Experimental modulation of electrochemical energy storage characteristics of cobalt metal-organic framework-based electrode materials via organic linker variance
Bibliographic record
Abstract
Metal-organic frameworks (MOFs) represent a class of materials characterized by metal ions coordinated with organic linkers, resulting in highly porous and adaptable microstructures. Their remarkable efficacy in ion exchange processes enables them to exhibit outstanding energy and power density capabilities. This study investigates the critical role of organic ligands Pyridine-2,6-dicarboxylic acid (H 2 PDC) and 5-Nitroisophthalic acid (5-NIP) in enhancing the electrochemical energy storage performance of pristine Cobalt-based MOFs (Co-MOFs). The sonochemically synthesized Co-H 2 PDC demonstrates a specific capacity of 1673.05 C/g at a scan rate of 2 mV/s and 1194.704 C/g at a current density of 2.8 A/g. Owing to its superior performance, a hybrid device was fabricated as Co-H 2 PDC//AC. The electrochemical performance of the hybrid device was evaluated using a two-electrode configuration. The Co-H 2 PDC//AC configuration achieved an impressive energy density of 82.18 Wh/kg and a power density of 4250 W/kg while maintaining 79% stability over 5000 consecutive galvanostatic charge-discharge cycles. Furthermore, the device's performance was further evaluated using simulation techniques to assess diffusive and capacitive contributions. The integration of MOFs as battery-type electrode materials paves the way for advanced energy storage devices.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.004 | 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".