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 as well as for implantable electrodes. Our group fabricated water-stable and flexible organic electrochemical transistors based on poly(3,4-ethylenedioxythiophene) doped with poly(styrenesulfonate) (PEDOT:PSS) on a plastic substrate using a new process based on a fluorinated photoresist. The PEDOT:PSS films, mixed solely with a biocompatible conductivity enhancer, show robust adhesion on plastic substrates, and exhibit unchanged electrical properties under extreme bending. This simplifies the fabrication of high-performance OECTs and places them in a highly competitive position for flexible electronics and healthcare applications. The fabrication of stretchable electronic devices is presently rather challenging due to both the limited number of materials showing the desired combination of mechanical and electrical properties and the lack of techniques to process and pattern them. My group reported on transfer patterning process to fabricate high-resolution metal microelectrodes on polydimethylsiloxane (PDMS) by using ultrathin Parylene films (2 μm thick). By combining transfer patterning of metal electrodes with orthogonal patterning of PEDOT:PSS on a pre-stretched PDMS substrate and a biocompatible “cut and paste” hydrogel, we demonstrated fully stretchable organic electrochemical transistors, relevant for wearable electronics, biosensors and surface electrodes to monitor body conditions. 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, after being wetted, 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. We have recently electropolymerized PEDOT coatings on sharp platinum-iridium recording and stimulating neural electrodes and demonstrated its mechanical and electrochemical stability Electropolymerization of PEDOT:tetrafluoroborate was carried out in three different solvents: propylene carbonate, acetonitrile and water. The stability of the coatings was assessed via ultrasonication, phosphate buffer solution soaking test, autoclave sterilization and electrical pulsing. Coatings prepared with propylene carbonate or acetonitrile possessed excellent electrochemical stability and survived autoclave sterilization, prolonged soaking and electrical stimulation without major changes in electrochemical properties. Stimulating microelectrodes were implanted in for 60 days. The electrochemical properties monitored in vivo demonstrated that coated electrodes show lower impedance and higher stability over time.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".