Facile Synthesis of Battery-Type CuMn2O4 Nanosheet Arrays on Ni Foam as an Efficient Binder-Free Electrode Material for High-Rate Supercapacitors
Bibliographic record
Abstract
The development of battery-type electrode materials with hierarchical nanostructures has recently gained considerable attention in high-rate hybrid supercapacitors. For the first time, in the present study novel hierarchical CuMn2O4 nanosheet arrays (NSAs) nanostructures are developed using a one-step hydrothermal route on a nickel foam substrate and utilized as an enhanced battery-type electrode material for supercapacitors without the need of binders or conducting polymer additives. X-ray diffraction, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) techniques are used to study the phase, structural, and morphological characteristics of the CuMn2O4 electrode. SEM and TEM studies show that CuMn2O4 exhibits a nanosheet array morphology. According to the electrochemical data, CuMn2O4 NSAs give a Faradic battery-type redox activity that differs from the behavior of carbon-related materials (such as activated carbon, reduced graphene oxide, graphene, etc.). The battery-type CuMn2O4 NSAs electrode showed an excellent specific capacity of 125.56 mA h g−1 at 1 A g−1 with a remarkable rate capability of 84.1%, superb cycling stability of 92.15% over 5000 cycles, good mechanical stability and flexibility, and low internal resistance at the interface of electrode and electrolyte. Due to their excellent electrochemical properties, high-performance CuMn2O4 NSAs-like structures are prospective battery-type electrodes for high-rate supercapacitors.
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".