Three-dimensional reconstruction of weakly scattering objects from single-defocus 4D-STEM data
Abstract
Three-dimensional (3D) atomic-structure analysis is of central importance in (scanning) transmission electron microscopy (STEM). STEM techniques to reconstruct 3D structure include tilt-series or defocus-series annular dark-field, best suited to heavier atomic species, and dynamical-scattering-model inversion applied to single-defocus four-dimensional (4D) STEM data, requiring computationally expensive post-experiment analysis. In this study, we propose a 3D-structure linear inversion (3D LINV) STEM algorithm, which enables a fast and direct reconstruction of 3D structures from a single-defocus 4D-STEM dataset. This method is based on solving linear equations relating the measured 4D-STEM data and the unknown 3D specimen potential under the thick weak phase object approximation. We show the capabilities of 3D LINV STEM through systematic 4D-STEM simulations across various observation parameters such as specimen thickness, partial coherence, and shot noise, and through an experimental demonstration of 3D structure reconstruction of a stacked freestanding membrane with atomic-scale lateral resolution and nanometre-scale depth resolution.
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BibTeX
@misc{ooe2026threedimensional,
title = {{Three-dimensional reconstruction of weakly scattering objects from single-defocus 4D-STEM data}},
author = {Kousuke Ooe and Yufan Shen and Yuichi Shimakawa and Daisuke Kan and Scott D. Findlay},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.15303},
eprint = {2610.15303},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.15303},
}
RIS
TY - UNPB
TI - Three-dimensional reconstruction of weakly scattering objects from single-defocus 4D-STEM data
AU - Kousuke Ooe
AU - Yufan Shen
AU - Yuichi Shimakawa
AU - Daisuke Kan
AU - Scott D. Findlay
PY - 2026
DA - 2026/10/11
PB - arXiv
DO - 10.48550/arxiv.2610.15303
UR - https://arxiv.org/abs/2610.15303
AB - Three-dimensional (3D) atomic-structure analysis is of central importance in (scanning) transmission electron microscopy (STEM). STEM techniques to reconstruct 3D structure include tilt-series or defocus-series annular dark-field, best suited to heavier atomic species, and dynamical-scattering-model inversion applied to single-defocus four-dimensional (4D) STEM data, requiring computationally expensive post-experiment analysis. In this study, we propose a 3D-structure linear inversion (3D LINV) STEM algorithm, which enables a fast and direct reconstruction of 3D structures from a single-defocus 4D-STEM dataset. This method is based on solving linear equations relating the measured 4D-STEM data and the unknown 3D specimen potential under the thick weak phase object approximation. We show the capabilities of 3D LINV STEM through systematic 4D-STEM simulations across various observation parameters such as specimen thickness, partial coherence, and shot noise, and through an experimental demonstration of 3D structure reconstruction of a stacked freestanding membrane with atomic-scale lateral resolution and nanometre-scale depth resolution.
ER -