Establishing Accurate High-Resolution Crystal Structures in the Absence of Diffraction Data and Single Crystals-An NMR Approach

    Authors

    K. Kalakewich; R. Iuliucci;J. K. Harper

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    Cryst. Growth Des.

    Keywords

    SOLID-STATE NMR; SMALL ORGANIC-MOLECULES; CHEMICAL-SHIFT TENSORS; STRUCTURE PREDICTION; BLIND TEST; NEUTRON-DIFFRACTION; CRYSTALLOGRAPHY; REFINEMENT; POWDER; SPECTROSCOPY; Chemistry, Multidisciplinary; Crystallography; Materials Science, ; Multidisciplinary

    Abstract

    Predicting accurate crystal structures from theoretical consideration has proven to be remarkably challenging. Although significant progress has been made and numerous approaches have now been investigated, selection of the correct structure as the first choice in blind studies is still rarely achieved. Here a process is described that consistently identifies the correct structure from the myriad candidates created from typical crystal structure prediction software. This approach relies on C-13 solid-state NMR data and a secondary refinement process that includes lattice fields. Four structures are considered, and in all cases the correct structure is selected as the first choice and the only statistically feasible candidate. Data from C-13 chemical shift tensor principal values are found to provide better selectivity, but C-13 isotropic shifts also consistently identify the correct structure. This process involves only experimental NMR data and computer-generated structures, yet the structures created appear to rival the accuracy of structures derived from single crystal diffraction methods including single crystal neutron diffraction.

    Journal Title

    Crystal Growth & Design

    Volume

    13

    Issue/Number

    12

    Publication Date

    1-1-2013

    Document Type

    Article

    Language

    English

    First Page

    5391

    Last Page

    5396

    WOS Identifier

    WOS:000328100400030

    ISSN

    1528-7483

    Share

    COinS