Thin-Film Approach to Rapid, Quantitative Measurements of Mixed-Gas Adsorption Equilibrium in Nanoporous Materials
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Nanoporous adsorbent materials are a key part of many industrial processes, including the rapidly expanding carbon capture industry. The development of advanced sorbents requires an assessment of the sorbent’s performance under mixed-gas conditions. Existing measurement techniques tend to be slow, material-intensive, and have limited ability to measure competitive mixed-gas sorption. We have developed a novel technique that measures thin films of sorbents deposited onto sensitive microelectromechanical system (MEMS) transducers. This technique is fast, requires very little material, and enables real-time monitoring of binary gas sorption. We report measurements of CO 2 /H 2 O mixed-gas isotherms at three different temperatures on the carbon capture MOF CALF-20. The measured experimental data on CO 2 /H 2 O mixture adsorption in CALF-20 demonstrate the severe limitations of the Ideal Adsorbed Solution Theory (IAST) in providing a quantitative estimation of the component loadings. Departures from the IAST are quantified by the introduction of activity coefficients and the use of the Real Adsorbed Solution Theory (RAST).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".