Preparation and Electrochemical Studies of Metal Fluorides for Lithium Batteries
Bibliographic record
Abstract
Conventional positive (cathodes) electrode materials for lithium batteries, use mixed-conducting lithium containing transition metal oxides, metal phosphates etc. which are able to store both lithium and electrons by changing their oxidation state. In this presentation, we discuss the facile synthesis of materials suitable for alternative electrode concepts including Transition metal fluorides MF2 (M=Fe, Mn, Zn) were obtained by reacting Fe, Mn, Zn-Metal salts with fumaric acid as a one-dimensional metal organic framework, and a polymer (PVDF) as Fluorine source, final products are obtained by heating at 600°C, 6h in Ar gas. The MOF were initially prepared by a simple chimie douce method. Incorporation of the MOF with a fluorinated polymer and the eventual decomposition lead to carbon coated metal fluoride nanoparticles of high surface area of >200 m2/g for FeF2. The obtained materials will be characterized in detail by X-ray diffraction, Scanning and Transmission electron microscope (SEM/TEM) are used to evaluate the structure and morphology, X-ray photoelectron spectroscopy are used understand structure, vibrational bands and oxidation state of the materials and BET surface area method. Electrochemical studies were carried out in the voltage, range 4 to 1.0 vs. Li, at current rate of 50 mA/g (0.1 C) using 1MLiPF6 (EC;DEC) as liquid electrolyte and tested with Li-metal as a counter and reference electrodes. The cyclic voltammetry at scan rate of 0.075 mV/sec at room temperature (24°C). Galvanostatic cycling of FeF2 demonstrates that the material exhibit stable and good reversible capacity of 580 mAh/g during the first cycle and slight capacity fading has been observed after 20 cycles. Further studies on rate performance is being carried up to 2.5 C rate. Whereas MnF2 and ZnF2 showed reversible capacity of 220 and 200 mAh/g and retained a capacity around 100 mAh/g after 20 cycles and showed lower capacity than FeF2. Discuss the structural, reaction mechanism of FeF2 during charge-discharge cycling by in situ/operando X-ray diffraction and electrochemical impedance spectroscopy studies discuss in detail. Keywords: Metal fluorides (MF2 M=Fe, Zn, Mn); Electrochemical properties; Insitu studies; Electrochemical impedance spectroscopy; energy storage
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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 | 0.001 |
| 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".