In Situ Transmission Electron Microscopy and Soft X-Ray Spectro-Microscopy to Understand Electrochemical Processes
Bibliographic record
Abstract
Electrochemical CO2 conversion offers a route to use renewable sources of electricity to convert CO2 into valuable carbon-based fuels and chemicals, including carbon monoxide, ethanol and ethylene. For electrochemical CO2 conversion technologies to become a viable component of future sustainable energy infrastructures, improved performance materials (catalysts, electrodes, membrane electrode assemblies) are needed to achieve high conversion rates, selectivity and single-pass utilization of CO2. This talk will focus on the development of techniques to characterize the properties of electrochemical CO2 conversion materials under reaction conditions. These in-situ methods are producing results which will guide the design of next generation materials and reactors. The talk will focus primarily on in situ transmission electron microscopy (TEM) and related spectroscopic techniques (energy dispersive X-ray analysis and selected area electron diffraction), along with synchrotron-based methods including in-situ soft X-ray scanning transmission X-ray microscopy (STXM).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".