Perfect crystals are rare in nature. Real materials often contain crystal defects and chemical order/disorder such as grain boundaries, dislocations, interfaces, surface reconstructions and point defects1,2,3. Such disruption in periodicity strongly affects material properties and functionality1,2,3. Despite rapid development of quantitative material characterization methods1,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18, correlating three-dimensional (3D) atomic arrangements of chemical order/disorder and crystal defects with material properties remains a challenge. On a parallel front, quantum mechanics calculations such as density functional theory (DFT) have progressed from the modelling of ideal bulk systems to modelling ‘real’ materials with dopants, dislocations, grain boundaries and interfaces19,20; but these calculations rely heavily on average atomic models extracted from crystallography. To improve the predictive power of first-principles calculations, there is a pressing need to use atomic coordinates of real systems beyond average crystallographic measurements. Here we determine the 3D coordinates of 6,569 iron and 16,627 platinum atoms in an iron-platinum nanoparticle, and correlate chemical order/disorder and crystal defects with material properties at the single-atom level. We identify rich structural variety with unprecedented 3D detail including atomic composition, grain boundaries, anti-phase boundaries, anti-site point defects and swap defects. We show that the experimentally measured coordinates and chemical species with 22 picometre precision can be used as direct input for DFT calculations of material properties such as atomic spin and orbital magnetic moments and local magnetocrystalline anisotropy. This work combines 3D atomic structure determination of crystal defects with DFT calculations, which is expected to advance our understanding of structure–property relationships at the fundamental level.
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We thank J. Shan, J. A. Rodriguez, M. Gallagher-Jones and J. Ma for help with this project. This work was primarily supported by the Office of Basic Energy Sciences of the US DOE (DE-SC0010378). This work was also supported by the Division of Materials Research of the US NSF (DMR-1548924 and DMR-1437263) and DARPA (DARPA-BAA-12-63). The chemical ordering analysis and ADF-STEM imaging with TEAM I were performed at the Molecular Foundry, Lawrence Berkeley National Laboratory, which is supported by the Office of Science, Office of Basic Energy Sciences of the US DOE (DE-AC02-05CH11231). M.E. (DFT calculations) was supported by the US DOE, Office of Science, Basic Energy Sciences, Material Sciences and Engineering Division. DFT calculations by P.K. were conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. This research used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the US DOE (DE-AC05-00OR22725).
Extended data figures
Extended data tables
Progressive orthoslices along the  direction (y-axis), showing the 3D reconstructed intensity from 68 experimental ADF-STEM images.
Each orthoslice integrates the intensity of a 1.86-Å-thick layer and individual Fe and Pt atoms can be clearly distinguished from their intensity contrast.
The nanoparticle consists of two large L12 FePt3 grains and seven smaller grains located between them, including three L12 FePt3 grains, three L10 FePt grains and a Pt-rich A1 grain.
About this article
Advanced Structural and Chemical Imaging (2018)