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A hybrid computational–experimental approach for automated crystal structure solution

Nature Materials volume 12, pages 123–127 (2013)Cite this article

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Abstract

Crystal structure solution from diffraction experiments is one of the most fundamental tasks in materials science, chemistry, physics and geology. Unfortunately, numerous factors render this process labour intensive and error prone. Experimental conditions, such as high pressure1 or structural metastability2, often complicate characterization. Furthermore, many materials of great modern interest, such as batteries3 and hydrogen storage media4, contain light elements such as Li and H that only weakly scatter X-rays. Finally, structural refinements generally require significant human input and intuition, as they rely on good initial guesses for the target structure. To address these many challenges, we demonstrate a new hybrid approach, first-principles-assisted structure solution (FPASS), which combines experimental diffraction data, statistical symmetry information and first-principles-based algorithmic optimization to automatically solve crystal structures. We demonstrate the broad utility of FPASS to clarify four important crystal structure debates: the hydrogen storage candidates MgNH and NH3BH3; Li2O2, relevant to Li–air batteries; and high-pressure silane, SiH4.

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Figure 1: A schematic comparison of three approaches for solving crystal structures: diffraction experiments, the present work’s FPASS, and purely predictive computation.
Figure 2: Results of the best FPASS run in each experimental candidate space group for MgNH.
Figure 3: A comparison of FPASS results for MgNH with those of crystal structure prediction methods.
Figure 4: FPASS results for 8- and 32-atom Li2O2 structures in the space group.
Figure 5: Performance of FPASS in a case for which DFT had been used to manually assist in a structure refinement of high-pressure ammonia borane25.

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Acknowledgements

B.M. was primarily supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. The work was further supported by DOE under Grant No. DE-FG02-07ER46433. The authors also gratefully acknowledge support from a Laboratory Directed Research and Development programme at Sandia National Laboratories, in the form of a Grand Challenge project entitled Reimagining Liquid Transportation Fuels: Sunshine to Petrol. B.M. would like to thank G. B. González Avilés, J. Emery, V. Ozoliņš and Y. Zhang for helpful conversations. B.M. is also indebted to A.U. Adler for lending his expertise to the creation of Fig. 1.

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  1. Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, USA

    Bryce Meredig & C. Wolverton

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  1. Bryce Meredig
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  2. C. Wolverton
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Contributions

C.W. and B.M. jointly conceived the work and analysed all results. B.M. designed the FPASS algorithm and carried out predictions. B.M. led the manuscript writing, with input from C.W.

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Correspondence to C. Wolverton.

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Meredig, B., Wolverton, C. A hybrid computational–experimental approach for automated crystal structure solution. Nature Mater 12, 123–127 (2013). https://doi.org/10.1038/nmat3490

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