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Record W1596172563 · doi:10.3968/3734

Spectral Analysis of Catalytic Oxidation and Degradation of Bromophenol Blue at Low pH with Potassium Dichromate

2013· article· en· W1596172563 on OpenAlexvenueno aff
Rafia Azmat, Zahida Khalid, Marium Haroon, Khalida Perveen Mehar

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsnot available
Fundersnot available
KeywordsBromophenol bluePotassium dichromateSodium oxalateChemistryNuclear chemistryOxalic acidPotassium carbonateChromate conversion coatingSodium carbonateInorganic chemistryOxalateCatalysisPotassium chromateDegradation (telecommunications)SodiumOrganic chemistryChromatographyCorrosionChromium

Abstract

fetched live from OpenAlex

Abstract This research investigated the efficacy of potassium dichromate (K2Cr2O7), ultraviolet (UV) solar irradiation and UV in combination with two diprotic acid i-e sulphuric and oxalic acid (UV chromate/carbonate), for decolorizing bromophenol blue (BPB). The results suggested that alone UV and solar exposure was the poor decolorizer of the dye waste water. Up to 10% color removal with alone UV and solar treatment were achieved which indicated that, only solar and UV were not effective for dye removal even though UV was slightly more effective as compared to solar one. The decline reaction rate was observed as a result of increased concentration of dye. Increase in concentration of dichromate showed two peaks at 592 and 515 which showed that bromophenol degraded into two smaller components through complex formation. Addition of sodium carbonate as a catalyst in dye chromate-oxalate system found to be effective in degradation of BPB with reduced time period. The reaction was rapid and almost maximum of the dye converted into CO2. Research outcome suggests that chromate-oxalate system is very effective techniques for reducing color of dye waste water for safety of aquatic environment. Reaction pathway of oxidation of BPB is discussed in the relevant section of the paper.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.008
Science and technology studies0.0000.005
Scholarly communication0.0000.009
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 head0.004
GPT teacher head0.244
Teacher spread0.240 · 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.

Study designObservational
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

Citations11
Published2013
Admission routes1
Has abstractyes

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