Adsorption microcalorimetry applied to the characterisation of adsorbents for CO<sub>2</sub> capture
Bibliographic record
Abstract
Abstract The present work presents the design, assembly and experimental validation of a microcalorimetric device coupled to a volumetric adsorption setup applied to the characterisation of adsorbents for carbon dioxide (CO2) capture. Three adsorbents were evaluated for CO2 adsorption at 273 K in the pressure range of vacuum to 101 kPa. The data for CO2 on zeolite 13X agreed well with the available data reported in the literature, thus validating the device, which also provided reproducible results with an activated carbon sample. For the amine‐modified zeolite, the differential enthalpy at lower coverage was increased by a factor of 1.7 as compared to the zeolite matrix. This points out to the potential of such technique to characterise heterogeneities introduced by amine impregnation. However, the adsorption uptake was decreased by factor of 2.7 at 101 kPa. This fact suggests that amino groups may be blocking some physisorption sites, leading to restricted chemisorption on the outer surface. Thus, the main novelty of this study is the simultaneous measurement of adsorption isotherms and respective differential enthalpy curves for amine‐impregnated adsorbents, which may be considered a fingerprint of the modified surface chemistry. This work has been carried out in the framework of a cooperation project between three South American universities and is part of the effort to develop and fully characterise adsorbent materials intended for CO2 capture. © 2012 Canadian Society for Chemical Engineering
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".