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Timothy M. Craig

Publications and source records attributed to Timothy M. Craig.

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Continuous three-dimensional imaging of nanoscale dynamics by in situ electron tomography

Visualizing nanoscale transformations in three dimensions (3D) is essential for understanding materials evolution under operating conditions, yet dynamic electron tomography remains limited by slow tilt series acquisition and by reconstruction methods that assume static specimens. These constraints prevent continuous 3D imaging of evolving structures and require electron doses that can alter the specimens and their dynamics. Here, we demonstrate a framework for dynamic electron tomography that combines continuous tilting with a self-supervised deep-learning reconstruction strategy. Our approach incorporates the temporal aspect into the electron tomography reconstruction process to recover 3D volumes at arbitrary time points from a single tilt series. We validate the method using simulations and demonstrate its merit in experimental studies of heat-induced transformations, including morphological evolution of Au nanostars and alloying in Au@Ag nanocubes. Our results establish a practical framework for dynamic, dose-efficient electron tomography, enabling in situ 3D investigation of nanomaterial transformations as well as the characterization of beam-sensitive structures.

cond-mat.mtrl-sci

Real-Time Tilt Undersampling Optimization during Electron Tomography of Beam Sensitive Samples using Golden Ratio Scanning and RECAST3D

Electron tomography is a widely used technique for 3D structural analysis of nanomaterials, but it can cause damage to samples due to high electron doses and long exposure times. To minimize such damage, researchers often reduce beam exposure by acquiring fewer projections through tilt undersampling. However, this approach can also introduce reconstruction artifacts due to insufficient sampling. Therefore, it is important to determine the optimal number of projections that minimizes both beam exposure and undersampling artifacts for accurate reconstructions of beam-sensitive samples. Current methods for determining this optimal number of projections involve acquiring and post-processing multiple reconstructions with different numbers of projections, which can be time-consuming and requires multiple samples due to sample damage. To improve this process, we propose a protocol that combines golden ratio scanning and quasi-3D reconstruction to estimate the optimal number of projections in real-time during a single acquisition. This protocol was validated using simulated and realistic nanoparticles, and was successfully applied to reconstruct two beam-sensitive metal-organic framework complexes.

eess.IV