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Record W2133161253 · doi:10.1186/1556-276x-9-184

Electron beam lithography with feedback using in situ self-developed resist

2014· article· en· W2133161253 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

VenueNanoscale Research Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Photolithography Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsResistElectron-beam lithographyMaterials scienceLithographyOpticsBeam (structure)NitrocelluloseDistortion (music)In situCathode rayNanotechnologyOptoelectronicsElectronPhysicsChemistry

Abstract

fetched live from OpenAlex

Due to the lack of feedback, conventional electron beam lithography (EBL) is a 'blind' open-loop process where the exposed pattern is examined only after ex situ resist development, which is too late for any improvement. Here, we report that self-developing nitrocellulose resist, for which the pattern shows up right after exposure without ex situ development, can be used as in situ feedback on the e-beam distortion and enlargement. We first exposed identical test pattern in nitrocellulose at different locations within the writing field; then, we examined in situ at high magnification the exposed patterns and adjusted the beam (notably working distance) accordingly. The process was repeated until we achieved a relatively uniform shape/size distribution of the exposed pattern across the entire writing field. Once the beam was optimized using nitrocellulose resist, under the same optimal condition, we exposed the common resist PMMA. We achieved approximately 80-nm resolution across the entire writing field of 1 mm × 1 mm, as compared to 210 nm without the beam optimization process.

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)
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 score0.093
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
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.302
Teacher spread0.282 · 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