Solution Deposition of Conformal Gold Coatings on Knitted Fabric for E‐Textiles and Electroluminescent Clothing
Bibliographic record
Abstract
Abstract The vision for wearable electronics involves creating an imperceptible boundary between humans and devices. Integrating electronic devices into clothing represents an important path to this vision; however, combining conductive materials with textiles is challenging due to the porous structure of knitted textiles. Stretchability depends on maintaining the void structure between the yarns of the fabric; filling these voids with conductive materials stiffens the textile and can lead to detrimental cracking. The authors demonstrate the solution‐based metallization of a knitted textile that conformally coats individual fibers with gold, leaving the void structure intact. The resulting gold‐coated textile is highly conductive, with a sheet resistance of 1.07 Ω per square in the course direction. The resistance decreases by 80% when the fabric is stretched to 15% strain, and remains at this value to 160% strain. This outstanding combination of stretchability and conductivity is accompanied by durability to wearing, sweating, and washing. Low‐cost screen printing of a wax resist is demonstrated to produce patterned gold textiles suitable for electrically connecting discrete devices in clothing. The fabrication of electroluminescent fabric by depositing layers of device materials onto the gold‐coated textile is furthermore demonstrated, intimately merging device functionality with textiles for imperceptible wearable devices.
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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) | 0.001 | 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".