MétaCan
Menu
Back to cohort
Record W1994571297 · doi:10.1021/nl0627801

Block Copolymer Templated Etching on Silicon

2007· article· en· W1994571297 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNano Letters · 2007
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSiliconMaterials scienceNanoscopic scaleNanotechnologyEtching (microfabrication)LithographySurface modificationReactive-ion etchingMesoscopic physicsCopolymerPolymerMonolayerIsotropic etchingFabricationChemical engineeringOptoelectronicsComposite materialLayer (electronics)

Abstract

fetched live from OpenAlex

The use of self-assembled polymer structures to direct the formation of mesoscopic (1-100 nm) features on silicon could provide a fabrication-compatible means to produce nanoscale patterns, supplementing conventional lithographic techniques. Here we demonstrate nanoscale etching of silicon, applying standard aqueous-based fluoride etchants, to produce three-dimensional nanoscale features with controllable shapes, sizes, average spacing, and chemical functionalization. The block copolymers serve to direct the silicon surface chemistry by controlling the spatial location of the reaction as well as concentration of reagents. The interiors of the resulting etched nanoscale features may be selectively functionalized with organic monolayers, metal nanoparticles, and other materials, leading to a range of ordered arrays on silicon.

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.

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), Insufficient payload (model declined to judge)
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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.002

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 head0.245
Teacher spread0.235 · 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