Improved carbon dioxide storage over clay-supported perhydroxylated glucodendrimer
Bibliographic record
Abstract
Low-cost biosourced hybrid microporous adsorbents with improved affinity towards carbon dioxyde (CO2) were prepared through the incorporation of various amounts of glucosylated dendrimer into bentonite- and montmorillonite-rich composite materials. Characterization by nitrogen adsorption–desorption isotherms, surface specific and pore size analyses (BET and BJH), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) revealed changes in the interlayer spacing and textural structure of the materials. Thermal programmed desorption measurements (TPD) showed significant improvements of the retention capacity of CO2 (CRC) and water (WRC). This was explained in terms of enhancement of both surface basicity and hydrophilic character due to the incorporation of terminal polyhydroxyl groups. The CRC was found to vary according to the previous saturation time with CO2 and the carrier gas throughput. CO2 was totally released upon temperature not exceeding 80 °C or even at room temperature upon strong carrier gas stream, thus providing evidence that CO2 capture involves almost exclusively physical interaction with the OH groups of the dendrimer. This result opens promising prospects for the reversible capture of carbon dioxide with easy release without thermal regeneration, more particularly when extending this concept to biosourced dendrimers.
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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".