Abstract
Advances in electron and probe microscopies allow 10 pm or higher precision in measurements of atomic positions. This level of fidelity is sufficient to correlate the length (and hence energy) of bonds, as well as bond angles to functional properties of materials. Traditionally, this relied on mapping locally measured parameters to macroscopic variables, for example, average unit cell. This description effectively ignores the information contained in the microscopic degrees of freedom available in a high-resolution image. Here we introduce an approach for local analysis of material structure based on statistical analysis of individual atomic neighbourhoods. Clustering and multivariate algorithms such as principal component analysis explore the connectivity of lattice and bond structure, as well as identify minute structural distortions, thus allowing for chemical description and identification of phases. This analysis lays the framework for building image genomes and structure–property libraries, based on conjoining structural and spectral realms through local atomic behaviour.
Highlights
Advances in electron and probe microscopies allow 10 pm or higher precision in measurements of atomic positions
We propose an approach based on the multivariate statistical analysis of the coordination spheres of individual atoms, made up by an array of values that represent a variety of metrics between an atom and its nearest or nearest neighbours, to reveal preferential structures and symmetries
Note that classical definitions of phase and ferroic variants further rely on the presence of translation symmetries, and below we demonstrate the development of a local picture and discuss possible pathways for global description
Summary
Advances in electron and probe microscopies allow 10 pm or higher precision in measurements of atomic positions. Clustering and multivariate algorithms such as principal component analysis explore the connectivity of lattice and bond structure, as well as identify minute structural distortions, allowing for chemical description and identification of phases This analysis lays the framework for building image genomes and structure–property libraries, based on conjoining structural and spectral realms through local atomic behaviour. These surface or lattice descriptions are based on the periodicity of the system in real space and are intrinsically linked to the underlying symmetry Cases where such description fails, including quasicrystals, nanoscale phase separation in strongly correlated oxides[3,4], morphotropic materials and relaxors[5,6,7]; remain a topic of much scientific excitement. We test this approach on a mixed-phase system with a variety of nearest neighbour environments and show how a framework for interpretation of this new type of structural data can be developed
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