MétaCan
Menu
Back to cohort
Record W2067520469 · doi:10.1021/ie049636f

Degradability of Iron(III)-aminopolycarboxylate Complexes in Alkaline Media:  Statistical Design and X-ray Photoelectron Spectroscopy Studies

2004· article· en· W2067520469 on OpenAlexafffund
Simon Piché, Faı̈çal Larachi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2004
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFerricChemistryIonic strengthAlkalinityFactorial experimentChelationInorganic chemistrySulfateNuclear chemistryAqueous solutionOrganic chemistry

Abstract

fetched live from OpenAlex

Use of ferric-aminopolycarboxylate complexes for odor control via the oxidative scrubbing of H 2 S and CH 3 SH contained in pulp and paper noncondensable gas emissions is evoked as potentially beneficial from the standpoint of iron-sequestration and protection against precipitation in the alkaline environments characteristic of the Kraft mill sulfate-pulp processes. In this study, the degradability of two ferric-aminopolycarboxylate complexes in alkaline solutions was investigated by means of replicated four-factor three-level fixed-effects completely randomized factorial (2 × 3 4 ) designs. Expressed in terms of ferric-ethylenediaminotetraacetate (Fe 3+ EDTA 4- ) and ferric- trans -1,2-diaminocyclohexanetetraacetate (Fe 3+ CDTA 4- ) daily degradation rates, the degradability response was monitored via UV−vis spectrophotometry as a function of temperature ( T = 25, 40, 55 °C), alkalinity (pH = 8, 9, 10), ionic strength ( I = 0.025, 0.1, 0.5 M) and ferric concentration ( C Fe = 175, 280, 450 μM). Analysis-of-variance (ANOVA) of the factorial design suggests that pH and temperature are the main factors increasing Fe 3+ EDTA 4- and Fe 3+ CDTA 4- degradation rates. To a lower extent, ionic strength and ferric chelate concentration also promote degradation. At the most severe factor-level combinations ( T = 55 °C, pH = 10, and I = 0.5 M), up to 40% of Fe 3+ CDTA 4- and 54% of Fe 3+ EDTA 4- degraded after 1 day, confirming that CDTA is a superior chelating agent against iron precipitation in alkaline solutions. The brownish fresh-state Fe 3+ EDTA 4- or Fe 3+ CDTA 4- solutions evolved with degradation into turbid solutions whereof the precipitated solid was recovered and its surface probed through X-ray photoelectron spectroscopy (XPS). XPS revealed that the solid degradation product was inorganic and mostly contributed by Fe(OH) 3 . It was, however, not possible to identify which one of the organometallic complex degradation or the ferric dechelation was responsible for iron(III) hydroxide formation since both routes can contribute to its formation.

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)0.001
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 score0.042
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.112
GPT teacher head0.352
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.

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
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicMetal Extraction and BioleachingFrench-language works237,207