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Record W2929436140 · doi:10.1088/1361-6463/ab1520

Effects of Au catalyst geometry on Ge films grown laterally on Si using the vapor–liquid–solid mechanism

2019· article· en· W2929436140 on OpenAlexafffund
Weizhen Wang, Yao Tong, Nathaniel J. Quitoriano

Bibliographic record

VenueJournal of Physics D Applied Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcGill University
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsCatalysisNucleationMaterials scienceGrain sizeEpitaxyCrucible (geodemography)CrystallographyChemical engineeringNanotechnologyChemistryComposite materialOrganic chemistryComputational chemistryLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract A lateral epitaxial growth technique has been demonstrated to grow high-quality Ge micro-films on Si at low temperatures using the vapor–liquid–solid mechanism. These Ge films were grown within a confined structure to foster horizontal growth in the presence of Au catalyst. In this work the size and geometric shape of the Au catalyst were shown to impact the film size and morphology. In particular, a general trend was observed, as the size of Au catalyst increased the Ge film size initially increased as well until the Ge film size plateaued and eventually decreased. This phenomenon is described by a model, which is a function of Au catalyst size and GeH 4 dose and can be used to estimate the final Ge film size. In general, a large-sized Au catalyst absorbs more Ge because of its large vapor–liquid interface but it also requires more Ge to saturate the liquid, and therefore this fact results in a peak in the plot of the Ge film size versus the Au size. In addition, a large GeH 4 dose due to more absorption of GeH 4 leads to multiple nucleation sites in a small Au catalyst, while a micro-crucible with a larger Au volume or reduced vapor–liquid interface can help to realize single nucleation. These results helped in designing two-opening Au catalysts with asymmetric sides, which preferentially nucleates a large crystal near the wider side.

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 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 score0.165
Threshold uncertainty score0.831

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)0.0000.000

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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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.

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

Citations5
Published2019
Admission routes2
Has abstractyes

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