The Designing of Magnetic-Driven Micromirror for Portable FTIRs
Bibliographic record
Abstract
Fourier transform infrared spectroscopy is a widely used instrument to analyze and test different materials including organic and inorganic. Most of current commercial Fourier transform infrared spectrometers are limited in miniaturization and scanning velocity by their macroscopic components. MEMS FTIR spectroscopy is one of the important applications of translational actuator-driven systems by using MEMS technology. The critical component in MEMS FTIRs is the large displacement translating micromirror and its actuator. The paper presents a large displacement and high-surface quality micromirror. The micromirror consists of a micromagnetic actuator and a micromirror plate. The mirror plate and the actuator are fabricated separately and bonded together afterwards, and its size is 3.6 × 3.6 mm2 high-surface quality square mirror plate and a 1cm2 moving part. The microactuator’s moving part is fabricated using MetalMUMPS, and its fixed part includes a ring permanent magnet and a solenoid to realize a large displacement. The mirror plate is fabricated using polished silicon coated with metal layer with high-surface prototypes that are fabricated and experimentally tested. A maximum stroke of 400 μm has been achieved in pull-in whereas only 140 μm stroke have been measured for a 4 to 5-volt DC-controlled displacement, and the resonance frequency is 10 Hz.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".