Computational Fluid Dynamics (CFD) Modeling of Microchannel Filling Applications Utilized in Consumer Electronics Manufacturing
Bibliographic record
Abstract
Abstract The increasing push for smaller and stacked electronics configurations along with a demand for faster time-to-market places great emphasis to improve the reliability of parts in the consumer electronics industry. Microchannel filling is an important class of manufacturing processes used to enhance the reliability of products by improving the reliability of parts assembled with adhesives, augmenting the reliability of printed circuit boards (PCB) used in handheld devices by encapsulation with epoxy, and enhancing the performance of flip-chip packaging technology in semiconductor packaging. For example, during a flip-chip process called underfilling, a highly viscous epoxy-like material is dispensed into microchannels between the chip and substrate. Depending on the epoxy dispensing process and the microchannel geometry, air entrapment can occur in the epoxy, which can lead to product reliability issues and formation of cracks in area of air entrapment. Similarly, the effectiveness of components in a device joined by coating of adhesives effectively depends on the uniformity of the adhesive layer between the device components and absence of air voids. An accurate three-dimensional (3D) flow analysis is required to optimize the parameters to ensure uniformity and accuracy of these filling processes for optimal flow of glue/epoxy, design better flip-chips and achieve the required thermo-mechanical performance of the assembled parts. High-fidelity 3D modeling needs to account for the flow of multiple fluid phases, surface tension effects and the ability to consider advanced fluid material properties. The present study focusses on microchannel filling applications such as bracket filling with nozzles, underfilling and printed circuit board (PCB) encapsulation, which are relevant to consumer electronics manufacturing. We present a robust multiphase workflow to accurately model the capillary-driven filling behavior of highly viscous materials like adhesives and epoxy in thin microchannels. The simulations utilize unstructured polyhedral meshes with Fluent meshing to accurately capture the true shape of thin complex electronic components and small gaps, without any approximation. Additionally, the latest capabilities of the CFD solver Ansys Fluent such as enhanced Volume-of-Fluid (VOF) method numerics, physics-based adaptive time-stepping, and advanced stabilization controls are utilized for these high-fidelity multiphase flow simulations. Using these simulations, we can examine the flow velocity of adhesive in microchannels, formation of air voids due to adhesive dispense parameters, air entrapment due to capillary flow and overflowing of adhesive due to incorrect nozzle flow rates, amongst other analysis parameters. This work highlights some of our recent efforts to optimize the adhesive/epoxy dispensing and filling processes to mitigate the effects of air entrapment and void formation to achieve reliable packaging solutions and improved manufacturing productivity.
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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) | 0.000 | 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 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".