Enhanced Electrochemical Behavior of Peanut-Shell Activated Carbon/Molybdenum Oxide/Molybdenum Carbide Ternary Composites
Bibliographic record
Abstract
Biomass-waste activated carbon/molybdenum oxide/molybdenum carbide ternary composites are prepared using a facile in-situ pyrolysis process in argon ambient with varying mass ratios of ammonium molybdate tetrahydrate to porous peanut shell activated carbon (PAC). The formation of MoO2 and Mo2C nanostructures embedded in the porous carbon framework is confirmed by extensive structural characterization and elemental mapping analysis. The best composite when used as electrodes in a symmetric supercapacitor (PAC/MoO2/Mo2C-1//PAC/MoO2/Mo2C-1) exhibited a good cell capacitance of 115 F g−1 with an associated high specific energy of 51.8 W h kg−1, as well as a specific power of 0.9 kW kg−1 at a cell voltage of 1.8 V at 1 A g−1. Increasing the specific current to 20 A g−1 still showcased a device capable of delivering up to 30 W h kg−1 specific energy and 18 kW kg−1 of specific power. Additionally, with a great cycling stability, a 99.8% coulombic efficiency and capacitance retention of ~83% were recorded for over 25,000 galvanostatic charge-discharge cycles at 10 A g−1. The voltage holding test after a 160 h floating time resulted in increase of the specific capacitance from 74.7 to 90 F g−1 at 10 A g−1 for this storage device. The remarkable electrochemical performance is based on the synergistic effect of metal oxide/metal carbide (MoO2/Mo2C) with the interconnected porous carbon. The PAC/MoO2/Mo2C ternary composites highlight promising Mo-based electrode materials suitable for high-performance energy storage. Explicitly, this work also demonstrates a simple and sustainable approach to enhance the electrochemical performance of porous carbon materials.
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 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) | 0.001 | 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".