In Liquid Observation and Quantification of Nucleation and Growth of Gold Nanostructures Using in Situ Transmission Electron Microscopy
Bibliographic record
Abstract
In situ liquid transmission electron microscopy (TEM) is a powerful technique for observing nanoscale processes in their native liquid environment and in real time. However, the imaging electron beam can have major interferences with the processes under study, altering the experimental outcome. Here, we use in situ liquid TEM to understand the differences between beam-induced and electrodeposition processes that result in nucleation and growth of gold crystallites. Through this study, we find that beam-induced and electrodeposition processes result in crystallites that deposit at different locations within the liquid cell and differ significantly in morphology. Furthermore, we develop a strategy based on increasing the liquid layer thickness for reducing the amount of beam-induced crystallites to negligible levels. Through this optimized system, we study the electrodeposition of gold on carbon electrodes by correlating current time transients and their corresponding time-resolved scanning TEM images. This analysis demonstrates that even when the electron-beam plays a negligible role in gold deposition under optimal conditions, there is a large discrepancy between the amount of deposits observed and the amount measured using the current time transients. This finding sheds light on the heterogeneity of the deposition process and provides insights into designing a new class of in situ liquid TEM systems.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".