Single-Chip CMOS-MEMS Dual Mode Scanning Microwave Microscope
Bibliographic record
Abstract
We present the design, fabrication and experimental validation of an integrated Scanning Microwave Microscopy (SMM)/Atomic Force Microscopy (AFM) system that does not require the use of a conventional laser-based AFM. Microfabricated SMM probes are collocated with piezoresistive strain-based sensing AFM probes in a CMOS-MEMS process, and are actuated by integrated electrothermal scanners. Integration of AFM enables dual mode imaging (topography and electrical properties) and more importantly, it enables control over tip-sample distance, which is crucial for accurate SMM imaging. This design is unique in the sense that the tip can be scanned over the sample in 3 degrees of freedom, over a$20\ \mu{\rm m}\times 10\ \mu{\rm m}\times 30\ \mu{\rm m}$scan range in the x, y, and z directions respectively. We fabricate our device by using a standard foundry CMOS process followed by in-house maskless MEMS post processing to release the devices. Single-chip SMM/AFM devices with integrated 1-D and 3-D actuation are thus obtained. These devices can be used to modulate the tip-sample separation to underlying samples with a periodic signal, improving immunity to long-term system drifts. We also investigate the effect of tip-sample separation on the resolution of the instrument. To increase measurement sensitivity, a single-stub matching network has been used to match the high tip-to-sample impedance to the 50 ohm characteristic impedance of a performance network analyzer. Measurement results of the CMOS-MEMS SMM are presented to verify the proposed concept.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".