Evaluation of Acrylamide/α-Lipoic Acid Statistical Copolymers as Degradable Water-Soluble Kinetic Gas Hydrate Inhibitors
Bibliographic record
Abstract
Readily degradable low-dose hydrate inhibitors are of great significance for flow assurance in the petroleum industry. Recently, α-lipoic acid (LA) was shown to undergo ring-opening reaction via reversible addition–fragmentation chain-transfer copolymerization with acrylamides to introduce labile disulfide bonds into the stable vinyl polymer backbone. Here, LA was copolymerized with acryloyl morpholine (AM) to evaluate their performance as kinetic hydrate inhibitors. Degradability was confirmed for the copolymers with 20 mol.% LA (AM/LA20, Mn = 19 → 9 kDa) after disulfide reduction. Thermogravimetric analysis also indicated faster thermal degradation of AM/LA due to the incorporation of weaker S-S and S-C linkages. Increasing LA content reduced hydrophilicity, and the copolymers were treated with NaOH to ensure water solubility. However, at 700 ppm, poly(AM) homopolymer reduced methane consumption during hydrate growth to 54% with respect to the uninhibited system, while gas consumption for the carboxylate AM/LA20 reached 78%. An advantageous feature of LA is its carboxylic acid, allowing desired functionalities to be grafted onto the degradable copolymer. Isopropyl amine (IPAm) was coupled with LA to form an amide known to be effective during hydrate inhibition (LA(IPAm)). The copolymer AM/LA(IPAm)20 demonstrated better water solubility compared to the original AM/LA20. Furthermore, the desirable IPAm functionality allowed the hydrate inhibition to be re-established at 54%, nearly recovering the performance of the poly(AM) homopolymer. This article assesses the application of LA and LA derivatives as building blocks for degradable amide-based kinetic hydrate inhibitors by validating their degradability with material characterizations and their inhibition performance during structure I hydrate growth.
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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 | 0.001 | 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) | 0.014 | 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 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".