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Record W2029532081 · doi:10.1116/1.3497019

Simulation of electron beam lithography of nanostructures

2010· article· en· W2029532081 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 B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Photolithography Techniques
Canadian institutionsApplied Nanotools (Canada)University of AlbertaNational Institute for Nanotechnology
Fundersnot available
KeywordsResistLithographyElectron-beam lithographyMaterials scienceCathode raySecondary electronsComputationElectronNanolithographyFabricationNanotechnologyOptoelectronicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

The authors report a numeric simulation tool that they developed for the modeling and analysis of electron beam lithography (EBL) of nanostructures employing a popular positive tone resist polymethylmethacrylate (PMMA). Modeling and process design for EBL fabrication of 5–50 nm PMMA structures on solid substrates is the target purpose of the simulator. The simulator is functional for exposure energies from 1 to 50 keV with arbitrary writing geometries. The authors employ a suite of kinetic models for the traveling of primary, secondary, and backscattered electrons in the resist, compute three-dimensional (3D) distributions of the yield of main-chain scission in PMMA, and convert these into the local volume fractions of fragments of various sizes. The kinetic process of development is described by the movement of the resist-developer interface with the rate derived from the mean-field theory of polymer diffusion. The EBL simulator allows the computation of detailed 3D distributions of the yield of main-chain scission in PMMA for various conditions of exposure, the corresponding volume fractions of small fragments, and the clearance profiles as functions of the development in time and temperature. This article describes the models employed to simulate the EBL exposure and development, reports examples of the computations, and presents comparisons of the predicted development profiles with experimental cross-sectional resist profiles in dense gratings.

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 score0.027
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.233
Teacher spread0.227 · 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