核磁共振谱（NMR）是精确表征局域结构的利器，尤其对于H和C这类轻元素，NMR表征更是不可替代，这为有机化学和生物领域带来技术性革命。对于有机体系，NMR的数据库已经积累了50年，成为这些体系NMR表征广泛应用的重要原因。然而对于无机材料，NMR的数据量还远远不够。目前无机材料NMR谱的研究主要针对具体一种或者几种材料体系开展相应的计算，并通过与实验比较来解谱，因此目前尚无通用高效的解谱方式。
来自美国华盛顿大学、加州大学和伯克利国家实验室的联合团队提出通过第一原理计算来构建固体核磁共振（NMR）材料数据库来提升该表征手段在无机固体中的应用，以29Si为例，他们探讨了该方法的可行性。具体地，他们计算了材料的NMR屏蔽矩阵，从该矩阵元中可以导出NMR谱信息。首先，基于42种Si的点位结构，他们分别采用两种第一性原理软件包（CASTEP和VASP），计算材料的NMR矩阵，并与实验结构进行了比较。通过数据驱动的方式比较验证了计算结果的可靠性，并针对不同软件修正了计算方法。进而，他们构建了局域谱数据库结构，通过计算又得到material project数据库中10000种含Si晶体材料的NMR矩阵。基于构建的NMR数据库，实验人员可以快速的实现NMR的解谱，确定材料的化学种类和局域结构。该工作的意义在于提出高通量计算构建无机材料的NMR数据库，并以含Si材料为例迈出了第一步，该数据库的构建有望大幅提升NMR表征在无机材料中的精度和效率，使之发挥更重要的作用。
该文近期发表于npj Computational Materials 6: 53 (2020)，英文标题与摘要如下，点击https://www.nature.com/articles/s41524-020-0328-3可以自由获取论文PDF。
Enabling materials informatics for 29Si solid-state NMR of crystalline materials
He Sun, Shyam Dwaraknath, Handong Ling, Xiaohui Qu, Patrick Huck, Kristin A. Persson & Sophia E. Hayes
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 from 29Si 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 reported 29Si 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 10,000 29Si NMR tensors for crystalline materials have been computed.
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