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Record W2128843137 · doi:10.1002/pssc.201000130

Porous germanium multilayers

2011· article· en· W2128843137 on OpenAlexfundno aff
Enrique Garralaga Rojas, Jlm Jan Hensen, Jürgen Carstensen, H. Föll, Rolf Brendel

Bibliographic record

VenuePhysica status solidi. C, Conferences and critical reviews/Physica status solidi. C, Current topics in solid state physics · 2011
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsnot available
FundersInstitute of Gender and HealthEuropean Space Agency
KeywordsElectrolyteEtching (microfabrication)PassivationMaterials scienceDissolutionElectropolishingAnodeLayer (electronics)PorosityMesoporous materialChemical engineeringNanoporousNanotechnologyComposite materialChemistryElectrode

Abstract

fetched live from OpenAlex

Abstract We present the reproducible fabrication of porous germanium (PGe) single‐ and multilayers. Mesoporous layers form on heavily doped 4” p‐type Ge wafers by electrochemical etching in highly concentrated HF‐based electrolytes with concentrations in a range of 30‐50 wt.%. Direct PGe formation is accompanied by a constant dissolution of the already‐formed porous layer at the electrolyte/PGe interface, hence yielding a thinner substrate after etching. This effect inhibits multilayer formation as the starting layer is etched while forming the second layer. We avoid dissolution of the porous layer by alternating the etching bias from anodic to cathodic. PGe formation occurs during anodic etching whereas the cathodic step passivates pore walls with H‐atoms and avoids electropolishing. The passivation lasts a limited time depending on the etching current density and electrolyte concentration, necessitating a repetition of the cathodic step at suitable intervals. With optimized alternating bias mesoporous multilayer production is possible. We control the porosity of each single layer by varying the etching current density and the electrolyte (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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 categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.073
GPT teacher head0.349
Teacher spread0.276 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations8
Published2011
Admission routes1
Has abstractyes

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