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Record W2121450147 · doi:10.1109/tnano.2006.880898

Nanostenciling of Functional Materials by Room Temperature Pulsed Laser Deposition

2006· article· en· W2121450147 on OpenAlex
C. V. Cojocaru, Cătălin Harnagea, A. Pignolet, Federico Rosei

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.

Bibliographic record

VenueIEEE Transactions on Nanotechnology · 2006
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsDeposition (geology)Materials scienceSubstrate (aquarium)NanostructureVacuum depositionPulsed laser depositionNanotechnologyOptoelectronicsLaserShadow maskRapid prototypingThin filmOpticsPhysics

Abstract

fetched live from OpenAlex

We present how various features drawn in a miniature shadow mask (nanostencil) can be efficiently transferred to a surface in the form of three-dimensional nanostructures of metals (Pt, Cr), semiconductors (Ge), and complex oxides (e.g., BaTiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> ) by room temperature pulsed laser deposition. Selective deposition is obtained by interposing a sieve with apertures down to 100 nm between source and substrate. Nanostenciling allows for the organization of structures in predefined architectures with high accuracy. The patterning process is simple and rapid, since it does not imply additional processing steps. It is also parallel, resistless, and does not interfere with the structures' growth dynamics. The material deposited through the stencil mask conserves the desired functionality even at the level of the individual nanostructures. Nanostenciling can be performed in high or ultrahigh vacuum and is suitable for parallel prototyping of fragile or functionalized surfaces

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)0.000
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 score0.480
Threshold uncertainty score0.715

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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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