Chip Scale 12-Channel 10 Gb/s Optical Transmitter and Receiver Subassemblies Based on Wet Etched Silicon Interposer
Bibliographic record
Abstract
In this paper, compact optical subassemblies are demonstrated based on a novel silicon interposer, which is designed and fabricated in a wafer scale process. The interposer includes the design of optical and electrical connections. A low-cost fabrication method, wet etching, is used to define light inputs and outputs as well as create the required recesses in the interposer to embed the chips into the silicon wafer at the same time. Impedance matched traces, for the high speed signals of the CMOS and opto-electronic ICs, are designed using advanced design system software and transferred onto the interposer by photolithography and electro-plating, which are accomplished on the deeply etched topology. The whole process flow of the silicon interposer patterning is designed and demonstrated, and the challenges are discussed. After the process, the optoelectronic dies and their complimentary CMOS parts are flipped and bonded on the interposer in close proximity, and a mechanical optical interface (MOI) is mounted for light coupling. Both transmitter and receiver subassemblies provide 12 parallel optical interconnections, and are scaled down to an area measuring 6 by 8 mm. Signal integrity testing is performed on a probe station for 10 Gb/s data signal delivering clear eye patterns for all channels (in both Rx and Tx subassemblies). The performance is further characterized using bit error rate (BER) testing. Both transmitter and receiver assemblies outperform a reference SFP+, with receiver sensitivity of -10 dBm at a BER lower than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-12</sup> after compensating for the MOI insertion loss. Finally, we also test the assemblies for crosstalk and demonstrate that the current design has a maximal additional penalty lower than 0.2 and 0.8 dB for transmitter and receiver, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".