Toward 2.5D Structures for Multi-Channel MEMS Acoustic-Based Digital Isolators using Through Silicon Openings
Bibliographic record
Abstract
In this paper, a piezoelectric MEMS-based digital isolator by the medium of air for transferring ultrasound waves between the transmitter (Tx) and receiver (Rx) is presented. A front-to-back 2.5-dimensional structure is also presented for assembling MEMS dice in the piezoMUMPs process. It is demonstrated that front-to-back stacking of dice is possible according to the thickness of layers in this process. This structure allows to minimize the distance between Tx and Rx, which is reduced and shows 43% improvement with the piezoMUMPS process compared to the conventional method. Also, it is explained that in the front-to-back bonding technique, there is only a need for top-side wire bonding. Through this process, it is possible to minimize the size of the final digital isolator by defining a waveguide utilizing a through silicon opening (TSO). Simulations show that according to the behavior of the sound wave inside the openings, the conical shape of the TSO has a direct effect on the transmission bit rate (improvement of 3.5 times) in contrast with the straight one.
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 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".