Dual Ni/Co-hemin metal–organic framework-PrGO for high-performance asymmetric hybrid supercapacitor
Bibliographic record
Abstract
Abstract In this study, we conducted direct synthesis of a dual metal–organic framework (Ni/Co-Hemin MOF) on phosphorous-doped reduced graphene oxide (PrGO) to serve as an active material in high-performance asymmetrical supercapacitors. The nanocomposite was utilized as an active material in supercapacitors, exhibiting a noteworthy specific capacitance of 963 C g −1 at 1.0 A g −1 , along with a high rate capability of 68.3% upon increasing the current density by 20 times, and superior cycling stability. Our comprehensive characterization and control experiments indicated that the improved performance can be attributed to the combined effect of the dual MOF and the presence of phosphorous, influencing the battery-type supercapacitor behavior of GO. Additionally, we fabricated an asymmetric hybrid supercapacitor (AHSC) using Ni/Co-Hemin/PrGO/Nickel foam (NF) and activated carbon (AC)/NF. This AHSC demonstrated a specific capacitance of 281 C g −1 at 1.0 A g −1 , an operating voltage of 1.80 V, an impressive energy density of 70.3 Wh kg −1 at a high power density of 0.9 kW kg −1 . Notably, three AHSC devices connected in series successfully powered a clock for approximately 42 min. These findings highlight the potential application of Hemin-based MOFs in advanced supercapacitor systems.
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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".