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1. Crystal structure predictions for molecules with soft degrees of freedom using intermonomer force fields derived from first principles

   https://doi.org/10.1107/S2052520624010837  

   Nikhar, Rahul; Podeszwa, Rafał; Rehman, Atta U; Ishaque, Ommair; Jing, Aling; Melkumov, John W; Hong, Richard; Szalewicz, Krzysztof (December 2024, Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials)

   A molecular crystal structure prediction (CSP) protocol used in the seventh blind test is presented. The seventh blind test was divided into two stages and included seven targets, with crystals containing from one to three molecules in asymmetric units, monomers built of up to 100 atoms, and all targets containing monomers with flexible degrees of freedom. Some targets were cocrystals and one target was a salt. These diverse targets were treated using a CSP protocol starting from finding the global and local minima conformations of the target molecule. Subsequently, anab initiotwo-body rigid-monomer six-dimensional force field (aiFF) was developed for the global-minimum conformer. These aiFFs were then used in CSPs consisting of packing and lattice-energy minimization stages. Flexible-monomer CSPs were used for some targets. To describe the intramonomer FF, either generic empirical FFs or reparametrized FFs of this type were used, with some parameters fitted toab initioenergies of monomers in the latter case. A novel packing procedure was applied for two targets in stage 1. The success rate in the structure generation stage was 15% in submission phase and 54% in post-submission phase, while the corresponding values in the structure rating stage were 33% and 89%. We conclude that the inexpensive conformer-based approach with rigid-monomer CSPs can be recommended for investigations of crystals with flexible monomers. An advantage of this protocol is that it is fully based on first-principles quantum mechanics and generates tailor-made FFs suitable for use in subsequent molecular dynamics simulations investigating temperature-dependent effects. However, empirical intramonomer FFs reparametrized usingab initiodata are not yet adequate for CSPs. 

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2. A data-driven and topological mapping approach for the a priori prediction of stable molecular crystalline hydrates

   https://doi.org/10.1073/pnas.2204414119  

   Hong, Richard S.; Mattei, Alessandra; Sheikh, Ahmad Y.; Tuckerman, Mark E. (October 2022, Proceedings of the National Academy of Sciences)

   Predictions of the structures of stoichiometric, fractional, or nonstoichiometric hydrates of organic molecular crystals are immensely challenging due to the extensive search space of different water contents, host molecular placements throughout the crystal, and internal molecular conformations. However, the dry frameworks of these hydrates, especially for nonstoichiometric or isostructural dehydrates, can often be predicted from a standard anhydrous crystal structure prediction (CSP) protocol. Inspired by developments in the field of drug binding, we introduce an efficient data-driven and topologically aware approach for predicting organic molecular crystal hydrate structures through a mapping of water positions within the crystal structure. The method does not require a priori specification of water content and can, therefore, predict stoichiometric, fractional, and nonstoichiometric hydrate structures. This approach, which we term a mapping approach for crystal hydrates (MACH), establishes a set of rules for systematic determination of favorable positions for water insertion within predicted or experimental crystal structures based on considerations of the chemical features of local environments and void regions. The proposed approach is tested on hydrates of three pharmaceutically relevant compounds that exhibit diverse crystal packing motifs and void environments characteristic of hydrate structures. Overall, we show that our mapping approach introduces an advance in the efficient performance of hydrate CSP through generation of stable hydrate stoichiometries at low cost and should be considered an integral component for CSP workflows. 

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3. Solid state photodimerization of 9- tert -butyl anthracene ester produces an exceptionally metastable polymorph according to first-principles calculations

   https://doi.org/10.1039/C8CE01985A  

   Beran, Gregory J. (January 2019, CrystEngComm)

