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Record W2509673721 · doi:10.2118/181294-ms

Effect of Date Palm Fiber (DPF) Sorbent Age on Sorption of Crude Oil During Oil Spill Cleanup: Gas Chromatography Study

2016· article· en· W2509673721 on OpenAlexaff
Mohammad Ibrahim Nasir, Zainab Mohsen Hameed, Paul A. Charpentier, H. A. Neamh, Ayyaz Muhammad, Zaheer Abbas

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2016
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsWestern University
Fundersnot available
KeywordsSorbentSorptionAdsorptionFiberChromatographyGas chromatographyChemical engineeringMaterials sciencePulp and paper industryChemistryWaste managementComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract One of the most efficient means for the removal of spilled oil from either land or sea is the use of sorbent. Date Palm Fibers (DPF) is a natural sorbent that exhibits good sorption characteristics although the relationship between fiber age and oil absorption has not been reported. Oil spill remediation process is presented and mechanism and selectivity of sorption was discussed. Oil spill simulation was carried out by placing 40 gm crude oil on surface of about 800 mL water at 1000 mL beaker. The removal of crude oil from water by 1 gm raw DPF as sorbent was investigated by batch sorption after varying contact times (5-120 min), oil film thickness (7-47 mm) and the use of two different age fibers (old and fresh fibers) at 5 min drainage time. Gas chromatography study of oil involved in the sorption process was done to determined the molecules sorbed by DPF sorbent. Scanning Electron Microscopy analysis for DPF was also take place. OSC of the two DPF sorbent increased with increasing contact times being 4.53 gm• oil/gm• sorbent for 5 min contact time while for fresh fiber was 6.286 gm• oil/gm• sorbent. The sorption rate was very fast for both sorbents. At 2 min sorption times we get 4.963 and 6.737 gm. oil/gm. sorbent for the aged and fresh fibers respectively at 2 min draining time. The results show that fresh fibers sorbed more oil than old fibers. This is attributed to the new fibers having a lower crystalline structure than the old fibers. The fresh fibers have more cavities and hollows than the old one as shown by Scanning Electron Microscopy, in which cross sectional images show multi lumens and the side images has a rough surface with large size cavities. Analysis of sorbed oils by new DPF with gas chromatography after four successive sorptions of the same crude oil at sorption time of 30 min to identify the oil components sorbed. The results showed that C2-C4 compounds were completely sorbed by DPF during the four sorptions process using 1 gm. each, e.g. total 4 gm. After 4 sorption cycles, only 4.80% of pentane remained while C6-C8 compounds were reduced by 63.70%. This works showed that the DPF have a good performance as low cost, biodegradable and environmental friendly sorbent for the removal of oil from water with excellent selectivity toward small molecules compounds. The fresh fiber prove to be superior sorbent for crude oil over the old one. Since PDF are naturally weaved and rectangular mesh net of about 30×40 cm2 area, it will have high sorption efficiency and easily removed from spill site.

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)0.001
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 score0.022
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.269
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

Citations3
Published2016
Admission routes1
Has abstractyes

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