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Record W2408702285 · doi:10.1021/acs.est.6b01350

Silver-Ion Solid Phase Extraction Separation of Classical, Aromatic, Oxidized, and Heteroatomic Naphthenic Acids from Oil Sands Process-Affected Water

2016· article· en· W2408702285 on OpenAlexafffund
Rongfu Huang, Yuan Chen, Mohamed Gamal El‐Din

Bibliographic record

VenueEnvironmental Science & Technology · 2016
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersHelmholtz-Alberta InitiativeShell CanadaNatural Sciences and Engineering Research Council of CanadaSyncrudeAlberta Environment and ParksCanadian Natural Resources Limited
KeywordsNaphthenic acidOil sandsExtraction (chemistry)ChemistryPhase (matter)Separation processProcess (computing)Solid phase extractionEnvironmental chemistryChromatographyMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

The separation of classical, aromatic, oxidized, and heteroatomic (sulfur-containing) naphthenic acid (NA) species from unprocessed and ozone-treated oil sands process-affected water (OSPW) was performed using silver-ion (Ag-ion) solid phase extraction (SPE) without the requirement of pre-methylation for NAs. OSPW samples before SPE and SPE fractions were characterized using ultra performance liquid chromatography ion mobility time-of-flight mass spectrometry (UPLC-IM-TOFMS) to corroborate the separation of distinct NA species. The mass spectrum identification applied a mass tolerance of ±1.5 mDa due to the mass errors of NAs were measured within this range, allowing the identification of O2S-NAs from O2-NAs. Moreover, separated NA species facilitated the tandem mass spectrometry (MS/MS) characterization of NA compounds due to the removal of matrix and a simplified composition. MS/MS results showed that classical, aromatic, oxidized, and sulfur-containing NA compounds were eluted into individual SPE fractions. Overall results indicated that the separation of NA species using Ag-ion SPE is a valuable method for extracting individual NA species that are of great interest for environmental toxicology and wastewater treatment research, to conduct species-specific studies. Furthermore, the separated NA species on the milligram level could be widely used as the standard materials for environmental monitoring of NAs from various contamination sites.

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 score0.049
Threshold uncertainty score0.534

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 studies0.0000.001
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 head0.006
GPT teacher head0.275
Teacher spread0.270 · 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

Citations30
Published2016
Admission routes2
Has abstractyes

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