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Record W3208664426 · doi:10.26434/chemrxiv.5850003.v1

Workfunction of Al-Doped ZnO Films Deposited by Atomic Layer Deposition

2018· preprint· en· W3208664426 on OpenAlexaff
Peter G. Gordon, Goran Bačić, Gregory P. Lopinski, Seán T. Barry

Bibliographic record

VenueChemRxiv · 2018
Typepreprint
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsCarleton University
Fundersnot available
KeywordsAtomic layer depositionMaterials scienceDopingRecipeElectrical resistivity and conductivityLayer (electronics)Stack (abstract data type)Deposition (geology)NanotechnologyThin filmOptoelectronicsChemical engineeringAnalytical Chemistry (journal)ChemistryComputer scienceOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Al-doped ZnO (AZO) is a promising earth-abundant alternative to Sn-doped In 2 O 3 (ITO) as an n-type transparent conductor for electronic and photovoltaic devices; AZO is also more straightforward to deposit by atomic layer deposition (ALD). The workfunction of this material is particularly important for the design of optoelectronic devices. We have deposited AZO films with resistivities as low as 1.1 x 10 -3 Ωcm by ALD using the industry-standard precursors trimethylaluminum (TMA), diethylzinc (DEZ), and water at 200 ◦ C. These films were transparent and their elemental compositions showed reasonable agreement with the pulse program ratios. The workfunction of these films was measured using a scanning Kelvin Probe (sKP) to investigate the role of aluminum concentration. In addition, the workfunction of AZO films prepared by two different ALD recipes were compared: a “surface” recipe wherein the TMA was pulsed at the top of each repeating AZO stack, and a interlamellar recipe where the TMA pulse was introduced halfway through the stack. As aluminum doping increases, the surface recipe produces films with a consistently higher workfunction as compared to the interlamellar recipe. The resistivity of the surface recipe films show a minimum at a 1:16 Al:Zn atomic ratio and using an interlamellar recipe, minimum resistivity was seen at 1:19. The film thicknesses were characterized by ellipsometry, chemical composition by EDX, and resistivity by four-point probe.

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 score0.040
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.250
Teacher spread0.223 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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