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Record W1994390480 · doi:10.1155/s1110662x04000121

Photochemical oxidation of short‐chain polychlorinated <i>n</i>‐alkane mixtures using H<sub>2</sub>O<sub>2</sub>/UV and the photo‐Fenton reaction

2004· article· en· W1994390480 on OpenAlexafffund
Ken J. Friesen, Taha M. Elmorsi, Alaa S. Abd‐El‐Aziz

Bibliographic record

VenueInternational Journal of Photoenergy · 2004
Typearticle
Languageen
FieldEngineering
TopicEnvironmental remediation with nanomaterials
Canadian institutionsUniversity of Winnipeg
FundersManitoba Hydro
KeywordsChemistryIrradiationDegradation (telecommunications)AlkaneMineralization (soil science)PhotochemistryChlorideEnvironmental chemistryCatalysisOrganic chemistryNitrogen

Abstract

fetched live from OpenAlex

The photochemical oxidation of a series of short‐chain polychlorinated n ‐alkane (PCA) mixtures was investigated using H 2 O 2 /UV and modified photo‐Fenton conditions (Fe 3+ /H 2 O 2 /UV) in both Milli‐Q and lake water. All PCA mixtures, including chlorinated (Cl 5 to Cl 8 ) decanes, undecanes, dodecanes and tridecanes degraded in 0.02 M H 2 O 2 /UV at pH 2.8 in pure water, with 80 ± 4 % disappearance after 3 h of irradiation using a 300 nm light source. Degradation was somewhat enhanced under similar conditions but in natural water. The modified photo‐Fenton system was more effective in degrading PCAs, with 72% and 80% disappearance of chlorinated decanes in 45 min of irradiation in pure and natural water, respectively. Carbon chain‐length had minimal effect on degradation rates; however, increased degree of chlorination (from Cl 5 to Cl 8 ) resulted in slower initial degradation rates and less complete conversion after 3 h of irradiation. Three hours of irradiation in natural water/H 2 O 2 /UV resulted in 95% degradation of parent PCAs accompanied by 93% release of chloride ion. Quantitative dechlorination, which may be indicative of complete mineralization, suggests that this is an effective water remediation technique for PCAs.

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 score0.012
Threshold uncertainty score0.860

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Citations8
Published2004
Admission routes2
Has abstractyes

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