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Record W4410507120 · doi:10.1088/2053-1583/adda02

Rapid nucleation of ZnO on MoS<sub>2</sub> and WS<sub>2</sub> using an atmospheric-pressure spatial atomic layer deposition system

2025· article· en· W4410507120 on OpenAlexaff
Poojitha Durgamahanti, Osamah Kharsah, Jixi Zhang, Denys Vidish, Farman Ullah, Yasaman Jarrahizadeh, André Maas, Rodney D. L. Smith, A. Lorke, Kevin P. Musselman

Bibliographic record

Venue2D Materials · 2025
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsNational Institute for NanotechnologyUniversity of Waterloo
FundersDeutsche Forschungsgemeinschaft
KeywordsAtomic layer depositionNucleationLayer (electronics)Materials scienceDeposition (geology)Atmospheric pressureNanotechnologyMeteorologyPhysicsThermodynamicsGeology

Abstract

fetched live from OpenAlex

Abstract Uniform deposition of metal oxides on 2D materials, while preserving their structural integrity, is a crucial step to realize the integration of 2D materials in practical devices. In this study, we demonstrate the rapid nucleation of ZnO using atmospheric-pressure spatial chemical vapor deposition (AP-SCVD) on 2D transition metal dichalcogenides MoS 2 and WS 2 . The high precursor partial pressure and uniform precursor delivery afforded by the AP-SCVD process, as compared to conventional atomic layer deposition (ALD), led to rapid ZnO nucleation on both CVD-grown MoS 2 and WS 2 in as little as 5 AP-SCVD oscillations and complete film closure was achieved on CVD-grown WS 2 flakes in less than 60 AP-SCVD oscillations. The ZnO nuclei formed larger interconnected clusters on MoS 2 , whereas more-isolated islands were formed on the WS 2 . Raman and photoluminescence (PL) spectroscopy revealed that AP-SCVD is a benign process that does not damage the underlying 2D materials and rather helps to passivate defects via oxygen/water adsorption from the air, when performed in an appropriate temperature window. Deposition of the ZnO was found to impact the optical and structural properties of CVD-grown MoS 2 and WS 2 differently. For the MoS 2 –ZnO heterostructure, electron doping and strain dominate, resulting in a reduction in the PL of MoS 2 , whereas for the WS 2 –ZnO, strain and dielectric screening have a larger impact, resulting in an enhanced PL.

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)
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 score0.004
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 communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.240
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

Citations3
Published2025
Admission routes1
Has abstractyes

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