To Study the Effect of LiMn2O4, Nanofibers of LiMn2O4, and Graphene/Polyaniline/Carbon Nanotube as Electrode Materials in the Fuel Cell
Bibliographic record
Abstract
This study is conducted to explore the best electrodes materials for energy conversion devices.The two cathode materials (LiMn2O4 and nanofibers of LiMn2O4) and the anode material (graphene/polyaniline/carbon-nanotube) were synthesized by a wet chemical method which includes sol-gel and chemical polymerization techniques.The prepared materials were characterized by SEM, XRD FTIR, and cyclic voltammetry.The characterization results show that LiMn2O4 exhibits a porous and hollow structure, which improves the utilization of the active mass area, and allows the dual conduction of Li+ and electrons, which effectively relieves the structural strain and volume change.The cyclic voltammetry results record that LiMn2O4 and nanofibers of LiMn2O4 as a cathode material enhanced the cycling performance and possess excellent stability.Further, the conductivity of each sample was measured using the DC four-probe method, and the highest conductivity was observed for the LiMn2O4 nanofibers 1.43 SCm -1 at 650℃.
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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 | 0.001 |
| 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".