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Record W3119013047 · doi:10.3390/en14020341

Amphiphilic Block Copolymers with Vinyl Caprolactam as Kinetic Gas Hydrate Inhibitors

2021· article· en· W3119013047 on OpenAlexafffund
Faraz Rajput, Milan Marić, Phillip Servio

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCaprolactamCopolymerChemistryChain transferMicellePolymer chemistryMethaneRaftHydratePolymerChemical engineeringAqueous solutionMaterials scienceOrganic chemistryRadical polymerization

Abstract

fetched live from OpenAlex

Macrosurfactants consisting of water-soluble poly(vinylcaprolactam) (PVCap) or poly(vinylpyrrolidone) (PVP) segments with comparatively shorter hydrophobic poly(styrene) (PS) or poly(2,3,4,5,6-pentafluorostyrene) (PPFS) segments were used as kinetic hydrate inhibitors (KHIs). These were synthesized with 2-cyanopropan-2-yl N-methyl-N-(pyridin-4-yl)dithiocarbamate switchable reversible addition–fragmentation chain transfer (RAFT) agent at 60 °C or 90 °C for 1-P(S/PFS) or 1-PVCap, respectively, followed by chain extension at 90 °C or 70 °C with PVCap or PVP, respectively. The addition of PVCap to the pure methane-water system resulted in a 53% reduction of methane consumption (comparable to PVP with 51% inhibition) during the initial growth phase. A PS-PVCap block copolymer comprised of 10 mol% PS and 90 mol% PVCap improved inhibition to 56% compared to the pure methane-water system with no KHIs. Substituting PS with a more hydrophobic PPFS segment further improved inhibition to 73%. By increasing the ratio of the hydrophobic PS- to PVCap- groups in the polymer, an increase of its inhibition potential was measured. For PPFS-PVCap, an increase of PPFS ratio from 5% to 10% decreased the methane formation rate by 6%. However, PPFS-PVCap block copolymers with more than 20 mol% PPFS were unable to dissolve in water due to increase in hydrophobicity and the attendant low critical micelle concentration (CMC).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.187
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2021
Admission routes2
Has abstractyes

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