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Record W2233033807 · doi:10.1063/1.4939744

A simple rule for determining the band offset at CH3NH3PbI3/organic semiconductor heterojunctions

2016· article· en· W2233033807 on OpenAlexafffund
Emmanuel S. Thibau, Adrian Llanos, Zheng‐Hong Lu

Bibliographic record

VenueApplied Physics Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsHeterojunctionSemiconductorOrganic semiconductorOptoelectronicsMaterials scienceThin filmPhotoemission spectroscopyIonization energyBand offsetWide-bandgap semiconductorValence (chemistry)NanotechnologyBand gapIonizationChemistryValence bandX-ray photoelectron spectroscopyChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Organo-metal halide perovskites have recently emerged as a highly promising class of semiconductors for optoelectronic device applications. Integrating these hybrid materials within organic molecular thin film devices is key to fabricate functional devices. By evaporating ultra-thin films of organic semiconductor on thermally evaporated CH3NH3PbI3 and using in-situ ultraviolet photoemission spectroscopy, we directly measure the interfacial energy offset between CH3NH3PbI3 valence band maximum and the highest occupied molecular orbital for 5 different archetypal organic semiconductors. It is found that the energy offsets scale linearly as a function of the ionization energies of the organic semiconductors. The experimental data are in excellent agreement with a theoretical model for ideal semiconductor heterojunctions.

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)0.004
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.205
Teacher spread0.192 · 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

Citations22
Published2016
Admission routes2
Has abstractyes

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