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Computationally Assisted Identification of Functional Inorganic Materials

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Science  11 Apr 2013:
1226558
DOI: 10.1126/science.1226558

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Abstract

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, the oxide Y2.24Ba2.28Ca3.48Fe7.44Cu0.56O21, with a largest unit cell dimension of over 60 Å and 148 atoms in the unit cell, was isolated using a combination of this method and experimental work, and is shown to have the properties necessary to function as a solid oxide fuel cell cathode.

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