A 3D thermal simulation tool for integrated devices-Atar
Bibliographic record
Abstract
This paper presents a novel three-dimensional (3D) thermal simulation tool for semiconductor integrated devices. The simulator is used to automatically generate an accurate 3D physical model of the device to be simulated from layout information. The simulator produces an appropriate mesh of the device based on a rectangular block structure. The mesh is automatically created such that a fine mesh is produced around heat generation regions, but a moderate number of blocks are used for the entire device. This paper first confirms that the simulator produces an accurate solution to the nonlinear differential equation describing the heat flow. Then model generation from three example technologies (silicon trench, GaAs mesa structures, silicon on insulator) is presented. The potential of the simulator to quickly and easily explore the effect of layout and process variations is illustrated, with the simulation of a two-transistor GaAs power cell as a large example. The program incorporates a transient solver based on a transmission line matrix (TLM) implementation using a physical extraction of a resistance and capacitance network. The formulation allows for temperature dependent material parameters and a nonuniform time stepping. An example of a full transient solution of heat flow in a realistic Si trench device is presented.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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".