Direct Growth of Vertically-Aligned Single-Walled Carbon Nanotubes on Conducting Substrates using Ethanol for Electrochemical Capacitor
Bibliographic record
Abstract
A massive growth of vertically-aligned single-walled carbon nanotubes (VA-SWCNTs) from aluminum oxide (Al-O)-supported Co catalyst and high purity ethanol was performed using alcohol catalytic chemical vapor deposition (ACCVD) technique. SWCNTs with 50-μm thickness were grown on the substrates via this technique. The Al metal layer of 20 nm thickness was thermally-oxidized for the production of Al-O, and 0.5 nm cobalt (Co) thin films was used as catalyst for the CVD process. The CNT growth was optimized using SiO2/Si substrates, and similar experimental condition was applied to the conducting substrates. The as-grown CNTs were characterized using Raman spectroscopy and electron microscopies for growth confirmation and for quality level investigation. Development of the catalyst nanoparticles and Al-O support layer was observed using atomic force microscopy (AFM) and transmission electron microscopy (TEM). The electrodes were fabricated using directly-grown VA-SWCNTs on SUS 310S, and were successfully used as an electrochemical capacitor. Electrochemical analysis using KOH aqueous electrolyte was performed by cyclic voltammetric (CV) and galvanostatic chargedischarge measurements; a maximum 52 Fg-1 specific gravimetric capacitance was obtained from the VA-SWCNT electrodes.
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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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".