Facile Synthesis of Ni/Co (Hydr)oxides with Nanosheet Structure for High Performance Supercapacitors
Bibliographic record
Abstract
In this article, the novel kind of binary metal oxides, Ni/Co (hydr)oxides, with nanosheet structure have been successfully established via a facile hydrothermal self-assembled process with ammonia solution as the reaction reagent. The as-prepared samples with peculiar morphologies and characteristics are easily realized by just controlling the calcination temperatures. The composition, morphology, and microstructure of the products were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS). The thermogravimetric analysis (TGA) revealed the decomposition details of the precursor. Electrochemical measurements show that the sample calcined at 250°C has the optimized capacitive performance, demonstrated by cyclic voltammetry and galvanostatic charge-discharge cycling techniques. The Ni/Co hydroxide nanosheets as electrode materials for supercapacitor exhibit high specific capacitance of 1427 F g -1 at 1 A g -1 , and 1270 F g -1 at 10 A g -1 , indicating an excellent rate capability. Also, the superior cyclic stability with the capacitance retention of 92.3% is achieved even over 3000 cycles at a high current density of 10 A g -1 . The improved capacity and cycling stability makes it promising electrode material for offering an effective way to achieve high supercapacitor performance.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".