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Record W2772196603 · doi:10.1021/jacs.7b11064

Photodecomposition of Metal Nitrate and Chloride Compounds Yields Amorphous Metal Oxide Films

2017· article· en· W2772196603 on OpenAlexafffund
Jingfu He, David M. Weekes, Wei Cheng, Kevan E. Dettelbach, Aoxue Huang, Tengfei Li, Curtis P. Berlinguette

Bibliographic record

VenueJournal of the American Chemical Society · 2017
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of British Columbia
FundersCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCanada Research ChairsCanadian Institute for Advanced Research
KeywordsAmorphous solidX-ray photoelectron spectroscopyChemistryNickelOxideSubstrate (aquarium)MetalFourier transform infrared spectroscopyAmorphous metalScanning electron microscopeInorganic chemistryInfrared spectroscopyChemical engineeringAnalytical Chemistry (journal)Materials scienceCrystallographyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

(where M = Fe, Co, Ni, Cu, or Zn) to form uniform, amorphous films of metal oxides. This process does not elevate the temperature of the substrate and thus conformal films can be coated on a range of substrates, including rigid glass and flexible plastic. The formation of the oxide films were confirmed by a combination of powder X-ray diffraction, X-ray photoelectron spectroscopy, X-ray fluorescence spectroscopy, Fourier transform infrared spectroscopy and scanning electron microscopy techniques. Amorphous oxide films of iron, nickel and a combination of iron and nickel demonstrated oxygen evolution reaction electrocatalytic activities commensurate with films of the same compositions prepared by widely used electrodeposition and sputtering methods. These results illuminate a potential route to amorphous oxides at scale using simple metal precursors without vacuum or heat.

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)0.000
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
Metaresearch0.0000.000
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)0.0010.001

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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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

Citations20
Published2017
Admission routes2
Has abstractyes

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Same venueJournal of the American Chemical SocietySame topicElectrocatalysts for Energy ConversionFrench-language works237,207