Application of Carbon Nanotubes Doped with Silicon As the Anode Electrode for Lithium Ion Battery
Bibliographic record
Abstract
It is well known that the structural modification of carbon nanotubes (CNT) with heteroatoms, could modify their physical and chemical properties. These modifications open the possibilities to improve the electrochemical performance of CNT thus enhancing their application in batteries for storage of lithium ions. However, to achieve such characteristics it is important to control its structure, morphology and chemical composition during synthesis. In this work, the CNT were modified in situ by the intercalation of silicon (CNT-Si) in the graphitic carbon network to be used as an anode electrode in lithium ion battery. CNT-Si were synthesized by a modified chemical vapor deposition; toluene, ferrocene and triphenylsilane were used as carbon source, metal catalyst and silicon precursor, respectively. The effect of doping and temperature was investigated using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy and X ray photoelectron spectroscopy (XPS). The microscopy results showed that the CNT-Si were structurally modified with various forms of roughness, distortions and defects not only in the inner walls but also on outer walls. The elevated synthesis temperature had the most significant effect in the graphitic carbon network. According to the Raman scattering, the CNT-Si presented greater structural disorder due to the integration of silicon atoms in the carbon, which increased the disorder in hexagonal network. Elemental analysis composition by XPS indicated that the silicon was intercalated preferably at a higher temperature with a concentration of 0.76±10 at. %, clearly showing that silicon was successfully linked in the carbon network as Si-C. In order to examine the electrochemical properties of the materials, CNT-Si were used as an anode electrode for galvanostatic charge and discharge tests, as well as for cyclic votammetry curves. The results highlighted that temperature played a very important role on the electrocatalytic characteristics of materials and the insertion of the silicon in the carbon structure provided more sites for the diffusion and storage of lithium. The processes of alloying and de-alloying lithium in the CNT-Si matrix, charge and discharge capacity, as well as its cyclic performance will be discussed.
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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".