Development of non-planar interconnects for double-sided flexible copper substrates using laser assisted maskless microdeposition processes
Bibliographic record
Abstract
Non-planar (3D) interconnects have an important role in the electronic packaging industry today. They allow manufacturers to save materials and space when connecting circuit components on flexible and non-planar substrates. Nowadays, double-sided flexible substrates have attracted the electronic industry to develop miniaturized flexible devices, such as sensors-on-chips, effectively and compactly. This study reports on our preliminary results for the creation of non-planar silver interconnects on the edge of double-sided copper substrates separated by a layer of polyethylene terephthalate (PET) using laser-assisted maskless microdeposition (LAMM). In the LAMM process, which is a laser-based direct write technology, suspensions of silver nano-particles are used in a layer-by-layer deposition followed by laser post sintering. This study includes the characterization of the LAMM process to achieve desired conductivity in the produced interconnects, which is the main indicator of performance for the electronic packages. Several parameters, including the deposition and laser processing parameters, are optimized to achieve interconnects free of pores, cracks and delamination with reasonable bonding. For investigating the topography and microstructure of the interconnects, an optical microscope and scanning electron microscope (SEM) are used.
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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".