Advanced Thermal Control Using Chip Cooling Laminate Chip (CCLC) with Finite Element Method for System-in-Package (SiP) Technology
Bibliographic record
Abstract
This paper introduces a novel approach to address thermal management challenges in system-in-package (SiP) technology, which is a significant concern in various advanced technologies. The main objective is to assess the electrical and thermal performance of the SiP model by utilizing Chip Cooling Laminate Chip (CCLC) technology. To achieve this, we employed finite element method (FEM) analysis using COMSOL Multiphysics® and MATLAB® to compare the results of electrical and thermal SiP models with and without CCLC technology. The numerical simulations revealed that, as opposed to the traditional model, the temperature variation decreased significantly with a uniform temperature distribution when employing the CCLC technology. Additionally, the thermal conduction performance of the packaging system using CCLC demonstrated remarkable reliability and resolution with cost-effective micro-devices, particularly in micro-medicine applications. The analysis of the electrical and thermal models reported a maximum error between them of 1.15 ∘C.
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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 | 0.000 |
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".