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Record W2749916848 · doi:10.1002/cjce.22966

Subcritical water hydrolysis of nylon 6 extract concentrate

2017· article· en· W2749916848 on OpenAlexvenueno aff
Chun Qin, Cheng Lin, Jie Tang, Zhen Xi, Ling Zhao

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicSubcritical and Supercritical Water Processes
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaHigher Education Discipline Innovation Project
KeywordsHydrolysisNylon 6Kinetic energyWastewaterChemistryChemical engineeringDimerMaterials scienceChromatographyPulp and paper industryOrganic chemistryEnvironmental engineeringPolymerEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Nylon 6 extract concentrate, namely, wastewater produced from industrial nylon 6 extraction unit, was hydrolyzed in subcritical water to efficiently decrease the cyclic dimer (CD) content. The CD equilibrium conversion reached a maximum when the initial water content ranged from 0.40 to 0.45 g/g; specifically, a CD conversion of 94.3 % was achieved at the hydrolysis temperature of 543 K and an initial water content of 0.40 g/g. A kinetic model including both acid‐ and base‐catalyzed mechanisms was developed. The model predictions were in good agreement with the experimental results. The hydrolysis reaction constants increased significantly with increasing subcritical water content. By considering the effects of subcritical water on the individual reaction constants, the kinetic model could reproduce the experimental results over a wide range of initial water contents. Hopefully, the developed kinetic model will be applied in the design of a novel nylon 6 extract liquor recycling process.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 teacher head, 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

Citations9
Published2017
Admission routes1
Has abstractyes

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