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Record W2103187241 · doi:10.1109/jsen.2005.860366

A micromachined wide-bandwidth magnetic field sensor based on all-PMMA electron tunneling transducer

2006· article· en· W2103187241 on OpenAlexaff
Jing Wang, Wei Xue, Naidu V. Seetala, Xueyuan Nie, Efstathios I. Meletis, Tianhong Cui

Bibliographic record

VenueIEEE Sensors Journal · 2006
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceQuantum tunnellingOptoelectronicsSiliconElectrodeMagnetic fieldPhotolithographyPhysics

Abstract

fetched live from OpenAlex

All-PMMA-based tunneling magnetic sensors were fabricated by hot embossing replication with silicon templates. The silicon templates had smooth surfaces, positive profiles, and pyramid-like pits with a high aspect ratio. With this fast (20 min), simple (one-step), and repeatable method, the all-PMMA tunneling sensor platform yielded sharp tunneling tips with 75 /spl mu/m in baseline and 50 /spl mu/m in depth. The sensors were assembled and fixed with measurement circuits, after their electrodes were patterned with modified photolithography and Co film was deposited with e-beam evaporation. A natural frequency response of 1.3 kHz was observed, and a tunneling barrier height of 0.713 eV was tested. Due to the quadratic relation between magnetic force and the field, the sensor field response (7.0/spl times/10/sup 6/ V/T/sup 2/) was also quadratic. The noise voltage at 1 kHz is 0.2 mV, corresponding to a magnet field of 0.46/spl times/10/sup -6/ T. The bandwidth of this sensor is 18 kHz. This new type of sensor platform is promising for the next generation of microsensing applications.

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 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
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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.

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

Citations2
Published2006
Admission routes1
Has abstractyes

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