Comparative Thermal Analysis of Single vs. Arrayed Layouts for Integrated Power Transistors Using COMSOL
Bibliographic record
Abstract
Monolithic power electronics are a key solution for compact and efficient industrial systems. However, in some applications, integrated power transistors must withstand high voltage and current stresses, especially during short-circuit faults, until protection features activate. This necessitates careful design, layout optimization, and advanced thermal modeling to ensure reliability. This work proposes an arrayed-layout approach, where a MOSFET power transistor is divided into multiple parallel instances to enhance thermal performance of the silicon chip. The effects of power dissipation (P), number of transistor instances (N), and inter-instance spacing (Δ) on steady-state and transient thermal behavior are analyzed using finite-element analysis in COMSOL. Results show that transitioning from a single-instance transistor (N=1) to a multi-instance transistor (N>1) using the proposed approach while optimizing Δ can reduce the maximum surface temperature by up to 12.5°C and 30°C (10% reduction) at 1W and 2.5W power dissipation, respectively. In addition, the time required to reach a critical temperature (e.g., 125°C) improves by up to 64%, delaying thermal runaway. These findings highlight the thermal benefits of arrayed transistor layouts, providing valuable insights for optimizing integrated power transistor design.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".