High-precision atomic-scale strain mapping of nanoparticles from STEM images.

Strain is a crucial factor that influences the physicochemical properties of nanoparticles. Being able to precisely measure strain is important in understanding the intrinsic mechanism of the enhanced performance of nanoparticles. Techniques that have been developed for strain analysis using scanning transmission electron microscopy (STEM) images can be categorized into diffraction-based method and imaging-based method. Here, using image simulation techniques, it is found that the measured two-dimensional (2D) displacements from annular dark field (ADF) STEM images of a nanoparticle are a good approximation to a projection of the actual three-dimensional (3D) displacements. A methodology for deformation analysis is presented which is based on the detection of atomic columns from atomic-resolution STEM images in real space. Elastic deformation parameters such as strain are usually defined on the basis of a continuum of deformation. The appropriateness of various deformation parameters for atomic-scale investigation on STEM images is explored and a method for determining these is presented. We found that the local lattice parameter and principal strain components are the most physically meaningful parameters to express the materials distortion behaviour. Apart from the local lattice parameter, the other deformation parameters such as normal strains, shear strains and displacements, heavily rely on the choice of reference lattice. It is also found that different reference grids add a series of uniform offsets to these strain variations. Finally, this approach is applied to a PtCo bimetallic nanoparticle to quantify its deformation behaviour.