Spatial–temporal characterization of photoemission in a streak-mode dynamic transmission electron microscope
Why this work is in the frame
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Bibliographic record
Abstract
A long-standing motivation driving high-speed electron microscopy development is to capture phase transformations and material dynamics in real time with high spatial and temporal resolution. Current dynamic transmission electron microscopes (DTEMs) are limited to nanosecond temporal resolution and the ability to capture only a few frames of a transient event. With the motivation to overcome these limitations, we present our progress in developing a streak-mode DTEM (SM-DTEM) and demonstrate the recovery of picosecond images with high frame sequence depth. We first demonstrate that a zero-dimensional (0D) SM-DTEM can provide temporal information on any local region of interest with a 0.37 μm diameter, a 20-GHz sampling rate, and 1200 data points in the recorded trace. We use this method to characterize the temporal profile of the photoemitted electron pulse, finding that it deviates from the incident ultraviolet laser pulse and contains an unexpected peak near its onset. Then, we demonstrate a two-dimensional (2D) SM-DTEM, which uses compressed-sensing-based tomographic imaging to recover a full spatiotemporal photoemission profile over a 1.85-μm-diameter field of view with nanoscale spatial resolution, 370-ps inter-frame interval, and 140-frame sequence depth in a 50-ns time window. Finally, a perspective is given on the instrumental modifications necessary to further develop this promising technique with the goal of decreasing the time to capture a 2D SM-DTEM dataset.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it