simulation Program (VASP)计算的结果进行比较。数据驱动的方法使我们能够在一系列实验和计算结果中确定差异的来源。来自核磁共振的信息(以核磁共振张量的形式)已经得到验证,并且在某些情况下进行了更正,以便为本地光谱数据库基础设施(LSDI)编目,其中已经计算了超过10,000个晶体材料的si核磁共振张量。特定张量值的知识可以作为精确执行NMR实验的基础,优化条件以准确捕获元素。从广泛的结构中预测和比较实验观察值的能力可以帮助研究人员进行化学分配和结构确定,因为计算值可以扩展到典型化学位移(或屏蔽)范围之外的表。
Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for obtaining precise information about the local bonding of materials, but difficult to interpret without a well-vetted dataset of reference spectra. The ability to predict NMR parameters and connect them to three-dimensional local environments is critical for understanding more complex, long-range interactions. New computational methods have revealed structural information available from29Si solid-state NMR by generating computed reference spectra for solids. Such predictions are useful for the identification of new silicon-containing compounds, and serve as a starting point for determination of the local environments present in amorphous structures. In this study, we have used 42 silicon sites as a benchmarking set to compare experimentally reported29Si solid-state NMR spectra with those computed by CASTEP-NMR and Vienna Ab Initio Simulation Program (VASP). Data-driven approaches enable us to identify the source of discrepancies across a range of experimental and computational results. The information from NMR (in the form of an NMR tensor) has been validated, and in some cases corrected, in an effort to catalog these for the local spectroscopy database infrastructure (LSDI), where over 10,00029Si NMR tensors for crystalline materials have been computed. Knowledge of specific tensor values can serve as the basis for executing NMR experiments with precision, optimizing conditions to capture the elements accurately. The ability to predict and compare experimental observables from a wide range of structures can aid researchers in their chemical assignments and structure determination, since the computed values enables the extension beyond tables of typical chemical shift (or shielding) ranges.
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