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Record W2329110941 · doi:10.2166/wst.2014.282

Impact of polymeric membrane filtration of oil sands process water on organic compounds quantification

2014· article· en· W2329110941 on OpenAlexafffund
Ahmed Moustafa, Eun‐Sik Kim, Alla Alpatová, Nian Sun, D. Scott Smith, Seoktae Kang, Mohamed Gamal El‐Din

Bibliographic record

VenueWater Science & Technology · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsWilfrid Laurier UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsFiltration (mathematics)Oil sandsMembraneEnvironmental scienceProcess (computing)ChemistryWaste managementEnvironmental chemistryMaterials scienceEngineeringAsphaltComputer science

Abstract

fetched live from OpenAlex

The interaction between organic fractions in oil sands process-affected water (OSPW) and three polymeric membranes with varying hydrophilicity (nylon, polyvinylidene fluoride and polytetrafluoroethylene) at different pHs was studied to evaluate the impact of filtration on the quantification of acid-extractable fraction (AEF) and naphthenic acids (NAs). Four functional groups predominated in OSPW (amine, phosphoryl, carboxyl and hydroxyl) as indicated by the linear programming method. The nylon membranes were the most hydrophilic and exhibited the lowest AEF removal at pH of 8.7. However, the adsorption of AEF on the membranes increased as the pH of OSPW decreased due to hydrophobic interactions between the membrane surfaces and the protonated molecules. The use of ultra pressure liquid chromatography-high resolution mass spectrometry (UPLC/HRMS) showed insignificant adsorption of NAs on the tested membranes at pH 8.7. However, 26±2.4% adsorption of NAs was observed at pH 5.3 following the protonation of NAs species. For the nylon membrane, excessive carboxylic acids in the commercial NAs caused the formation of negatively charged assisted hydrogen bonds, resulting in increased adsorption at pH 8.2 (25%) as compared to OSPW (0%). The use of membranes for filtration of soluble compounds from complex oily wastewaters before quantification analysis of AEF and NAs should be examined prior to application.

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 score0.006
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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