High-Performance Fiber-Shaped Zn Microbattery Based on Dendrite-Free Anode and Ultraconductive Cathode
Bibliographic record
Abstract
Rechargeable Zn-ion microbatteries emerge as a promising power solution due to their remarkable safety, high capacity, low cost, simple manufacturing, and environmental friendliness. Their fiber-shaped counterparts are particularly attractive due to their lightweight, tiny volume, and mechanical flexibility. However, it is still fundamentally challenging to construct high-performance fiber-shaped Zn-ion microbatteries (FZMB) because of the dendrite growth at the anode, the poor electrical conductivity of current cathode materials, the lack of suitable fiber substrates (high electrical conductivity and strong interaction with cathode materials). We developed a simple and scalable process to fabricate dendrite-free fiber anodes by sputtering an ultrathin conductive carbon layer on rock-like Zn deposits around carbon fibers (CF) . The carbon layer plays a critical role in suppressing dendrites by uniformizing the surface electric field and provide additional surface and abundant nucleation sites. The obtained CF@Zn@C can stably run over 200h. Plus, we demonstrate a highly conductive and well-interacted fiber cathode, i.e., PEDOT: PSS@PANI core-sheath fiber, with a record high conductivity of 3676 S cm−1. The superior conductivity enables a fast electron transfer which is beneficial to high rate performance. Based on the same PEDOT: PSS platform, we have fabricated the next-generation FZMB by using citriate as electrolyte additives to suppress the dendrite formation. Compared to the carbon layer on the Zn anode, the use of additives in the electrolyte is much easier in production. . Figure 1
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 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) | 0.001 | 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".