Printable Conductive Hydrogels and Elastomers for Biomedical Application
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Printed flexible materials have garnered considerable attention as next-generation materials for bioelectronic applications, particularly hydrogels and elastomers, owing to their intrinsic softness, tissue-like mechanical compliance, and electrical conductivity. In contrast to conventional fabrication approaches, printing technologies enable precise spatial control, design versatility, and seamless integration with complex biological interfaces. This review provides a comprehensive overview of the progress in printable soft conductive materials, with a particular emphasis on the composition, processing, and functional roles of conductive hydrogels and elastomers. This review first introduces traditional fabrication methods for conductive materials and explains the motivation for using printing techniques. We then introduce two major classes of soft conductive materials, hydrogels and elastomers, and describe their applications in both in vitro systems, such as biosensors and soft stimulators, and in vivo settings, including neural interfaces and implantable devices. Finally, we discuss current challenges and propose future directions for advancing printed soft bioelectronics toward clinical translation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it