Carbon Dioxide Capture from Ambient Air Using Amine-Grafted Mesoporous Adsorbents
Bibliographic record
Abstract
Anthropogenic emissions of carbon dioxide (CO2) have been identified as a major contributor to climate change. An attractive approach to tackle the increasing levels of CO2 in the atmosphere is direct extraction via absorption of CO2 from ambient air, to be subsequently desorbed and processed under controlled conditions. The feasibility of this approach depends on the sorbent material that should combine a long lifetime with nontoxicity, high selectivity for CO2, and favorable thermodynamic cycling properties. Adsorbents based on pore-expanded mesoporous silica grafted with amines have previously been found to combine high CO2 adsorption capacity at low partial pressures with operational stability under highly defined laboratory conditions. Here we examine the real potential and functionality of these materials by using more realistic conditions using both pure CO2, synthetic air, and, most importantly, ambient air. Through a combination of thermogravimetric analysis and Fourier transform infrared (TGA-FTIR) spectroscopy we address the primary functionality and by diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy the observed degradation of the material on a molecular level.
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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 | 0.000 |
| 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".