Design and commissioning of a high-temperature electrochemical cell for hard x-ray in-operando studies
Bibliographic record
Abstract
Solid oxide cells are a promising technology that can both utilize fuel efficiently in fuel cell mode (SOFC) and store energy as fuel in electrolysis mode (SOEC). Of particular interest is the ability to use clean and renewable energy to both electrolyze water to make hydro- gen fuel, and break down CO2 combustion products into valuable products such as syngas (H2 + CO). As a potential cornerstone of a closed-loop sustainable energy system, we must advance our understanding of the electrocatalysts incorporated in solid-oxide cells to accelerate the energy transition. Operando x-ray absorption spectroscopy (XAS) is a proven tool for the element-specific characterization of low temperature electrochemical cells, since it provides local structural and chemical information on the catalyst. However, operando techniques are challenging to apply to SOC studies because their real-world operating conditions are more demanding. Here we present an experimental apparatus designed to perform XAS on working electrochemical cells under realistic operating conditions. This cell design is adaptable to any beamline, and can be configured to probe both fuel and air electrodes in oxidizing and reducing atmospheres. We present data from commissioning at the SXRMB beamline, demonstrating the ability to obtain XAS and electrochemical measurements from cells at high temperatures. This apparatus has the potential to reveal new insights about SOC mechanism, leading to more directed design of efficient catalysts.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".