MétaCan
Menu
Back to cohort
Record W2049916440 · doi:10.1063/1.3432447

A metallic molybdenum suboxide buffer layer for organic electronic devices

2010· article· en· W2049916440 on OpenAlexaff
Mark Greiner, Michael G. Helander, Zhecheng Wang, Wing Man Tang, J. Qiu, Zheng‐Hong Lu

Bibliographic record

VenueApplied Physics Letters · 2010
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMolybdenum trioxideBuffer (optical fiber)OxideMaterials scienceMolybdenumMetalStoichiometryLayer (electronics)Inorganic chemistryValence (chemistry)Analytical Chemistry (journal)ChemistryNanotechnologyMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Molybdenum trioxide (MoO3) is commonly used as a buffer layer in organic electronic devices to improve hole-injection. However, stoichiometric MoO3 is an insulator, and adds a series resistance. Here it is shown that a MoO3 buffer layer can be reduced to form a metallic oxide buffer that exhibits more favorable energy-level alignment with N,N′-diphenyl-N,N′-bis-(1-naphthyl)-1-1′-biphenyl-4,4′-diamine (α-NPD) than does MoO3. This buffer layer thus provides the conductivity of a metal with the favorable energy alignment of an oxide. Photoemission shows the reduced oxide contains Mo4+ and Mo5+, with a metallic valence band structure similar to MoO2.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.233
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0010.000
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 head0.007
GPT teacher head0.207
Teacher spread0.200 · 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

Citations90
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueApplied Physics LettersSame topicElectrocatalysts for Energy ConversionFrench-language works237,207