Time-Gated and Multi-Junction SPADs in Standard 65 nm CMOS Technology
Bibliographic record
Abstract
SPADs (Single-Photon Avalanche Diodes) are important detectors for a wide range of applications including positron emission tomography, Raman spectroscopy, light detection and ranging, and quantum key distribution. For some applications, custom image sensor technologies are used, but at a higher cost and lower performance imagers when compared to implementation in a standard planar CMOS technology. In this paper, we explore time-gating and multi-junction techniques to improve the SPAD's performance in smaller standard planar CMOS processes to take advantage of their potential for monolithic integration with other advanced, mixed-signal circuitry for simple, low-cost, high-performance imaging solutions. A passively quenched, unbuffered, triple-junction SPAD structure was designed in a standard 65 nm CMOS process from TSMC. The characterization of the SPAD junctions in this process is the first in literature and proves useful for SPAD designers aiming for advanced CMOS technology nodes. The time-gated (TG) pixel design used the top shallow junction. The potential for improved photon detection efficiency and wavelength distinction through a multi-junction design was investigated. Our testing demonstrated that the proposed implementation of the triple-junction SPAD in this technology node is not suitable for wavelength distinction. The TG design achieved a fill-factor of 28.6%, and at an excess voltage of 300 mV, it achieved a peak photon detection efficiency of ~2.1% at 440 nm,22 ns, and <; 200 ps timing jitter.
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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) | 0.000 | 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 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".