3D printing of transparent pH-mediated high-water-content hydrogels for electromagnetic interference (EMI) shielding
Bibliographic record
Abstract
3D printing techniques allow for fabricating accurate structured and complex parts, designed via computer-aided design (CAD). In this research, we introduce extrusion 3D printing of optically transparent, high-water-content (96%) hydrogels toward fabrication of easy-to-make, cost-effective electromagnetic interference (EMI) shields. First, we designed polyacrylic acid soft hydrogels with different concentrations to achieve a 3D printable composition with desired rheological properties. Then, 4wt.% transparent hydrogel was printed into different structures on a cellulose acetate substrate. The 3D-printed (100% infill) hydrogels containing 96wt.% water demonstrated appreciable EMI shielding as high as 18.6 dB at a thickness of 1.6 mm. More importantly, it is shown that the 3D printing technique allows for macroscale patterning of the shields, providing more degrees of freedom in tuning the EMI shielding performance. Our achieved results validated that the 3D-printed transparent hydrogels attenuate EM waves noticeably, rendering them a superb candidate for high-performance optically transparent EMI shields.
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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 | 0.000 |
| 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".