The evolution of texture in polycrystalline thin films lie within the process of crystal growth which undergone a selection process where grains with energetically favorable orientations grows at the cost of unfavorable ones. Texture evolution is conventionally evaluated by probing the reciprocal space using X-ray and/or electron diffraction methods, where spatial information, e.g., orientation relationship of particular grains, are hardly accessible.
Here, we explore the possibility to study the texture evolution of a polycrystalline gold thin film in-situ in the TEM by four-dimensional scanning transmission electron microscopy (4D-STEM) using a fast direct electron detector (DED) capable to run up to 100 kHz. Nominal 15 nm nano-crystalline gold thin with was deposited with PVD on MEMS heating chips (DENSsolutions Wildfire) and annealed in the TEM at 150⁰C up to 180 s. During annealing at different times, nano-beam 4D-STEM datasets were acquired (with MEMS chips quenched to RT) at high speed, allowing identical regions of interest (ROI) to be tracked over annealing time. The acquired data is them analyzed using the ACOM [1] routine within Py4dstem [2] package as well as custom codes. To enable in-situ observation and reliable ACOM analysis, experimental conditions including convergence angle, probe current, real- and reciprocal space sampling, detector binning and speed has to be balanced. With optimized conditions, we found that time resolution of 5 – 10s for statistically relevant ROI and sub-3nm spatial resolution is realizable. Finally, we were able to visualize the grain orientation from the datasets and tracking the evolution of texture evolution of a defined ROI from the early stage on. We observed the growth of <111> oriented grains at the cost of neighboring high-index oriented grains. The 4D-STEM datasets allow grain orientation relationship to be analyzed qualitatively as well quantitatively, shedding light to the complex interplay between various factors including grain boundaries, defects and even local strain.

References:
[1] Ophus, C., Zeltmann, S. E., Bruefach, A., Rakowski, A., Savitzky, B. H., Minor, A. M., & Scott, M. C. (2022). Automated Crystal Orientation Mapping in py4DSTEM using Sparse Correlation Matching. Microscopy and Microanalysis, 28, 390–403.
[2] Savitzky, B. H., Hughes, L. A., Zeltmann, S. E., Brown, H. G., Zhao, S., Pelz, P. M., … Ophus, C. (2021). py4DSTEM: A software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets. Microscopy and Microanalysis, 27, 712.