Nanocomposite of TiO<sub>2</sub> Nanoparticles-Reduced Graphene Oxide with High-Rate Performance for Li-Ion Battery
Bibliographic record
Abstract
A simple and effective method is developed to synthesize the nanocomposites of anatase TiO2 nanoparticles deposited on the reduced graphene oxide (TiO2-RGO) sheets as anode materials for Li-ion battery applications. Structure analyses demonstrated that anatase TiO2 nanoparticles were well dispersed onto the reduced graphene oxide nanosheets with chemical bonds. These TiO2-RGO nanocomposites were electrochemically investigated in the coin-type cells versus metallic lithium, and the lithium storage performance of these nanocomposites showed the enhanced high-rate capabilities and good cycling stability. These improved electrochemical performance can be attributed mainly to efficient dispersion of TiO2 nanocrystals on the surface of conductive RGO sheets, which makes these TiO2-RGO nanocomposites practical for high-rate Li-ion battery applications.
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 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".