The effect of secondary electrons on radiolysis as observed by in liquid TEM: The role of window material and electrical bias
Why this work is in the frame
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Bibliographic record
Abstract
The effect of window material on electron beam induced phenomena in liquid phase electron microscopy (LPEM) is an interesting yet under-explored subject. We have studied the differences of electron beam induced gold nanoparticle (AuNP) growth subject to three encapsulation materials: Silicon Nitride (Si3N4), carbon and formvar. We find Si3N4 liquid cells (LCs) to result in significantly higher AuNP growth yield as compared to LCs employing the other two materials. In all cases, an electrical bias of the entire LC structures significantly affected particle growth. We demonstrate an inverse correlation of the AuNP growth rate with secondary electron (SE) emission from the windows. We attribute these differences at least in part to variations in SE emission dynamics, which is seen as a combination of material and bias dependent SE escape flux (SEEF) and SE return flux (SERF). Furthermore, our model predictions qualitatively match electrochemistry expectations.
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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