Ceramic Interposers for Ultra-High Density Packaging and 3D Circuit Integration
Bibliographic record
Abstract
Higher data speeds spurred on by the arrival of 5G technology and the Internet of Things (IoT) have accelerated the need for increased circuit integration with shorter interconnects. 3D integration and packaging techniques that employ silicon interposers with Through Silicon Vias (TSVs) have emerged as one of the key technologies in enabling this trend. In this paper, a cost-effective alternative to silicon interposers based on Low Temperature Co-fired Ceramic (LTCC) technology is proposed and demonstrated. Using ultra-thin ceramic layers and laser ablation, ceramic interposers with micro-via holes as small as 20 μm in diameter and 40 μm pitch have been successfully realized. In addition to the standalone interposers, the developed fabrication process has been used to design a high-density package for the integration of Silicon Photonic (SiP) and electronic chips with operational bandwidth up to 48 GHz. This novel cost-effective packaging technology offers a viable alternative to silicon interposers for the integration of multi-chip high-speed electronic systems in a single package with high reliability and very good performance to maintain signal integrity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".