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Record W2807722833 · doi:10.1080/15599612.2018.1465147

Dynamic response of ferrofluidic deformable mirrors using elastomer membrane and overdrive techniques

2018· preprint· en· W2807722833 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

VenueInternational Journal of Optomechatronics · 2018
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceFerrofluidMillisecondSettling timeElastomerMembraneActuatorResponse timeOpticsOptoelectronicsMagnetic fieldPhysicsStep responseComputer scienceComposite materialElectrical engineeringChemistryEngineeringControl engineering

Abstract

fetched live from OpenAlex

The experimental results obtained with a ferrofluidic deformable mirror controlled by electro-magnet actuators are presented here. Using a step input through a single actuator, we obtained a steady-state settling time of 100 ms; however, different combinations of overdrive inputs can be used to decrease it to 25 ms. A new technique which consists of laying down an elastomer membrane, coated with an aluminum film, on the ferrofluid is also discussed. By adding the membrane on the ferrofluid, it further decreases the time response by a factor of 2. Furthermore, the thin aluminum layer improves the reflectivity of the mirror. Finally, using the membrane and the overdrive techniques combined, the time response is improved by a factor of 20. Numerical simulations show that ferrofluidic mirrors using membranes and improved electronics should reach settling times of the order of a millisecond. Presumably, even lower settling times could be possible.

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 score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.319
Teacher spread0.301 · 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