Investigation of magnetron sputtered Ni@Cu/ <scp> WS <sub>2</sub> </scp> as an electrode material for potential supercapattery devices
Bibliographic record
Abstract
The supercapattery, a hybrid device with both capacitive and battery characteristics, owing to its excellent energy, capacity and power capabilities has broadly been recognized as an eminent energy storage device. With such fascinating features, it still craves for efficient electrode materials to improve energy storage performance. Our study presents the electrochemical analysis of magnetron sputtered pristine tungsten disulfide (WS2) and WS2 anchored over copper (Cu) interfacial layer by employing nickel foam as a current collector. To probe the structural composition, surface morphology and elemental analysis of sputtered materials, X-ray diffraction, scanning electron microscopy and energy-dispersive X-ray spectroscopy are utilized. By employing three-electrode cell configuration the deposited electrodes are then examined for electrochemical characterizations. The optimal electrode Ni@Cu/WS2 (S2) in this assembly revealed a specific capacity (Qs) of 357 C/g at 3 mV/s and 247.4 C/g at 0.5 A/g. Relying on the electrochemical performance, S2 is further utilized for asymmetric architecture (hybrid device), and hence attained Qs of 185.8 C/g and divulged high energy (Ed) and power (Pd) of 43.9 Wh/kg and 425 W/kg, respectively. Furthermore, for cyclic performance at a high current density js of 8 A/g, the device exhibited efficient stability performance of 98.1% against 4500 consecutive galvanostatic charge discharge (GCD) cycles. Moreover, by applying the semi-empirical approach, a device is assessed for capacitive and diffusive contribution, with maximum contribution of 36.93% and 93.68% against potential scan rates of 100 and 3 mV/s, respectively. All the intriguing results attained via magnetron sputtered S2 vibrantly increase its worth as an electrode material for practical hybrid device applications.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".