503 research outputs found
An optimized intermolecular force field for hydrogen bonded organic molecular crystals using atomic multipole electrostatics
No full textWe present a re-parameterization of the a popular intermolecular force field for describing intermolecular interactions in the organic solid state. Specifically, we optimize the performance of the exp-6 force field when used in conjunction with atomic multipole electrostatics. We also parameterize force fields that are optimized for use with multipoles derived from polarized molecular electron densities, to account for induction effects in molecular crystals. Parameterization is performed against a set of 186 experimentally determined, low temperature crystal structures and 53 measured sublimation enthalpies of hydrogen bonding organic molecules. The resulting force fields are tested on a validation set of 129 crystal structures and show improved reproduction of the structures and lattice energies of a range of organic molecular crystals compared to the original force field with atomic partial charge electrostatics. Unit cell dimensions of the validation set are typically reproduced to within 3% with the re-parameterized force fields. Lattice energies, which were all included during parameterisation, are systematically underestimated when compared to measured sublimation enthalpies, with mean absolute errors of between 7.4 and 9.0%
Accelerating computational discovery of porous solids through improved navigation of energy structure function maps
No full textWhile energy-structure-function (ESF) maps are a powerful new tool for in silico materials design, the cost of acquiring an ESF map for many properties is too high for routine integration into high-throughput virtual screening workflows. Here, we propose the next evolution of the ESF map. This uses parallel Bayesian optimization to selectively acquire energy and property data, generating the same levels of insight at a fraction of the computational cost. We use this approach to obtain a two orders of magnitude speedup on an ESF study that focused on the discovery of molecular crystals for methane capture, saving more than 500,000 central processing unit hours from the original protocol. By accelerating the acquisition of insight from ESF maps, we pave the way for the use of these maps in automated ultrahigh-throughput screening pipelines by greatly reducing the opportunity risk associated with the choice of system to calculate.</p
Cognitive Chemistry: The Marriage of Machine Learning and Chemistry to Accelerate Materials Discovery
No full text
Controlling the crystallization of porous organic cages: molecular analogs of isoreticular frameworks using shape-specific directing solvents
No full textSmall structural changes in organic molecules can have a large influence on solid-state crystal packing, and this often thwarts attempts to produce isostructural series of crystalline solids. For metal–organic frameworks and covalent organic frameworks, this has been addressed by using strong, directional intermolecular bonding to create families of isoreticular solids. Here, we show that an organic directing solvent, 1,4-dioxane, has a dominant effect on the lattice energy for a series of organic cage molecules. Inclusion of dioxane directs the crystal packing for these cages away from their lowest-energy polymorphs to form isostructural, 3-dimensional diamondoid pore channels. This is a unique function of the size, chemical function, and geometry of 1,4-dioxane, and hence, a noncovalent auxiliary interaction assumes the role of directional coordination bonding or covalent bonding in extended crystalline frameworks. For a new cage, CC13, a dual, interpenetrating pore structure is formed that doubles the gas uptake and the surface area in the resulting dioxane-directed crystals
Predicted crystal energy landscapes of porous organic cages
No full textIn principle, the development of computational methods for structure and property prediction offers the potential for the in silico design of functional materials. Here, we evaluate the crystal energy landscapes of a series of porous organic cages, for which small changes in chemical structure lead to completely different crystal packing arrangements and, hence, porosity. The differences in crystal packing are not intuitively obvious from the molecular structure, and hence qualitative approaches to crystal engineering have limited scope for designing new materials. We find that the crystal structures and the resulting porosity of these molecular crystals can generally be predicted in silico, such that computational screening of similar compounds should be possible. The computational predictability of organic cage crystal packing is demonstrated by the subsequent discovery, during screening of crystallisation conditions, of the lowest energy predicted structure for one of the cages
In silico design of supramolecules from their precursors: Odd–even effects in cage-forming reactions
No full textWe synthesize a series of imine cage molecules where increasing the chain length of the alkanediamine precursor results in an odd–even alternation between [2 + 3] and [4 + 6] cage macrocycles. A computational procedure is developed to predict the thermodynamically preferred product and the lowest energy conformer, hence rationalizing the observed alternation and the 3D cage structures, based on knowledge of the precursors alone
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