Sorbent Cost and Performance in CO<sub>2</sub> Capture Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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