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A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures. 

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol⁻¹at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases. 

We demonstrate that natural isotopic abundance 2D heteronuclear correlation (HETCOR) solid-state NMR spectra can be used to significantly reduce or eliminate the broadening of 1 H and 13 C solid-state NMR spectra of organic solids due to anisotropic bulk magnetic susceptibility (ABMS). ABMS often manifests in solids with aromatic groups, such as active pharmaceutical ingredients (APIs), and inhomogeneously broadens the NMR peaks of all nuclei in the sample. Inhomogeneous peaks with full widths at half maximum (FWHM) of ∼1 ppm typically result from ABMS broadening and the low spectral resolution impedes the analysis of solid-state NMR spectra. ABMS broadening of solid-state NMR spectra has previously been eliminated using 2D multiple-quantum correlation experiments, or by performing NMR experiments on diluted materials or single crystals. However, these experiments are often infeasible due to their poor sensitivity and/or provide limited gains in resolution. 2D 1 H– 13 C HETCOR experiments have previously been applied to reduce susceptibility broadening in paramagnetic solids and we show that this strategy can significantly reduce ABMS broadening in diamagnetic organic solids. Comparisons of 1D solid-state NMR spectra and 1 H and 13 C solid-state NMR spectra obtained from 2D 1 H– 13 C HETCOR NMR spectra show that the HETCOR spectrum directly increases resolution by a factor of 1.5 to 8. The direct gain in resolution is determined by the ratio of the inhomogeneous 13 C/ 1 H linewidth to the homogeneous 1 H linewidth, with the former depending on the magnitude of the ABMS broadening and the strength of the applied field and the latter on the efficiency of homonuclear decoupling. The direct gains in resolution obtained using the 2D HETCOR experiments are better than that obtained by dilution. For solids with long proton longitudinal relaxation times, dynamic nuclear polarization (DNP) was applied to enhance sensitivity and enable the acquisition of 2D 1 H– 13 C HETCOR NMR spectra. 2D 1 H– 13 C HETCOR experiments were applied to resolve and partially assign the NMR signals of the form I and form II polymorphs of aspirin in a sample containing both forms. These findings have important implications for ultra-high field NMR experiments, optimization of decoupling schemes and assessment of the fundamental limits on the resolution of solid-state NMR spectra.