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Record W2108676390 · doi:10.1109/pvsc.2009.5411208

Formation of mesoporous gallium arsenide for lift-off processes by electrochemical etching

2009· article· en· W2108676390 on OpenAlexfundno aff
Enrique Garralaga Rojas, Carsten Hampe, Heiko Plagwitz, Rolf Brendel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsnot available
FundersInstitute of Gender and Health
KeywordsEtching (microfabrication)Materials scienceMesoporous materialPorositySubstrate (aquarium)WaferGallium arsenideLayer (electronics)Isotropic etchingChemical engineeringEpitaxyMonocrystalline siliconElectrolyteOptoelectronicsAnalytical Chemistry (journal)NanotechnologySiliconComposite materialChemistryElectrodeCatalysis

Abstract

fetched live from OpenAlex

Monocrystalline, mesoporous GaAs double layers with controlled porosities are formed by means of electrochemical etching on p-type GaAs substrates using highly concentrated HF-based electrolytes. Variations in the electrolyte concentration and etching current density lead to changes in the porosity, morphology, thickness and etching rate of the porous layers. The porous layer is composed of micro and mesopores with a diameter in the range of 1 nm to 38 nm and a mean value of less than 10 nm. The etching rate of the porous layer lies in a range of 1.7 nm/sec to 1725 nm/sec. Hundred nm sized <111> oriented pyramids form at the interface between porous layer and substrate if etching current densities below 7.5 mA/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> are applied. Mesoporous layers with thicknesses of up to 7 ¿m form reproducibly. Porous layers thicker than 7 ¿m automatically lift-off from the substrate. We demonstrate the spatially homogenous formation of mesopores on GaAs wafers with 4" in diameter. The etching rates and thicknesses values achieved indicate that etching of GaAs mesopores may be applicable to the industrial production of space solar cells.

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 score0.004
Threshold uncertainty score0.340

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 head0.007
GPT teacher head0.239
Teacher spread0.233 · 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
Published2009
Admission routes1
Has abstractyes

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