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Record W4389237336 · doi:10.3390/coatings13122030

High-Rate Epitaxial Growth of Silicon Using Electron Beam Evaporation at High Temperatures

2023· article· en· W4389237336 on OpenAlexfundno aff
Marit Stange, Tor Olav Sunde, Runar Dahl-Hansen, Kalpna Rajput, Joachim Seland Graff, Branson D. Belle, A. Ulyashin

Bibliographic record

VenueCoatings · 2023
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
FundersInstitute of Gender and HealthNorges ForskningsrådUniversitetet i Oslo
KeywordsMaterials scienceWaferIngotRaman spectroscopySiliconEvaporationElectron beam physical vapor depositionAnalytical Chemistry (journal)Electron backscatter diffractionCrystallinityMicrostructureChemical vapor depositionOptoelectronicsComposite materialOpticsChemistry

Abstract

fetched live from OpenAlex

This paper describes the high-rate (~1.5 μm/min) growth of Si films on Si supporting substrates with (100) crystallographic orientation at 600 °C, 800 °C, and 1000 °C in a vacuum environment of ~1 × 10−5 mbar using electron beam (e-beam) evaporation. The microstructure, crystallinity, and conductivity of such films were investigated. It was established that fully crystalline (Raman spectroscopy, EBSD) and stress-free epi-Si layers with a thickness of approximately 50 µm can be fabricated at 1000 °C, while at 600 °C and 800 °C, some poly-Si inclusions were observed using Raman spectroscopy. Hall effect measurements showed that epi-Si layers deposited at 1000 °C had resistivity, carrier concentration, and mobility comparable to those obtained for c-Si wafers fabricated through ingot growth and wafering using the same solar grade Si feedstock used for the e-beam depositions. The dislocation densities were determined to be ∼2 × 107 cm−2 and ∼5 × 106 cm−2 at 800 and 1000 °C, respectively, using Secco etch. The results highlight the potential of e-beam evaporation as a promising and cost-effective alternative to conventional CVD for the growth of epi-Si layers and, potentially, epi-Si wafers. Some of the remaining technical challenges of this deposition technology are briefly indicated and 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)0.000
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 score0.006
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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