Selectively Metallized Polymeric Substrates by Microcontact Printing an Aluminum(III) Porphyrin Complex
Bibliographic record
Abstract
We report a simple, low-cost method for the fabrication of copper wires and contacts on a wide range of flexible, rigid, and inert polymeric substrates. This method relies on procedures to oxidize the polymeric substrates to form surface-bound carboxylic acid groups. Patterning of an aluminum porphyrin ink using microcontact printing results in the formation of an aluminum porphyrin monolayer that is covalently anchored to the oxidized polymer surface via an aluminum-carboxylate bond. We characterize this monolayer using ultraviolet-visible absorption spectra, reflection-absorption infrared spectroscopy, and contact angle measurements. Patterned aluminum porphyrin monolayers bind a Pd/Sn colloidal catalyst from solution that subsequently initiates the selective deposition of copper in an electroless plating solution. We demonstrate the fabrication of patterned copper films on a variety of both flexible and rigid polymers with minimum feature sizes of 2 microm over 2 cm(2) substrates. Measurements of electrical resistivity of copper wires fabricated on flexible poly(ethylene naphthalate) (PEN) substrates as a function of the bending radius show no negative impact on electrical performance at bending radii as small as 500 microm. Permanently damaging the PEN substrate by creasing (corresponding to a bending radius of 100 microm) results in only a modest increase in resistivity.
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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 | 0.001 | 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".