npj：29Si固態NMR光譜—構建無機材料信息學

核磁共振譜（NMR）是精確表徵局域結構的利器，尤其對於H和C這類輕元素，NMR表徵更是不可替代，這為有機化學和生物領域帶來技術性革命。對於有機體系，NMR的資料庫已經積累了50年，成為這些體系NMR表徵廣泛應用的重要原因。然而對於無機材料，NMR的數據量還遠遠不夠。目前無機材料NMR譜的研究主要針對具體一種或者幾種材料體系開展相應的計算，並通過與實驗比較來解譜，因此目前尚無通用高效的解譜方式。

來自美國華盛頓大學、加州大學和伯克利國家實驗室的聯合團隊提出通過第一原理計算來構建固體核磁共振（NMR）材料資料庫來提升該表徵手段在無機固體中的應用，以29Si為例，他們探討了該方法的可行性。具體地，他們計算了材料的NMR屏蔽矩陣，從該矩陣元中可以導出NMR譜信息。首先，基於42種Si的點位結構，他們分別採用兩種第一性原理軟體包（CASTEP和VASP），計算材料的NMR矩陣，並與實驗結構進行了比較。通過數據驅動的方式比較驗證了計算結果的可靠性，並針對不同軟體修正了計算方法。進而，他們構建了局域譜資料庫結構，通過計算又得到material project資料庫中10000種含Si晶體材料的NMR矩陣。基於構建的NMR資料庫，實驗人員可以快速的實現NMR的解譜，確定材料的化學種類和局域結構。該工作的意義在於提出高通量計算構建無機材料的NMR資料庫，並以含Si材料為例邁出了第一步，該資料庫的構建有望大幅提升NMR表徵在無機材料中的精度和效率，使之發揮更重要的作用。

該文近期發表於npj Computational Materials 6: 53 (2020)，英文標題與摘要如下，點擊https://www.nature.com/articles/s41524-020-0328-3可以自由獲取論文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.