Bibliographic record
Abstract
This thesis deals with the design and implementation of Super Junction Lateral Double Diffused MOSFETs (SJ-LDMOSTs) targeting a wide range of smart PIC applications. The off-state performance of SJ-LDMOSTs implemented on finite resistivity substrates is affected by substrate-assisted-depletion effects. Original solutions to eliminate and/or suppress these effects are proposed in this thesis and lead to device structures which break the established Silicon Limit in terms of specific on-resistance (Ron.sp) and breakdown voltage (BV). One proposed solution is the use of an insulating sapphire substrate, to eliminate charge coupling from the substrate and achieve charge compensation between the opposite polarity SJ pillars comprising the drift region. The uniform electric field distribution achieved in the SJ drift region and the high doping concentration in the SJ pillars result in a significant improvement in the Ron.sp for a given BV, particularly at high pillar height to width aspect ratio. To verify the viability of the structure, the design and implementation of SJ-LDMOSTs on silicon on sapphire (SOS) substrates using a custom 7 mask CMOS compatible process are described. The SJ pillars are generated using multiple high energy ion implantation to achieve well-defined vertical pillars. Experimental devices with drift region lengths of 66 mum and pillar width to height aspect ratio of 1.2 mum/0.7 mum exhibit R on.sp of 0.82 O.cm2 and BV ranging between 500 and 600V corresponding to less than 8.5% charge imbalance in the pillars. A third solution to integrate SJ-LDMOSTs in mainstream CMOS technology using bulk silicon substrates is proposed. The device features a terminating RESURF region, inserted between the SJ drift region and the n+ drain to alleviate substrate-assisted-depletion effects. Simulation results on such devices predict that a significant reduction in Ron.sp for a given BV is achieved, as compared to conventional RESURF-LDMOSTs, using pillar height to width aspect ratios of 10 mum/1 mum. In a second proposed solution, a 170V SJ-LDMOST implemented in a commercial 0.5 mum, CMOS/SOS process is presented to demonstrate that high voltage SJ-LDMOSTs can be fully integrated into a standard CMOS process. Fabricated devices featuring overlapping SJ pillars with drift regions of 10 mum and pillar aspect ratios of 0.3 mum/0.12 mum (effective width/height) exhibit Ron.sp of 87 mO.cm2 and BV of 170V.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".