Lignin Cellulose Nanofibrils as an Electrochemically Functional Component for High‐Performance and Flexible Supercapacitor Electrodes
Bibliographic record
Abstract
Abstract The increasing demand for wearable electronics has driven the development of supercapacitor electrode materials toward enhanced energy density, while being mechanically strong, flexible, as well as environmentally friendly and low‐cost. Taking advantage of faradaic reaction of quinone groups in natural lignin that is covalently bound to the high‐strength cellulose nanofibrils, the fabrication of a novel class of mechanically strong and flexible thin film electrodes with high energy storage performance is reported. The electrodes were made by growing polyaniline (PANI) on flexible films composed of lignin‐containing cellulose nanofibrils (LCNF) and reduced graphene oxide (rGO) nanosheets at various loading levels. The highest specific capacitance was observed for the LCNF/rGO/PANI electrode with 20 wt% rGO nanosheets (475 F g −1 at 10 mV s −1 and 733 F g −1 at 1 mV s −1 ), which represented a 68 % improvement as compared to a similar electrode made without lignin. In addition, the LCNF/rGO(20)/PANI electrode demonstrated high rate performance and cycle life (87 % after 5000 cycles). These results indicated that LCNF functioned as an electrochemically active multifunctional component to impart the composite electrode with mechanical strength and flexibility and enhanced overall energy storage performance. LCNF/rGO(20)/PANI electrode was further integrated in a flexible supercapacitor device, revealing the excellent promise of LCNF for fabrication of advanced flexible electrodes with reduced cost and environmental footprint and enhanced mechanical and energy storage performances.
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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".