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Record W2883196275 · doi:10.1002/ceat.201700489

Tertiary Amine‐Naphthenic Acid Self‐Assembled Surfactants for Viscosity Reduction of Crude Oil

2018· article· en· W2883196275 on OpenAlex
Dongfang Liu, Yuxin Suo, Jiang Tan, Peiyao Zhu, Jihe Zhao, Baogang Wang, Hongsheng Lu

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemical Engineering & Technology · 2018
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsMinistry of Agriculture
FundersNational Natural Science Foundation of China
KeywordsNaphthenic acidEmulsionChemistryCrude oilPulmonary surfactantViscosityEnhanced oil recoveryLight crude oilAmine gas treatingOrganic chemistryChromatographyChemical engineeringPetroleum engineeringMaterials scienceCorrosionGeology

Abstract

fetched live from OpenAlex

Abstract The formation of low‐viscosity emulsions is a vital method for viscosity reduction of crude oil. Naphthenic acids, which are present in crude oil, are potential surface‐active substances. Tertiary amines with CO 2 response can be self‐assembled in situ with the naphthenic acids in the crude oil to form a surfactant, which can emulsify the heavy crude oil and water to form an emulsion. The emulsion can be easily demulsified in the presence of CO 2 . N , N ‐Dimethylbutylamine, N , N ‐dimethyloctylamine, and N , N ‐dimethyldodecylamine were used to prepare heavy crude oil emulsions in this work. This convenient emulsification and demulsification approach provides a new concept for pipeline transportation of heavy crude oil.

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 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 score0.006
Threshold uncertainty score0.812

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 science0.0000.000
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 head0.005
GPT teacher head0.216
Teacher spread0.211 · 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