Highly Stable Ag–Au Core–Shell Nanowire Network for ITO‐Free Flexible Organic Electrochromic Device
Bibliographic record
Abstract
Abstract Solid and flexible electrochromic (EC) devices require a delicate design of every component to meet the stringent requirements for transparency, flexibility, and deformation stability. However, the electrode technology in flexible EC devices stagnates, wherein brittle indium tin oxide (ITO) is the primary material. Meanwhile, the inflexibility of metal oxide usually used in an active layer and the leakage issue of liquid electrolyte further negatively affect EC device performance and lifetime. Herein, a novel and fully ITO‐free flexible organic EC device is developed by using Ag–Au core–shell nanowire (Ag–Au NW) networks, EC polymer and LiBF4/propylene carbonate/poly(methyl methacrylate) as electrodes, active layer, and solid electrolyte, respectively. The Ag–Au NW electrode integrated with a conjugated EC polymer together display excellent stability in harsh environments due to the tight encapsulation by the Au shell, and high area capacitance of 3.0 mF cm−2 and specific capacitance of 23.2 F g−1 at current density of 0.5 mA cm−2. The device shows high EC performance with reversible transmittance modulation in the visible region (40.2% at 550 nm) and near‐infrared region (−68.2% at 1600 nm). Moreover, the device presents excellent flexibility (>1000 bending cycles at the bending radius of 5 mm) and fast switching time (5.9 s).
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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) | 0.001 | 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".