Bibliographic record
Abstract
Organic electronics, based on semiconducting and conducting polymers, have been extensively investigated in the past decades and have found commercial applications in lighting panels, smartphone and TV screens using OLEDs (organic light emitting diodes) technology. Many other applications are foreseen to reach the commercial maturity in future in areas such as transistors, sensors and photovoltaics. Organic electronic devices, apart from consumer applications, are paving the path for key applications at the interface between electronics and biology, such as in polymer electrodes for recording and stimulating neural activity in neurological diseases. In such applications, organic polymers are very attractive candidates due to their distinct property of mixed conduction: the ability to transport both electron/holes and ionic species. Additionally, conducting polymers offer the possibility to tune their surface properties (e.g., wettability or chemical reactivity) by changing their oxidation state, thus promoting or hindering the adhesion of biomolecules. This feature can be particularly useful for enhancing the biocompatibility of implantable electrodes. My talk will deal with processing and characterization of conducting polymer films and devices for flexible, stretchable and healable electronics. Self-healing electronic materials are highly relevant for application in biology and sustainable electronics. We observed mechanical and electrical healability of PEDOT:PSS thin films. Upon reaching a certain thickness (about 1 µm), PEDOT:PSS thin films damaged with a sharp blade can be healed by simply wetting the damaged area with water. The process is rapid, with a response time on the order of 150 ms. Significantly, by blending with other polymers, the films are transformed into autonomic self-healing materials without the need of external stimulation. This reveals a new property of PEDOT:PSS and enables its immediate use in flexible and biocompatible electronics, such as electronic skin and bio-implanted electronics, placing conducting polymers on the front line for healing applications in bioelectronics. References [1] S. Zhang, F. Cicoira, Water-Enabled Healing of Conducting Polymer Films, Adv. Mater. 29, 1703098, 2017. [2] Y. Li, X. Li, S. Zhang, L. Liu, N. Hamad, S. R. Bobbara, D. Pasini, F. Cicoira, Autonomic self-healing of PEDOT:PSS achieved via polyethylene glycol addition, Adv. Funct. Mater. 30, 2002853, 2020. [3] Y. Li, S. Zhang, N. Hamad, K. Kim, L. Liu, M. Lerond, F. Cicoira, Tailoring the Self-Healing Properties of Conducting Polymer Films, Macromol. Biosci. i2000146, 2020.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".