Samsung Advanced Institute of Technology

By designing the configuration of polymorphs in high-k oxide thin films, new functionalities such as persistent ferroelectricity at an extremely small scale can be exploited. To bolster the technological progress and fundamental understanding in the research area, efficient and reliable mapping of the crystal symmetry encompassing the whole scale of thin films is an urgent requisite. Atomic-scale observation with electron microscopy can provide decisive information for discriminating structures with similar symmetries. However, it often demands multiple/multiscale analysis for cross-validation with other techniques, such as X-ray diffraction, due to the limited range of observation. We developed an efficient and automated methodology for large-scale mapping of the crystal symmetry in polycrystalline high-k oxide thin films using scanning probe-based diffraction and a hybrid deep neural network at a 2 nm2 resolution. The results for doped hafnia films were compatible with atomic structures revealed by microscopy imaging, not requiring intensive human input for interpretation.