Single-Atom Catalyst with Optimized Ni Content in a Flexible Zn-Air Battery Operated at a Wide Temperature Range
Bibliographic record
Abstract
Flexible and safe energy storage systems are critical for the advancement of wearable and portable electronics. Although lithium-ion batteries dominate the market, their reliance on flammable electrolytes and rigid structures limits their use in flexible applications. Herein, we report the development of a flexible Zn–air battery featuring a nitrogen-doped lamellar carbon cathode embedded with Ni single-atom catalytic sites. The battery demonstrated a high areal capacity of ∼32 mA·h cm –2 and sustained stable operation over nearly 325 charge–discharge cycles. It also achieved a maximum discharge current density of 150 mA cm – 2 under the polarization conditions. In the half-cell configuration, the optimized Ni–N x catalyst exhibited a low overpotential of 1.45 V vs. RHE at 10 mA cm – 2 for the oxygen evolution reaction, outperforming the benchmark IrO 2 catalyst (1.49 V vs. RHE). The full cell maintained excellent electrochemical stability across a broad temperature range (5–60 °C) and retained its functionality under severe mechanical deformation, including bending, cutting, and puncturing. Postcycling SEM analysis revealed the formation of vertically aligned Zn nanostructures that effectively suppressed dendrite growth.
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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".