In Situ Transmission Electron Microscopy of Electrocatalyst Materials: Proposed Workflows, Technical Advances, Challenges, and Lessons Learned
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In situ electrochemical liquid phase transmission electron microscopy (LP‐TEM) measurements utilize micro‐chip three‐electrode cells with electron transparent silicon nitride windows that confine the liquid electrolyte. By imaging electrocatalysts deposited on micro‐patterned electrodes, LP‐TEM provides insight into morphological, phase structure, and compositional changes within electrocatalyst materials under electrochemical reaction conditions, which have practical implications on activity, selectivity, and durability. Despite LP‐TEM capabilities becoming more accessible, in situ measurements under electrochemical reaction conditions remain non‐trivial, with challenges including electron beam interactions with the electrolyte and electrode, the lack of well‐defined experimental workflows, and difficulty interpreting particle behavior within a liquid. Herein a summary of the current state of LP‐TEM technique capabilities alongside a discussion of the relevant experimental challenges researchers typically face, with a focus on in situ studies of electrochemical CO 2 conversion catalysts is provided. A methodological approach for in situ LP‐TEM measurements on CO 2 R catalysts prepared by electro‐deposition, sputtering, or drop‐casting is presented and include case studies where challenges and proposed workflows for each are highlighted. By providing a summary of LP‐TEM technique capabilities and guidance for the measurements, the goal is for this paper to reduce barriers for researchers who are interested in utilizing LP‐TEM characterization to answer their scientific questions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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