Assessment of commercial hydrate inhibitors using the 3‐in‐1 method
Bibliographic record
Abstract
Abstract Phase equilibria, kinetics, and morphology studies of gas hydrates require separate pieces of equipment and experimentation times in the order of days. Recently, we designed a reactor that allows for tight control of the crystallization temperature. Coupled with a novel method, this reactor can screen the crystal morphology, phase equilibria, and apparent kinetics of gas hydrates. Compared to traditional multi‐trial methods, the main advantage of this method is that only a single experiment, completed in the order of hours, is required to assess: (a) the change in hydrate growth velocity with respect to temperature, (b) the HLV equilibrium temperature at the experimental pressure, and (c) the change in crystal morphology with respect to driving force. Using this 3‐in‐1 method, methane hydrate growth and dissociation was studied in the presence of four commercial inhibitors. Phase equilibria, kinetics, and morphology were obtained for all hydrate systems with inhibitors. The standard uncertainty for the HLV equilibrium temperature was 0.05 K and for pressure 0.005 MPa. The apparent rates of growth were measured for all systems (standard uncertainty was 0.008 mm · s−1) and the difference between the inhibited systems and the pure system was very clear. Crystal habits varied considerably among inhibitors and radically with respect to the uninhibited system. Overall, we present an innovative technology to assess the morphology, kinetics, and thermodynamics of hydrate forming systems with a single apparatus. Furthermore, with little time investment, small sample sizes can be used to obtain replicates with minimum temperature and pressure uncertainties.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".