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Record W2002273187 · doi:10.1116/1.1513790

Anomalies in modeling of anisotropic etching of silicon: Facet boundary effects

2002· article· en· W2002273187 on OpenAlexaff
Z. Elalamy, L. M. Landsberger, A. Pandy, Mojtaba Kahrizi, Irina Stateikina, Stephen L. Michel

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsFacet (psychology)Etching (microfabrication)SiliconAnisotropyCrystal (programming language)Materials scienceEnhanced Data Rates for GSM EvolutionBoundary (topology)RowCrystallographyGeometryCondensed matter physicsOpticsChemistryComposite materialPhysicsMathematicsOptoelectronicsComputer scienceLayer (electronics)Mathematical analysis

Abstract

fetched live from OpenAlex

Beginning with an idealized model of anisotropic etching of silicon in which the etch behavior depends only on the crystal features presented to the etchant, this article extends the model to address certain anomalies observed in the data. The idealized model is based on profiles of underetched surfaces and underetch behavior as a function of mask-edge deviation in wagon-wheel experiments on Si{110} and Si{100} at different TMAH concentrations. Underetched surfaces are found to follow a cohesive system composed of planes defined by two types of crystal features: periodic bond chains and rows of kinks. But it is also found that the same crystal planes in the same etchant often exhibit different etch rates. These anomalies are outlined, and interactions at the boundaries between adjacent facets are proposed to explain them.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.223
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2002
Admission routes1
Has abstractyes

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