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Record W2017371738 · doi:10.1116/1.1286394

Three-dimensional simulation of film microstructure produced by glancing angle deposition

2000· article· en· W2017371738 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.

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2000
Typearticle
Languageen
FieldMaterials Science
TopicOptical Coatings and Gratings
Canadian institutionsUniversity of AlbertaCarleton University
Fundersnot available
KeywordsDeposition (geology)Materials scienceThin filmSubstrate (aquarium)MicrostructureScanning electron microscopePhysical vapor depositionNanotechnologyOpticsSimulationComputer scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

A novel three-dimensional (3D) ballistic deposition simulator 3D-FILMS has been developed for the modeling of thin film deposition and structure. The simulator features a ballistic transport algorithm to model incident species with angular distributions appropriate to physical vapor deposition systems. Two-tiered data structuring is employed in order to enable the simulator to run using memory resources available to workstations. The simulator has been applied to a unique class of thin films grown by the technique of glancing angle deposition (GLAD). These films exhibit low bulk density due to an internal structure consisting of isolated microcolumns, which can be engineered into a variety of 3D forms. Because of their inherent 3D morphology, created by a combination of complex substrate motion and 3D shadowing, GLAD films represent an ideal test subject for 3D simulation. Scanning electron microscope images of films are presented together with simulation results, which correctly reproduce aspects of column morphology, column growth competition and extinction, and film bulk density.

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 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 score0.039
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.235
Teacher spread0.229 · 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