Optimization-Based Thickness Estimation and Depth-Resolved FIB-Induced Damage Characterization via Multislice Electron Ptychography
Abstract
Quantitative electron microscopy requires accurate knowledge of specimen thickness because dynamical scattering strongly affects image contrast and diffraction intensities. In multislice electron ptychography (MEP), specimen thickness is a required input parameter to its forward model, yet the local thickness of a transmission electron microscope (TEM) lamella is often precisely what is unknown. Moreover, thickness is coupled to probe defocus and the number of slices, making its determination from the reconstruction itself nontrivial. Here, we assess whether joint Bayesian optimization of these parameters can provide a physically meaningful estimate of local thickness from four-dimensional scanning transmission electron microscopy (4D-STEM) data. Applied to a wedge-shaped silicon lamella, the optimization reproduced similar local thickness variation measured by electron energy loss spectroscopy (EELS), with a systematic offset of 10-17% relative to the EELS estimates. Using the optimized reconstruction parameters, depth-resolved MEP further separated the crystalline silicon interior from focused ion beam (FIB)-induced amorphous surface layers within the same reconstructed volume. Regions milled at final voltages of 2, 5, 8, and 30 kV yielded amorphous-layer thicknesses of 3.2, 5.0, 7.0, and 26.4 nm, respectively, increasing monotonically with milling voltage and agreeing reasonably with previous cross-sectional measurements. These results show that applying MEP coupled with Bayesian optimization on a single 4D-STEM dataset can provide both local thickness estimates and depth-resolved characterization of FIB-induced damage, offering a route toward more self-consistent, thickness-aware quantitative 4D-STEM analysis.
Related
- Structured Illumination improves Multislice Ptychography
- Trade-off between interface morphology and compositional homogeneity in AlGaAs/GaAs quantum wells revealed by multislice electron ptychography
- Three-Dimensional Imaging of High-Density Dislocation Networks and Their Interactions using Multislice Electron Ptychography
- Assessing quantitative phase reliability in electron ptychography using a twisted trilayer WS2 thickness staircase
- Selecting movements for muscle parameter estimation: insights from gradient analysis in trajectory optimization
BibTeX
@misc{park2026optimizationbased,
title = {{Optimization-Based Thickness Estimation and Depth-Resolved FIB-Induced Damage Characterization via Multislice Electron Ptychography}},
author = {Keun-Yeol Park and Chuqiao Shi and Murat Tuna Pamuk and Sooyoung Cheong and Seonyu Lee and Juhui Oh and Yu-Tsun Shao and Celesta S. Chang},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.09465},
eprint = {2610.09465},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.09465},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Optimization-Based Thickness Estimation and Depth-Resolved FIB-Induced Damage Characterization via Multislice Electron Ptychography
AU - Keun-Yeol Park
AU - Chuqiao Shi
AU - Murat Tuna Pamuk
AU - Sooyoung Cheong
AU - Seonyu Lee
AU - Juhui Oh
AU - Yu-Tsun Shao
AU - Celesta S. Chang
PY - 2026
DA - 2026/10/07
PB - arXiv
DO - 10.48550/arxiv.2610.09465
UR - https://arxiv.org/abs/2610.09465
AB - Quantitative electron microscopy requires accurate knowledge of specimen thickness because dynamical scattering strongly affects image contrast and diffraction intensities. In multislice electron ptychography (MEP), specimen thickness is a required input parameter to its forward model, yet the local thickness of a transmission electron microscope (TEM) lamella is often precisely what is unknown. Moreover, thickness is coupled to probe defocus and the number of slices, making its determination from the reconstruction itself nontrivial. Here, we assess whether joint Bayesian optimization of these parameters can provide a physically meaningful estimate of local thickness from four-dimensional scanning transmission electron microscopy (4D-STEM) data. Applied to a wedge-shaped silicon lamella, the optimization reproduced similar local thickness variation measured by electron energy loss spectroscopy (EELS), with a systematic offset of 10-17% relative to the EELS estimates. Using the optimized reconstruction parameters, depth-resolved MEP further separated the crystalline silicon interior from focused ion beam (FIB)-induced amorphous surface layers within the same reconstructed volume. Regions milled at final voltages of 2, 5, 8, and 30 kV yielded amorphous-layer thicknesses of 3.2, 5.0, 7.0, and 26.4 nm, respectively, increasing monotonically with milling voltage and agreeing reasonably with previous cross-sectional measurements. These results show that applying MEP coupled with Bayesian optimization on a single 4D-STEM dataset can provide both local thickness estimates and depth-resolved characterization of FIB-induced damage, offering a route toward more self-consistent, thickness-aware quantitative 4D-STEM analysis.
ER -