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Ab initio crystal structure prediction-I. Rigid molecules.

Panagiotis G Karamertzanis1, Constantinos C Pantelides

  • 1Centre for Process Systems Engineering, Department of Chemical Engineering and Chemical Technology, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom.

Journal of Computational Chemistry
|December 29, 2004
PubMed
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This study introduces a novel method to predict molecular crystal structures from atomic connectivity. The approach uses global lattice enthalpy minimization, successfully identifying known crystal structures for several compounds.

Area of Science:

  • Crystallography
  • Computational Chemistry
  • Materials Science

Background:

  • Predicting molecular crystal structures is crucial for materials design and drug development.
  • Current methods often require experimental data or are computationally intensive.
  • Accurate structure prediction is essential for understanding solid-state properties.

Purpose of the Study:

  • To develop a new computational methodology for predicting molecular crystal structures.
  • To enable structure prediction using only the molecule's atomic connectivity.
  • To identify crystal structures, including those in less common space groups and with multiple molecules per asymmetric unit.

Main Methods:

  • Global minimization of lattice enthalpy.
  • Modeling electrostatic interactions using distributed charges derived from quantum mechanical calculations.

Related Experiment Videos

  • A four-step global optimization algorithm with parallelized implementation.

    • Main Results:

    • Successful prediction of crystal structures for 3-aza-bicyclo(3.3.1)nonane-2,4-dione, allopurinol, 1,3,4,6,7,9-hexa-azacycl(3.3.3)azine, and triethylenediamine.
    • The algorithm identified experimentally known structures among the most stable predicted polymorphs.
    • The method allows exploration of a wider solution space, including complex crystal packing arrangements.

    Conclusions:

    • The presented methodology offers a robust approach for *de novo* crystal structure prediction.
    • The method's ability to handle complex cases expands the scope of computational crystallography.
    • Further refinement may improve the identification of the global minimum structure.