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Record W2256467250 · doi:10.14447/jnmes.v15i4.51

Electrochemical Behavior of (Zn, Mn)-Al Nitrated Hydrotalcites

2012· article· en· W2256467250 on OpenAlexaffvenue
Álvaro Sampieri, Jorge Vázquez-Arenas, Ignacio González, Geolar Fetter, Heriberto Pfeiffer, María-Elena Villafuerte, P. Bosch

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2012
Typearticle
Languageen
FieldMaterials Science
TopicLayered Double Hydroxides Synthesis and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHydrotalciteTernary operationManganeseElectrochemistrySpinelCyclic voltammetryLamellar structureZincChemistryRedoxInorganic chemistryOxidation processMaterials scienceCatalysisCrystallographyChemical engineeringMetallurgyPhysical chemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

The electrochemical behavior of synthetic binary, Zn-Al and Mn-Al, and ternary (Zn-Mn)-Al hydrotalcites (HT) was studied by cyclic voltammetry in alkaline conditions (pH≡12). The Zn-Al HT characterization revealed two irreversible and continuous oxidation processes: i) Zn0|Zn2+ and ii) Zn0|ZnO. On the other hand, the binary HT containing Mn presented a reversible behavior for the oxidation-reduction process Mn4+|Mn3+. The same oxidation-reduction processes were observed in the ternary HT. However, variations in the reduction-oxidation process were detected by XRD for the ternary HT as a result of spinel formation. These results could also be influenced due to a higher accessibility of manganese in HT since the morphology of hydrotalcite (lamellar structure) provides a regular distribution of Mn atoms interacting with Zn atoms through hydroxyl bridges.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.279
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), 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
Published2012
Admission routes2
Has abstractyes

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