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Scott Habershon

Publications and source records attributed to Scott Habershon.

2 recordsLinked to original sources

Determining molecular structures and conformations directly from electron diffraction using a genetic algorithm.

A global optimization strategy, based upon application of a genetic algorithm (GA), is demonstrated as an approach for determining the structures of molecules possessing significant conformational flexibility directly from gas-phase electron diffraction data. In contrast to the common approach to molecular structure determination, based on trial-and-error assessment of structures available from quantum chemical calculations, the GA approach described here does not require expensive quantum mechanical calculations or manual searching of the potential energy surface of the sample molecule, relying instead upon simple comparison between the experimental and calculated diffraction pattern derived from a proposed trial molecular structure. Structures as complex as all-trans retinal and p-coumaric acid, both important chromophores in photosensing processes, may be determined by this approach. In the examples presented here, we find that the GA approach can determine the correct conformation of a flexible molecule described by 11 independent torsion angles. We also demonstrate applications to samples comprising a mixture of two distinct molecular conformations. With these results we conclude that applications of this approach are very promising in elucidating the structures of large molecules directly from electron diffraction data.

Journal Article↗

Development of a multipopulation parallel genetic algorithm for structure solution from powder diffraction data.

Previously, the genetic algorithm (GA) approach for direct-space crystal structure solution from powder diffraction data has been applied successfully in the structure determination of a range of organic molecular materials. In this article, we present a further development of our approach, namely a multipopulation parallel GA (PGA), which is shown to give rise to increased speed, efficiency, and reliability of structure solution calculations, as well as providing new opportunities for further optimizing our GA methodology. The multipopulation PGA is based on the independent evolution of different subpopulations, with occasional interaction (e.g., transfer of structures) allowed to occur between the different subpopulations. Different strategies for carrying out this interpopulation communication are considered in this article, and comparisons are made to the conventional single-population GA. The increased power offered by the PGA approach creates the opportunity for structure determination of molecular crystals of increasing complexity.

Journal Article↗