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Record W2093947769 · doi:10.1021/ef8002944

Polyphosphoric Acid (PPA)-Modified Bitumen: Disruption of the Asphaltenes Network Based on the Reaction of Nonbasic Nitrogen with PPA

2008· article· en· W2093947769 on OpenAlexaff
J-F. Masson, Matthew Gagné

Bibliographic record

VenueEnergy & Fuels · 2008
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsIndole testChemistryDouble bondPyrroleAsphalteneHydrogen bondTryptamineCarbocationPhotochemistryProtonationOrganic chemistryMedicinal chemistryMoleculeIon

Abstract

fetched live from OpenAlex

Relatively little is known about the effect of polyphosphoric acid (PPA) on bitumen chemistry and structure. In an effort to increase this understanding, the reaction of indole with PPA was studied by Fourier transform infrared spectroscopy (FTIR). Indole contains a pyrrole functional group very common in bitumen. The results revealed that both the amine and the double bond of indole can be reactive and that the indole concentration affected the reaction pathway. All reactions began with the protonation of the indole double bond, which provided two reactive carbocation intermediates. When the concentration of indole was high, each carbocation coupled with unprotonated indole and two products were obtained. In one case, two N−H groups produced a N−N bond, and in the other case, two indole double bonds produced a cyclobutane ring. When the concentration of indole was reduced by dilution, N−H coupling proceeded without double bonds coupling and a reaction with the PPA anion was found to occur instead. These findings indicate that the effect of PPA in bitumen may be to raise molecular stiffness through N−N bridging, while at the same time, disrupt the hydrogen-bond network where the N−H function of pyrrole groups is involved and reduce the effective molecular weight of asphaltenes.

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 score0.015
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.205
Teacher spread0.193 · 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

Citations32
Published2008
Admission routes1
Has abstractyes

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