Computationally Assisted Identification of Functional Inorganic Materials

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Science  17 May 2013:
Vol. 340, Issue 6134, pp. 847-852
DOI: 10.1126/science.1226558

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Modules of Desire

Using computational methods to design materials with specific properties has found some limited success. Dyer et al. (p. 847, published online 11 April) have devised a method, based on extended module materials assembly, that combines chemical intuition and ab initio calculations starting from fragments or modules of structure types that show the desired functionality. The method was tested by identifying materials suitable for a solid oxide fuel cell cathode.


The design of complex inorganic materials is a challenge because of the diversity of their potential structures. We present a method for the computational identification of materials containing multiple atom types in multiple geometries by ranking candidate structures assembled from extended modules containing chemically realistic atomic environments. Many existing functional materials can be described in this way, and their properties are often determined by the chemistry and electronic structure of their constituent modules. To demonstrate the approach, we isolated the oxide Y2.24Ba2.28Ca3.48Fe7.44Cu0.56O21, with a largest unit cell dimension of over 60 angstroms and 148 atoms in the unit cell, by using a combination of this method and experimental work and show that it has the properties necessary to function as a solid oxide fuel-cell cathode.

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