Pilot-Scale CO<sub>2</sub> Electrolysis Enables a Semi-empirical Electrolyzer Model
Bibliographic record
Abstract
Carbon dioxide (CO 2 ) electrolysis powered with renewable electricity can help close the carbon cycle by converting emissions into chemicals and fuels. Two key advancements are required to bridge the technological gaps for industrial implementation: pilot plant demonstrations with detailed performance data; and chemical engineering process models built and tested with lab- and pilot-scale data. Here, we develop a semi-empirical electrolyzer model in Aspen Custom Modeler which is trained on a 5 cm 2 lab-scale CO 2 electrolyzer. We then scale to a pilot-scale 800 cm 2 single cell and 10 × 800 cm 2 stack and use the results to validate the model; at 100 mA cm –2, the model can predict six of seven cell performance metrics within 16% absolute error and three of five stack metrics within 11% absolute error. With the combination of the electrolyzer model and the pilot-scale data, this work provides the prerequisites for further scaling of CO 2 electrolysis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".