Bibliographic record
Abstract
The emission of carbon dioxide (CO2) is gradually increasing, and CO2 adsorption from post-combustion processes in thermal power plants could be a viable option. As a solid adsorbent for CO2 capture, metal-organic frameworks (MOFs) have higher selectivity and capacity for flue gas. Compared with traditional adsorbents, calgary framework 20 (CALF-20) that belongs to a zinc-based MOFs, efficiently captures CO2 from flue gas and is affordable and durable also, which lays the foundation for its large-scale production. This article will introduce the overall idea of CO2 adsorption, the structure of CALF-20, selectivity for N2 and H2O, competitive adsorption with H2O-CO2 and durability, and verify the excellent performance of CALF-20 with experimental results. In addition, the possibility of mass production was also shown. Specifically, CALF-20 is not as difficult to large scaling produce as other MOFs. In fact, its large-scale industrial production is feasible with its advantages of low cost, high yield, stability, environmentally friendly and safety.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".