A Review of Reactor Designs and Materials Employed for Increasing the Rate of Gas Hydrate Formation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the course of the last 50 years, gas hydrates have been proposed for use in a diverse range of applications, including gas storage, gas transportation, gas separation, ice cream production, and seawater desalination. While there have been many studies that have demonstrated the thermodynamic potential for using gas hydrates in these applications, the slow kinetics of formation and, to a lesser extent, dissociation, have hindered their adoption. Since the early 1990s, there have been numerous studies that have highlighted the use of surfactants, such as sodium dodecyl sulfate (SDS), for the enhancement of gas hydrate kinetics. More recently, there has been growing interest in non-surfactant-based methods for enhancing the rate of gas hydrate formation, which physically increase the surface area available for gas hydrate formation. These methods, which include hydrate formation in sand packs, silica gels, dry water, foams, nanoparticles, and hydrogels are relatively recent advances and are discussed in a disparate array of academic journals. The purpose of this review article is to compile and summarize this knowledge in a single article and to highlight the prospect and future challenges.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it