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Record W4383215532 · doi:10.1088/1361-6439/ace453

Crosstalk-free large aperture electromagnetic 2D micromirror for LiDAR application

2023· article· en· W4383215532 on OpenAlexaff
Behrad Ghazinouri, Siyuan He

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDigital micromirror deviceOpticsCrosstalkMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Abstract This paper presents a novel design of a 2D electromagnetic micromirror without crosstalk. The proposed micromirror uses a flexible printed circuit board (FPCB) and four layers of coils embedded in the polyimide layers. The insulated layers of the coil allow for independent actuation of the mirror plate to rotate about two orthogonal axes. The diamond shaped micromirror uses a hyperbola-shaped magnetic field on the coils under the mirror plate and a 45-degrees magnetic field on the coils embedded in the FPCB frame to eliminate the mechanical crosstalk. Finite element analysis was used to predict the novel 2D micromirror’s behavior. The novel 2D micromirror prototype is used in scanning LiDAR, The results indicate that the crosstalk-free pattern yielded significantly clearer results, particularly for detecting object boundaries and reducing barrel distortion. The experimental test has verified the novel crosstalk-free 2D micromirror working principle and showed good scanning quality: no crosstalk and an improvement in the horizontal field of view up to 19% But with the cost of reducing the vertical field of view by up to 12%. The novel 2D micromirror prototype has a large aperture of 19 × 19 mm 2 , which is very suitable for coaxial scanning LiDAR.

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 score0.221
Threshold uncertainty score0.802

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 communication0.0000.000
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 head0.004
GPT teacher head0.205
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

Citations9
Published2023
Admission routes1
Has abstractyes

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