Determination of the chemical shift tensor anisotropy and asymmetry of strongly dipolar coupled protons under fast MAS

IF 1.8 3区 化学 Q4 CHEMISTRY, PHYSICAL
Takeshi Kobayashi , Frédéric A. Perras , Yusuke Nishiyama
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引用次数: 9

Abstract

Orientationally-dependent interactions such as dipolar coupling, quadrupolar coupling, and chemical shift anisotropy (CSA) contain a wealth of spatial information that can be used to elucidate molecular conformations and dynamics. To determine the sign of the chemical shift tensor anisotropy parameter (δaniso), both the |m| ​= ​1 and |m| ​= ​2 components of the CSA need to be symmetry allowed, while the recoupling of the |m| ​= ​1 term is accompanied with the reintroduction of homonuclear dipolar coupling components. Therefore, previously suggested sequences which solely recouple the |m| ​= ​2 term cannot determine the sign a 1H's δaniso in a densely-coupled network. In this study, we demonstrate the CSA recoupling of strongly dipolar coupled 1H spins using the Cnn1(9003601805400360180900) sequence. This pulse scheme recouples both the |m| ​= ​1 and |m| ​= ​2 CSA terms but the scaling factors for the homonuclear dipolar coupling terms are zeroed. Consequently, the sequence is sensitive to the sign of δaniso but is not influenced by homonuclear dipolar interactions.

Abstract Image

快速MAS下强偶极耦合质子化学位移张量各向异性和不对称性的测定
取向依赖的相互作用,如偶极耦合、四极耦合和化学位移各向异性(CSA)包含丰富的空间信息,可用于阐明分子构象和动力学。为了确定化学位移张量各向异性参数(δaniso)的符号,CSA的|m| = 1和|m| = 2分量都需要是对称的,而|m| = 1项的重耦合伴随着同核偶极耦合分量的重新引入。因此,先前提出的仅重新耦合|m| = 2项的序列不能确定在密耦合网络中1H的δaniso的标志。在这项研究中,我们利用Cnn1(9003601805400360180900)序列证明了强偶极耦合1H自旋的CSA重耦合。该脉冲方案将|m| = 1和|m| = 2 CSA项重新耦合,但同核偶极耦合项的标度因子为零。因此,该序列对δaniso符号敏感,但不受同核偶极相互作用的影响。
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来源期刊
CiteScore
5.30
自引率
9.40%
发文量
42
审稿时长
72 days
期刊介绍: The journal Solid State Nuclear Magnetic Resonance publishes original manuscripts of high scientific quality dealing with all experimental and theoretical aspects of solid state NMR. This includes advances in instrumentation, development of new experimental techniques and methodology, new theoretical insights, new data processing and simulation methods, and original applications of established or novel methods to scientific problems.
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