The Probe Profile and Lateral Resolution of Scanning Transmission Electron Microscopy of Thick Specimens
Bibliographic record
Abstract
Lateral profiles of the electron probe of scanning transmission electron microscopy (STEM) were simulated at different vertical positions in a micrometers-thick carbon sample. The simulations were carried out using the Monte Carlo method in CASINO software. A model was developed to fit the probe profiles. The model consisted of the sum of a Gaussian function describing the central peak of the profile and two exponential decay functions describing the tail of the profile. Calculations were performed to investigate the fraction of unscattered electrons as a function of the vertical position of the probe in the sample. Line scans were also simulated over gold nanoparticles at the bottom of a carbon film to calculate the achievable resolution as a function of the sample thickness and the number of electrons. The resolution was shown to be noise limited for film thicknesses less than 1 μm. Probe broadening limited the resolution for thicker films. The validity of the simulation method was verified by comparing simulated data with experimental data. The simulation method can be used as quantitative method to predict STEM performance or to interpret STEM images of thick specimens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".