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).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".