| Autor: |
Lund, Albert M., Orendt, Anita M., Pagola, Gabriel I., Ferraro, Marta B., Facelli, Julio C. |
| Zdroj: |
Crystal Growth & Design; 20240101, Issue: Preprints |
| Abstrakt: |
Previously, it was shown that crystal structure prediction based on genetic algorithms (MGAC program) coupled with force field methods could consistently find experimental structures of crystals. However, inaccuracies in the force field potentials often resulted in poor energetic ranking of the experimental structure, limiting the usefulness of the method. In this work, dispersion-corrected density functional theory is employed to improve the accuracy of the energy rankings, using the software package Quantum Espresso. The best choices of running parameters for this application were determined, followed by completion of crystal optimizations on a test set of archetypical pharmaceutical molecules. It is shown here that the variable cell optimization of experimental structures reproduces the experimental structure with high accuracy (RMS < 0.5 Å) for this test set. It is also shown that the use of electronic structure theory based methods greatly improves the energetic ranking of structures produced by MGAC when used with a force field method, such that the experimental match is found with a high degree of accuracy. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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