A 4D-STEM Tomographic Framework Assisted by Object Tracking for Nanoparticle Structure Solution

TL;DR

This paper introduces a novel 4D-STEM tomography method combined with object tracking to solve nanoparticle structures, overcoming limitations of traditional 3D ED, especially for beam-sensitive and agglomerated samples.

Contribution

The study develops an integrated 4D-STEM tomography framework with object tracking, enabling high-quality 3D electron diffraction data from challenging nanoparticle samples.

Findings

Achieved single-crystalline 3D ED datasets from nanopowders.

Enhanced data quality with improved signal-to-noise ratio.

Reduced beam damage through low illumination time.

Abstract

Three-dimensional electron diffraction (3D ED) has emerged as a powerful method for solving the structures of sub-micron-sized particles down to nanoparticles. However, it faces technical challenges when applied to beam-sensitive samples or conglomerated and agglomerated nanoparticles. This study presents a novel approach that combines 4D-STEM tomography with object tracking and segmentation algorithms to overcome these limitations and achieve single-crystalline 3D ED datasets from nanopowder samples. The method and data quality are assessed on brookite TiO2 nanorods and beam-sensitive CsPbBr3 nanoparticles. To finely sample the reciprocal-space, the data acquisition was automated to acquire hundreds of 4D-STEM scans using a slightly convergent beam and at fine tilt steps. The proposed method provides enhanced signal-to-noise ratio, low illumination time for reducing beam damage, and the ability to analyze multiple particles from a single tomographic dataset. The procedure is optimized to be feasible using commercially available desktops and detectors. This extends the method applicability in the community to the systems and samples that were previously inaccessible for conventional 3D ED methods, particularly breaking the technical challenges for the data acquisition.