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Record W4200259369 · doi:10.1002/admi.202101423

Formation of MoO<sub>3</sub>/Organic Interfaces

2021· article· en· W4200259369 on OpenAlexaff
Yan Wu, Juntao Hu, Zhenxin Yang, Dengke Wang, Tao Zhang, Nan Chen, Di Wu, Zheng‐Hong Lu

Bibliographic record

VenueAdvanced Materials Interfaces · 2021
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceMolybdenum trioxideBiphenylBenzidineX-ray photoelectron spectroscopyBenzeneMolybdenumOLEDTransition metalGlass transitionSputteringLayer (electronics)Analytical Chemistry (journal)Chemical engineeringThin filmOrganic chemistryCatalysisNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Abstract Molybdenum trioxide (MoO 3 ) has been extensively used in numerous organic semiconductor devices for hole injection and extraction. In this paper, photoelectron spectroscopy combined with cleavage and sputter depth profile has been used to probe the structures of buried MoO 3 /organic semiconductor interfaces. Organics used in this work include: tris(4‐carbazoyl‐9‐ylphenyl)amine (TCTA), N,N′‐bis(naphthalene‐l‐yl)‐N,N′‐bis(phenyl)benzidine (NPB), 4,4′‐bis(carbazol‐9‐yl)‐2,2′‐biphenyl (CBP), and 1,3‐bis(N‐carbazolyl) benzene (mCP). It is found that there are two distinct types of interfaces: sharp interfaces (type‐I) where the oxide layer has limited or no diffusion when deposited on organics that have a high glass transition temperature such as TCTA and NPB; mixed interfaces (type‐II) where the formation of interfaces is followed by significant diffusion and reaction on organics having low glass transition temperatures such as CBP and mCP. The causes for these two types of interfaces are 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.003
Threshold uncertainty score1.000

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 communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 spread0.227 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

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