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Record W2035805583 · doi:10.1115/1.2917315

A Submicron Multiaxis Positioning Stage for Micro- and Nanoscale Manufacturing Processes

2008· article· en· W2035805583 on OpenAlexaff
Ashwin Balasubramanian, Martin Byung‐Guk Jun, Richard E. DeVor, Shiv G. Kapoor

Bibliographic record

VenueJournal of Manufacturing Science and Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsUniversity of Victoria
FundersUniversity of Illinois at Urbana-ChampaignNational Science Foundation
KeywordsNanoscopic scaleMaterials scienceRobustness (evolution)NanowireFinite element methodMicrofluidicsNanotechnologyChipStructural engineeringEngineeringElectrical engineeringChemistry

Abstract

fetched live from OpenAlex

A piezoelectrically driven, submicron XY-positioning stage with multiprocess capability is developed and then integrated into two micro∕nanoscale manufacturing processes to improve their performance. The design is based on the HexFlex™ mechanism but is modified to improve structural robustness using a combination of factorial design, linear programming, and finite element analysis. Performance analysis reveals travel ranges of 16μm (X-axis) and 8μm (Y-axis), positioning accuracies of 87nm (X-axis) and 92nm (Y-axis), and overall stiffnesses of 32N∕μm (X-axis) and 36N∕μm (Y-axis). A comparison of microfluidic channels manufactured with a micromachine tool (mMT) alone and with the stage stacked on the mMT shows an improvement in feature accuracy from 870nmto170nm. The stage is integrated with an electrochemical deposition setup. Nanowire structures with sharp angles are fabricated. The diameter of these nanowires shows an improvement in uniformity by decreasing the standard deviation of diameter variation from 2.088μmto0.009μm.

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.

How this classification was reachedexpand

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 score0.029
Threshold uncertainty score0.569

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 communication0.0000.001
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 head0.008
GPT teacher head0.209
Teacher spread0.201 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2008
Admission routes1
Has abstractyes

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