Flexible cellulose-based hybrid nanogenerators for self-powered wearable bio-monitoring applications
Bibliographic record
Abstract
Cellulose-based flexible hybrid nanogenerator (HNG) with remarkable durability for self-powered wearable biosensor devices were fabricated using polydopamine @ barium titanate /cellulose acetate nanofiber (PDA@BTO/CA) films, exhibiting stable signal outputs in extreme conditions, such as underwater, and in high or low-temperature environments. Flexible hybrid nanogenerators (HNGs) have received significant attention for their potential in harvesting mechanical energy to power portable and miniaturized portable devices. This work presents a method to fabricate flexible, durable and biodegradable electrospun polydopamine@barium titanate/cellulose acetate (PDA@BTO/CA) nanofiber films. This design integrates polydopamine (PDA) and piezoelectric barium titanate (BTO) nanoparticles within a flexible cellulose acetate (CA) matrix to enable self-powered wearable biomonitoring. The inclusion of PDA enhances the physical adhesion between BTO and CA, resulting in a significant 40% increase in voltage output. Notably, the PDA-modified composite PDA@BTO/CA demonstrates remarkable durability over 15,000 cycles and effectively detects a range of human motions (such as fist clenching, wrist bending, elbow movement, walking, running and jumping), transducing them into stable, precise electrical signals. Intriguingly, the hybrid nanogenerator device exhibits robust performance in extreme conditions, including underwater and high or low temperatures, while maintaining its good biodegradability. This work paves the way for advanced self-powered wearable biosensor devices capable of precise and reliable human motion monitoring.
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.
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".