Free-Standing S-CNT-rGO Nanocomposite Paper Cathodes for Li-S Batteries
Bibliographic record
Abstract
For electric vehicles (EVs), hybrid electric vehicles (HEVs), and smart electric grids, it is important to develop advanced energy storage systems due to the ever-increasing demands for high energy density and long-life energy sources.With a high theoretical gravimetric energy density of 2500 Wh kg -1 , Lithium-sulfur (Li-S) batteries are considered to be one of the most promising candidates in this respect [1].However, the practical electrochemical performance of Li-S battery have been restricted by the low conductivity of sulfur and the insoluble and insulating lithium sulfides, Li2S2/Li2S on the cathode surface [2].To resolve these problems, especially carbon materials are used to increase the conductivity.Due to their high electrical conductivity, porous carbon, carbon nanotubes (CNTs) and reduced graphene oxide (rGO) are generally used to enhance the conductivity of sulfur and Li2S / Li2S2 during charge-discharge process [3].In this work, we produced S-CNT-rGO nanocomposites as binderless free-standing paper.Firstly, functionalized MWCNTs were prepared with H2SO4/HNO3 mixture (3:1, v/v) and graphite oxide was produced by modified Hummers method.Then, Na2S2O3.5H2Oprecursor was added into the mixture of graphite oxide and CNTs.After ultrasonication of 2h, HCl solution was added dropwise to resulting homogeneous suspension.During this process, the sulfur anions reduced and deposited on the surface of the graphene oxide and CNTs as sulfur nanoparticles.The resulting suspension was filtered through a 0.22 µm porous PVDF membrane filter (Millipore, Durapore Membrane) with a vacuum filtration system and washed three times with deionized water and ethanol.After the paper dried, it was peeled off the membrane and flexible S-CNT-GO paper was obtained.To obtain S-CNT-rGO from this structure, the S-CNT-GO paper was treated with a dilute solution of hydrazine as reducing agent.Obtained papers were characterized by field emission scanning electron microscopy (FESEM), energy dispersive X-ray spectrometer (EDS), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR) analyses.Electrochemical analysis was performed using battery tester device.Charge-discharge capabilities, specific capacity and capacity retention parameters were investigated of the cathode electrodes assembled in the type of CR2032 cells.When the results have been evaluated, it has seen that the aimed structure of S-CNT-rGO has been obtained for advanced Li battery applications.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".