Collaborative Computational Project in NMR Crystallography

固态核磁共振(核磁共振)能够提供对各种材料的结构和动力学的极其详细的洞察-从药物化合物和超分子阵列等有机系统到用于下一代电池的无机材料和核废料的安全存储。这些信息对于利用日益复杂的新材料的特性以及应对物理科学领域的重大挑战至关重要。然而，这种实验技术的真正潜力只有通过与先进的计算方法相结合才能实现。特别是，对关键的核磁共振相互作用的第一性原理电子结构预测，如化学位移，允许实验测量与结构直接联系。在解决具有挑战性的问题时，核磁共振结晶学的发展领域得益于与其他实验技术的密切互动，例如粉末X射线衍射和计算方法，特别是晶体结构预测。核磁共振结晶学合作计算项目支持这个由核磁共振光谱学家、结晶学家、材料模型师和应用科学家组成的多学科社区，他们在学术界和工业界工作。我们开发主要的软件工具，使主要以实验为重点的社区能够利用先进的计算技术。

Solid-state nuclear magnetic resonance (NMR) is capable of providing extremely detailed insights into the structure and dynamics of a wide range of materials - from organic systems, such as pharmaceutical compounds and supramolecular arrays, to inorganic materials for next-generation batteries and safe storage of nuclear waste. Such information is crucial for harnessing the properties of increasingly complex new materials, and to address major challenges across the physical sciences. However, the true potential of this experimental technique is only realized through combination with advanced computational methods. In particular, first-principles electronic structure predictions of key NMR interactions, such as chemical shifts, allow experimental measurements to be directly linked to structure. In tackling challenging problems, the developing field of NMR crystallography benefits from close interaction with other experimental techniques, typically powder X-ray diffraction, and computational approaches, particularly crystal structure prediction. The Collaborative Computational Project for NMR Crystallography supports this multidisciplinary community of NMR spectroscopists, crystallographers, materials modellers and application scientists, who work both within academia and industry. We develop overarching software tools enabling a largely experimentally focused community to exploit advanced computational techniques.