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Record W2889032436 · doi:10.14447/jnmes.v15i1.85

Electrochemical Activation of Metal Hydride Alloy by Inclusion of Nickel and Palladium Nanoparticles

2011· article· en· W2889032436 on OpenAlexvenueno aff
Miguel Rivera, S.A. Gamboa, P.J. Sebastián

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2011
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsnot available
Fundersnot available
KeywordsHydrideMaterials scienceNanoparticlePalladiumAlloyCatalysisElectrochemistryNickelMetalHydrogenChemical engineeringHydrogen storageInorganic chemistryColloidMetallurgyNanotechnologyChemistryPhysical chemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Nickel and palladium nanoparticles were obtained by colloidal dispersion. Chemical reduction was used to obtain good quality nanoparticles showing electrocatalytic characteristics for improving the electrochemical hydrogen content in typical metal hydride at the initial stage of absorption process. The particle size and distribution of the colloidal nanoparticles were calculated by analyzing TEM images. The colloidal nanoparticles obtained were impregnated onto LaNi5-xMx type metal hydride alloy via catalytic dipping. The impregnated metal hydride alloy was characterized by SEM, AFM and EDS to obtain quasi-quantitative measurements of the position and concentration of the agglomerated colloidal nanoparticles forming nano-clusters onto de surface of the metal hydride alloy. Electrochemical characterization showed the enhancement of absorbed hydrogen content in the metal hydride due to the presence of agglomerated nanoparticles and the localized catalytic activity of Pd more than that of Ni nano-clusters.

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 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 score0.001
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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