Mini LED array transferred onto a flexible substrate using Simultaneous Transfer and Bonding (SITRAB) process and Anisotropic Solder Film (ASF)
Bibliographic record
Abstract
We transferred and bonded a Mini-LED array onto flexible substrates using the simultaneous transfer and bonding (SITRAB) technology. We also developed the bonding material called anisotropic solder film (ASF). ASF consisted of thermosetting resin as the base matrix and type-7 Sn/58Bi solder powder and reductant. We fabricated Mini-LED carriers and substrates to analyze the compatibility of the SITRAB process and ASF with the flexible substrates. The Mini-LED carrier was made of glass, and transparent PDMS was used as an adhesive considering the laser's wavelength in the SITRAB process. Mini LEDs are arranged in a 32 × 32 array by 450 μm pitch on the glass carrier. Substrates were made of a 20 μm-thick polyimide (PI) and a 75 μm-thick polyethylene terephthalate (PET), respectively. 32 × 32 Mini-LED arrays were successfully transferred and bonded onto those substrates using the SITRAB process and ASF. We measured the light output from the Mini-LED array on the flexible substrate and performed a bending test. All LED was worked without degradation with a bending radius of less than 3 mm. We also observed the bonding joint from the cross-sectional microscopic and SEM images of Mini-LED on the flexible substrate.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".