   Molecular crystal engineering seeks to tune the material properties by controlling the crystal packing. However, the range of achievable properties is constrained by the limited energy range of polymorphs which can be crystallized. Here, computational modeling highlights that a solid-state crystal-to-crystal chemical reaction in 9- tert -butyl anthracene ester (9TBAE) nanorods [Al-Kaysi et al. , J. Am. Chem. Soc. , 2006, 128 , 15938] imparts “synthetic memory” into the crystal structure that allows reproducible formation of a highly metastable, yet long-lived polymorph. Specifically, whereas the vast majority of known polymorphs exhibit lattice energy differences below 10 kJ mol −1 , the conformational polymorph formed via solid state reaction chemistry lies 14 kJ mol −1 higher in energy than the form grown from solution, according to calculations that combine a dispersion-corrected second-order Møller–Plesset perturbation theory (MP2D) treatment of the monomer and photodimer with a density functional theory treatment (B86bPBE-XDM) of the intermolecular interactions in the crystal. Moreover, the solid-state reaction environment traps a highly unstable intramolecular photodimer conformation which defies the conventional wisdom surrounding conformational polymorphs. These observations suggest that solid-state reaction chemistry represents an under-appreciated strategy for producing polymorphs that would likely be unobtainable otherwise. 

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4. Genarris 3.0: Generating Close-Packed Molecular Crystal Structures with Rigid Press

   https://doi.org/10.26434/chemrxiv-2025-046zn  

   Yang, Yi; Tom, Rithwik; Wui, Jose; Moussa, Jonathan E; Marom, Noa (June 2025, ChemRxiv)

   Polymorphism in molecular crystals influences their properties and performance. Crystal structure prediction (CSP) can help explore the crystal structure landscape and discover potentially stable polymorphs computationally. We present a new version of the Genarris open-source code, which generates random molecular crystal structures in all space groups and applies physical constraints on intermolecular distances. The main new feature in Genarris 3.0 is the ``Rigid Press algorithm, which uses a regularized hard-sphere potential to compress the unit cell and achieve a maximally close-packed structure based on purely geometric considerations without performing any energy evaluations. In addition, Genarris 3.0 is interfaced with machine-learned interatomic potentials (MLIPs) to accelerate the exploration of the potential energy landscape. We present a new clustering and down-selection workflow that employs the MACE-OFF23(L) MLIPs to perform geometry optimization and energy ranking in the early stages. We use Genarris 3.0 to successfully predict the structure of six targets: aspirin, Target I and Target XXII from previous CSP blind tests, and the energetic materials HMX, CL-20, and DNI. We further analyze the performance of MACE-OFF23(L) compared to dispersion-inclusive density functional theory (DFT) for geometry relaxation and energy ranking. We find significant variability in the performance of MACE-OFF23(L) across chemically diverse targets with particularly poor performance for energetic materials, which is mitigated by our clustering and down-selection procedure. Genarris 3.0 can thus be used effectively to perform CSP and to generate molecular crystal datasets for training ML models. 

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5. The interplay of intra- and intermolecular errors in modeling conformational polymorphs

   https://doi.org/10.1063/5.0088027  

   Beran, Gregory J. O.; Wright, Sarah E.; Greenwell, Chandler; Cruz-Cabeza, Aurora J. (March 2022, The Journal of Chemical Physics)

   Conformational polymorphs of organic molecular crystals represent a challenging test for quantum chemistry because they require careful balancing of the intra- and intermolecular interactions. This study examines 54 molecular conformations from 20 sets of conformational polymorphs, along with the relative lattice energies and 173 dimer interactions taken from six of the polymorph sets. These systems are studied with a variety of van der Waals-inclusive density functionals theory models; dispersion-corrected spin-component-scaled second-order Møller–Plesset perturbation theory (SCS-MP2D); and domain local pair natural orbital coupled cluster singles, doubles, and perturbative triples [DLPNO-CCSD(T)]. We investigate how delocalization error in conventional density functionals impacts monomer conformational energies, systematic errors in the intermolecular interactions, and the nature of error cancellation that occurs in the overall crystal. The density functionals B86bPBE-XDM, PBE-D4, PBE-MBD, PBE0-D4, and PBE0-MBD are found to exhibit sizable one-body and two-body errors vs DLPNO-CCSD(T) benchmarks, and the level of success in predicting the relative polymorph energies relies heavily on error cancellation between different types of intermolecular interactions or between intra- and intermolecular interactions. The SCS-MP2D and, to a lesser extent, ωB97M-V models exhibit smaller errors and rely less on error cancellation. Implications for crystal structure prediction of flexible compounds are discussed. Finally, the one-body and two-body DLPNO-CCSD(T) energies taken from these conformational polymorphs establish the CP1b and CP2b benchmark datasets that could be useful for testing quantum chemistry models in challenging real-world systems with complex interplay between intra- and intermolecular interactions, a number of which are significantly impacted by delocalization error. 

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