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Record W2067870155 · doi:10.1002/cjce.5450800511

Preparation and Kinetic Considerations for the Dissolution of Cr‐substituted Iron Oxides in Reductive‐complexing Formulations

2002· article· en· W2067870155 on OpenAlexvenueno aff
J. Manjanna, G. Venkateswaran

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2002
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsnot available
Fundersnot available
KeywordsDissolutionHematiteChemistryMagnetiteOxideKinetic energyCitric acidKineticsMass fractionInorganic chemistryParticle sizeAscorbic acidIron oxideMaterials scienceMineralogyPhysical chemistryMetallurgyOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract The dissolution rate coefficients of Cr‐substituted (0‐20 at.% Cr) iron oxides viz. hematite and magnetite were determined by using an inverse cubic rate (ICR) law applicable for spherical particles as well as by a general kinetic equation (GKE) applicable for polydispersed particles. An attempt is made to compare both the treatments for different kinds of dissolution profiles obtained by employing oxides with narrow particle size distribution in V(II)‐EDTA and citric acid‐EDTA‐ascorbic acid formulations at 353±5K. The dissolution profiles could be classified into three types based on the nature of oxide and formulations. It is observed that both ICR and GKE treat the dissolution course as a function of decrease in fraction of undissolved mass, m/m 0 . The dissolution rate coefficients determined by ICR and GKE have shown the similar trend of decrease with increasing Cr content of the oxides and was ascribed to lattice stabilization.

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 score0.132
Threshold uncertainty score0.180

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 head0.025
GPT teacher head0.234
Teacher spread0.208 · 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

Citations11
Published2002
Admission routes1
Has abstractyes

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