Interface‐Engineered Dendrite‐Free Anode and Ultraconductive Cathode for Durable and High‐Rate Fiber Zn Dual‐Ion Microbattery
Bibliographic record
Abstract
Abstract Despite the advantages of the fiber‐shaped Zn‐ion microbattery (FZMB) in powering wearable electronics, several fundamental challenges hinder its practical application, mainly including dendrite growth on Zn anodes (leading to short cycle life) and low electrical conductivity of cathode (resulting in poor rate performance). Herein, a facile approach of sputtering a nano‐thin conductive carbon layer on Zn anode to effectively suppress dendrite growth and a dual‐conductive polymer strategy to fabricate ultraconductive core‐sheath fiber cathode (poly(3,4‐ethylenedioxythiophene)‐poly(styrene sulfonate) (PEDOT:PSS) fiber@polyaniline nanobulges) are demonstrated. The carbon layer suppresses Zn dendrites by uniformizing surface electric field and providing abundant nucleation sites. The superior conductivity of the cathode is inherited from two conductive polymers (in particular, PEDOT:PSS fibers have an ultrahigh conductivity of 3676 S cm−1) and their strong intermolecular interactions. The resulting FZMB shows excellent stability (over 100% capacity retention after 3000 cycles) and supercapacitor‐level rate performance (73% capacity retention from 0.1 to 10 A g−1). Kinetics and mechanism studies reveal that the surface‐controlled dual‐ion migration mechanism is also correlated with the high rate performance. The corresponding quasi‐solid‐state device exhibits high stability under extreme deformation conditions and superior water‐proof capability (94.6% capacity retention after 12 h underwater immersion), demonstrating great practical application potential.
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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) | 0.000 | 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 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".