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Patterning in an Imperfect World—Limitations of Focused Ion Beam Systems and Their Effects on Advanced Applications at the 14 nm Process Node

2016· article· en· W2583649081 on OpenAlex
Christopher M. Scheffler, Richard H. Livengood, Haripriya E. Prakasam, Michael W. Phaneuf, Ken Lagarec

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

VenueProceedings - International Symposium for Testing and Failure Analysis · 2016
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsFibics (Canada)
Fundersnot available
KeywordsLimitingProcess (computing)Node (physics)Computer scienceImperfectDimension (graph theory)NanotechnologyProcess controlMaterials scienceComputer engineeringEngineeringMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

Abstract This paper provides information on ion beam dose delivery and machining a perfect pattern in an ideal world and summarizes the various beam control limitations of the current generation systems. It discusses conventional and proposed solutions to these limitations and highlights their effect on minimum dimension nanomachining applications at the 14 nm Si process node and beyond. The paper highlights the solutions that can be implemented to help negate inconsequential effects of systems. With that in mind, the most significant of these factors in limiting a tool's ability to complete a perfect pattern can be grouped into two categories: timing and placement and non-uniform dose delivery. With good understanding and discipline, most of these issues described can be corrected, significantly minimized, or simply avoided.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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