Electrochemical Performance of FeF3·0.33H2O/MWCNTs Composite Cathode Synthesized by Solvothermal Process
Bibliographic record
Abstract
This paper reports a FeF3·0.33H2O/multi-walled carbon nanotubes (MWCNTs) composite for energy storage applications. The composite material is prepared by solvothermal reaction with FeF3·3H2O and MWCNTs as precursors, and FeF3·3H2O was removed of crystalliferous water and converted to FeF3·0.33H2O during solvothermal treatment. Structural characterizations show that FeF3·0.33H2O that crystalline with a diameter of about 30 nm were distributed in the network of MWCNTs. As a cathode material for lithium ion batteries, FeF3·0.33H2O/MWCNTs was superior to pure FeF3·0.33H2O in terms of high capacity (an initial capacity of 181 mAh g-1 in 2.0-4.3 V at 20 mA g-1), good cycleability (50% capacity retension at 50th cycle) and good rate capability (116 mAh g-1 at 100 mA g-1). The enhanced performances were attributed to the conductive MWCNT network which improved the electron transport ability and buffered volume change of the cathode.
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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".