MétaCan
Menu
Back to cohort
Record W2463214277 · doi:10.5935/0103-5053.20160039

UV-Assisted Digestion of Petrochemical Industry Effluents Prior to the Determination of Zn, Cd, Pb and Cu by Differential Pulse Anodic Stripping Voltammetry

2016· article· en· W2463214277 on OpenAlexaff
Daniela Domingos, Maria de Lourdes S. Ferreira Neta, Ana Rosa C. G. Massa, Márcio V. Rebouças, Leonardo S.G. Teixeira

Bibliographic record

VenueJournal of the Brazilian Chemical Society · 2016
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsEspace pour la vie
FundersFundação de Amparo à Pesquisa do Estado da BahiaConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsAnodic stripping voltammetryStripping (fiber)PetrochemicalEffluentVoltammetryAnodeEnvironmental chemistryChemistryEnvironmental scienceMaterials scienceElectrodeEnvironmental engineeringElectrochemistry

Abstract

fetched live from OpenAlex

A petrochemical effluent is usually a matrix of very high complexity and composition variability, requiring robust and suitable methods for routine analysis. In this paper, the feasibility of applying a voltammetric technique for the determination of metals species in the petrochemical industry effluent was demonstrated after UV-assisted digestion procedure. Voltammetric (electrolyte volume, deposit time, pulse time, pulse amplitude and scan rate) and digestion variables (hydrogen peroxide volume, nitric acid volume and digestion time) were studied using a 2-level factorial design. The developed voltammetric method using anodic stripping voltammetry (ASV) presented limits of quantification of 11, 5, 15 and 5 g L -1 for Zn, Cd, Pb and Cu, respectively, and was effective to analyze petrochemical effluents after UV-digestion.

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 score0.016
Threshold uncertainty score0.392

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 science0.0010.000
Research integrity0.0000.001
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 head0.239
Teacher spread0.232 · 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

Explore more

Same venueJournal of the Brazilian Chemical SocietySame topicElectrochemical Analysis and ApplicationsFrench-language works237,207