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Record W2325808289 · doi:10.1021/jp510234f

Theory, Substantiation, and Properties of Novel Reversible Electrocatalysts for Oxygen Electrode Reactions

2015· article· en· W2325808289 on OpenAlexaff
Jelena M. Jakšić, Feihong Nan, Γεώργιος Παπακωνσταντίνου, Gianluigi A. Botton, Milan M. Jakšić

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2015
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElectrocatalystChemistryDissociation (chemistry)Reversible hydrogen electrodeCatalysisRedoxOxygen evolutionInorganic chemistryOxideMoleculeElectrodeElectrochemistryPhysical chemistryWorking electrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Hypo-d–(f)-oxides of transition elements (d ≤ 5) usually feature decisive and highly pronounced effects of spontaneous adsorptive dissociation of water molecules, as the main and initial thermodynamic precondition state for the reversible latent storage and spillover properties of primary oxides (Pt–OH, Au–OH), otherwise indispensable ingredients in electrocatalysis for the oxygen electrode reactions. The higher the altervalent number (or capacity) of the former, and when mostly further advanced for the proper mixed valence hypo-d–(f)-oxide supports, the higher the overall (electro)catalytic yields primarily for cathodic oxygen reduction (ORR) and its anodic evolution (OER). In fact, cyclic voltammetry revealed the interrelated redox properties of the primary (Pt–OH) and surface (Pt═O) oxides between the cathodic hydrogen and anodic oxygen evolving limits, though the former has already been for longer known as the intermediate state from hydrogen oxidation in heterogeneous Doeberriner reaction upon Pt catalyst, and as being water molecules self-catalyzed (Ertel). Such interfering interrelated and autocatalytic species substantially define electrocatalytic properties of plain (Pt) or noninteractive supported noble metals (Pt/C), along the potential axis, and within some range even make them highly polarizable. Meanwhile, the latter can be continuously and successfully electrocatalytically depolarized and maintained reactivated. Such spontaneously renewable activation and maintenance of the reversible electrocatalytic state for the oxygen electrode reactions all along such cyclic voltammograms is the main Sir William Grove target challenge of the present study. In such a respect, continuously and spontaneously renewable adsorptive water molecule dissociation effectively means and enables the latent storage and electrocatalytic spillover properties of the primary oxide(s) for the reversible oxygen electrode (ROE) behavior, and these have been identified and substantiated, back and forth, all along the potential axis between hydrogen and oxygen evolving limits. Such advanced electrocatalytic properties imply selective grafting of interactive (SMSI, strong metal–support interaction) nanostructured hyper-d-Pt (Au, RuPt) clusters upon individual and/or preferably composite mixed valence hypo-d–(f)-oxide supports. The latter then feature the extra high stability, pronounced electronic conductivity, and many other d-electronic-based metal properties mostly arising and being established upon the hypo–hyper-d–d–(f)-interelectronic bonding effect, along with and based upon spontaneous dissociative water molecule adsorption upon exposed oxide support surfaces, thereby yielding renewable primary oxide latent storage by simple continuous water vapor supply and imposed characteristic membrane type hydroxide ion surface migration. Migrating hydroxide, as individual species, under imposed polarization transfers its prevailing part of electron to the metallic electrocatalyst, hence resulting as the Pt–OH (Au–OH) dipole, and by the surface repulsion obeys reversible spillover distribution and imposes the electrocatalytic ROE properties all over the catalyst surface and DL pseudocapacitance charging and discharging, as well. The strong adsorptive surface oxide (Pt═O → 1) deposition out of the primary oxide (Pt–OH → 0) irreversible disproportionation thereby imposes unusually high reaction polarization of Pt, Au, Pd, and all other noble and transition d-metals within a very broad (600 mV, and even broader) potential range and, thereby, in general, mostly pronounced polarizable noncatalytic properties for oxygen electrode (ORR, OER) reactions. Thus, the strong interactive and selective hypo–hyper-d–d-interelectronic grafting bonding of nanostructured individual (Pt) or prevailing hyper-d-intermetallic phase (MoPt 3; HfPd 3 ) cluster catalysts on altervalent and mixed-valence hypo-d–(f)-oxide supports, as substantially and typically based upon the metallic d–d- or d–f-interelectronic bonding strengths and SMSI features, provide and keep just inferred basically all (inter)metallic properties of composite electrocatalysts, the primary oxide latent storage, and enhanced spillover and thereby enable approaching their reversible (electro)catalytic properties and optimization for the ROE. The reversibly revertible alterpolar bronze behaves (Pt/H x NbO 5 ⇔ Pt/Nb(OH) 5, x ≈ 0.3) as the thermodynamic equilibrium alterpolar state, and thereby substantially advanced electrocatalytic properties of these composite interactive electrocatalysts for both oxygen (ORR, OER) and hydrogen (HOR, HER) electrode reactions, consequently, have been inferred as spontaneously altering and strong spillover features, in particular unique and superior for the revertible (PEMFC versus WE (water electrolysis)) cells.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.021
GPT teacher head0.235
Teacher spread0.214 · 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 designTheoretical or conceptual
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".

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Citations18
Published2015
Admission routes1
Has abstractyes

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