Durable ZrB<sub>2</sub>–ZrC Composite Materials as Advanced Electrodes for High-Performance Supercapacitors
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Boride and carbide-based materials attract increasing attention as promising options for energy storage applications. This research focuses on synthesizing pure boride and carbide compounds of zirconium (ZrB 2 and ZrC) and their composite powders using mechanical activation-assisted route and subsequent heating processes. The chemical and microstructural characterization results indicate that the synthesized composite powders are of high purity, possess submicron-scale particle sizes (below 400 nm), and exhibit a high surface area of up to 9.41 m 2 /g. Supercapacitor devices, using the resulting powders as symmetrical electrodes, exhibit high energy density values ranging from 5.8 to 8.8 Wh/kg. The ZrB 2 –15 wt % ZrC composite sample achieves the highest power density at 155 W/kg, compared to 118 W/kg for the pure ZrB 2 sample. Cycling tests demonstrate exceptional capacitance retention (99.4–99.9%) and cyclic stability, even after 5000 cycles, highlighting the high durability of the composite samples. These findings show that ZrB 2 –ZrC composites exhibit high energy and power density values and excellent cycling performance, making them strong candidates for use in high–performance supercapacitor devices.
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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".