Sorbent Cost and Performance in CO<sub>2</sub> Capture Systems
Bibliographic record
Abstract
Power plants are prime candidates to apply CO 2 capture for final storage as a mitigation option for climate change. Many CO 2 capture concepts make use of a sorption−desorption cycle to separate CO 2 from flue gas or O 2 from air. These include commercial absorption processes, as well as processes using new sorbent formulations, adsorption, and high-temperature chemical looping cycles for CO 2 and O 2 . All of these new processes must confront the large scale of carbon flows typical in a power plant. In this work, a common mass balance for all of these processes is used to define a parameter that highlights the minimum sorbent performance required to keep sorbent makeup costs at an acceptable level. A well-established reference system for which reliable commercial data exist (absorption with monoethanolamine, MEA) is used as a technoeconomic baseline to show that some of the sorbents being proposed in the open literature might need to be tested under laboratory conditions for tens of thousands of sorption−desorption cycles before they can be further considered as viable options for CO 2 capture from power plants.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".