Dual Promotional Effect of <scp>l</scp>-Tryptophan and 1,3-Dioxane on CO<sub>2</sub> Hydrate Kinetics in Seawater under Static/Unstatic Conditions for Carbon Capture and Storage Application
Bibliographic record
Abstract
CO 2 hydrates hold promising applications, including as a medium for carbon storage in oceanic sediments, as a result of their high storage capacity. However, the presence of high salinity in sediments is likely to affect the CO 2 hydrate kinetics. To counter this challenge, the CO 2 hydrate formation, dissociation, and deep morphology have been investigated in seawater (SW) under static and non-static conditions. Moreover, the effect of a kinetic promoter [1000 ppm of l -tryptophan ( l -tryp)] and a thermodynamic promoter (5 wt % 1,3-dioxane) and dual promotional effects of kinetic and thermodynamic promoters (1000 ppm of l -tryp + 5 wt % 1,3-dioxane) have also been studied. In situ Raman spectroscopy was used to probe the real-time CO 2 dissolution in seawater in the presence of 1,3-dioxane. The CO 2 uptake in seawater for the static system was estimated to be in the following order (20 h): CO 2 (30.5 ± 5.0 mmol/mol) > CO 2 + 1000 ppm of l -tryp (30 ± 1.20 mmol/mol) > CO 2 + 1,3-dioxane + 1000 ppm of l -tryp (26.2 ± 7.1 mmol/mol) > CO 2 + 1,3-dioxane (21.1 ± 6.1 mmol/mol). In comparison, for the non-static system, the CO 2 uptake in seawater was estimated to be in the following order (20 h): CO 2 + 1000 ppm of l -tryp (67.8 ± 2.20 mmol/mol) > CO 2 + 5 wt % 1,3-dioxane (49.3 ± 7.0 mmol/mol) > CO 2 + 5 wt % 1,3-dioxane + 1000 ppm of l -tryp (42.9 ± 4.8 mmol/mol) > CO 2 (39.5 ± 4.1 mmol/mol).
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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".