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Record W3134222398 · doi:10.1002/cmtd.202000069

In situ X‐ray Absorption Spectroscopy of Platinum Electrocatalysts

2021· article· en· W3134222398 on OpenAlexafffund
David J. Morris, Peng Zhang

Bibliographic record

VenueChemistry - Methods · 2021
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsDalhousie University
FundersCanadian Light Source
KeywordsNanomaterial-based catalystPlatinumCatalysisX-ray absorption spectroscopyCharacterization (materials science)Absorption spectroscopyMaterials scienceNanotechnologyIn situAbsorption (acoustics)SpectroscopyCarbon monoxideChemical engineeringChemistryOrganic chemistryPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract Platinum nanocatalysts have shown high performance in a wide variety of electrocatalytic reactions, making them the focus of many studies. High quality characterization results are vital for the proper understanding of a catalyst's structure and properties, allowing for further discoveries to be made. X‐ray absorption spectroscopy is a powerful characterization tool, permitting both the local structure and electronic properties to be determined for a sample of interest. This can be taken further by collecting in situ measurements, which offer the unique advantage of characterization results collected in real‐time while the catalytic reaction is taking place. This review summarizes recent studies which utilized in situ X‐ray absorption spectroscopy to characterize platinum nanocatalysts, highlighting the important structural parameters and electronic properties determined under the real catalytic reaction conditions. Specific examples of catalysts for use in the oxygen reduction reaction, chlorine evolution reaction, and carbon monoxide oxidation are discussed in detail. Future prospects for work in this field are also highlighted and discussed.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.227
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.349
Teacher spread0.332 · 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.

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

Citations30
Published2021
Admission routes2
Has abstractyes

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