Blend of Polymers As New Solid Electrolytes for Lithium-Ion Batteries
Bibliographic record
Abstract
With the increase of energy demand, the depletion of oil reserves and the development of intermittent renewable energy sources, the storage and the production of energy are one of the main concerns of the XXI century. Lithium Ion Battery (LIB) are among the best choices because of their high energy and power densities, longer lifespan and lighter than other energy storage systems. [1] LIB are composed of two intercalation electrodes, electronically isolated by an ions conductive electrolyte. The early LIB were composed of an organic liquid electrolyte. However, they had many disadvantages, the most worrying of which is their safety concern related to short-circuits and potential leakages of the flammable liquid solvent [2]. In this context, the development of new solid materials for electrolyte (such as ceramics and polymers) are a central issue. Solid Polymer Electrolyte (SPE) are among the most promising solution to deal with safety problems. They are ionically conducting solid material in which lithium salts are dissolved thanks to polar groups [3]. In LIBs, polymer electrolyte has a dual role. It plays both the role of separator between electrodes and binder in the composite electrodes. Chemical and electrochemical stabilities, absence of solvents intercalation and good interfacial contact between active material and electronic components are among the advantages of SPE. The conduction mechanisms in polymer are quite different from the processes in low molecular weight solvents and are still not fully understood. Cation transport in polymer involves two steps which are considered to be dissociated or not, depending on the model chosen (Arrhenius or Vogel-Fulcher-Tammann, respectively) [4]. Above the glass transition temperature, segmental motions of polymer chains allow ions hopping between coordinating sites on the same polymer chain or between two neighbouring chains. According to previous studies, ionic conduction takes place mainly in the amorphous phase with high segmental motions. That’s why, polymer electrolytes often suffer from poor ionic conductivity at room temperature (less than 10 -5 S/cm) compared to their liquid counterparts. Lots of research tried to improve this factor by decreasing the crystalline part and the glass transition, melting and crystallisation temperatures, but to the detriment of mechanical, thermal or electrochemical stabilities. Our team made an effort to preserve a good ionic conductivity, and at the same time, improve other stability properties, by using a blend of polymers. The existence of functional polar groups makes them ideal candidates to dissolve lithium salts (such as Lithium bis(trifluoromethanesulfonyl)imide LiTFSI) and Lithium bis(fluorosulfonyl)imide (LiFSI)) and form stable ion-polymer complexes. In this work, thermal, mechanical and electrochemical properties of our solid polymer electrolyte based on different ratios of each polymer and salt were characterized thanks to Differential Scanning Calorimetry (DSC), Atomic Force Microscopy (AFM) and other electrochemical techniques (such as Electrochemical Impedance Spectroscopy and Cyclic Voltammetry). Conduction mechanisms and salt/polymers interactions are characterised thanks to Scanning electron microscopy, Energy Dispersive X-ray Spectroscopy (SEM/EDX) and Fourier-transform Infrared Spectroscopy (FTIR). Half-cells with high voltage cathodes (LiNiMnCoO 2 (NMC), LiFePO 4 (LFP)) and low voltage anodes (Graphite, Li 4 Ti 5 O 12 (LTO)) showed high charge/discharge capacity at 0.1C (at 60°C and 50°C). These first results indicate that this blend of polymers is a promising candidate as SPE for Lithium-Ion Batteries. References : J. B. Goodenough and K. S. Park, American Chemical Society , 2013 , 135, 1167-1176. D. Baril, C. Michot and M. Armand, Solid State Ionics , 1997 , 94, 35-47. F. M. Gray, Solid polymer electrolytes , VCH New Tork, 1991 . R. C. Agrawal and G. P. Pandey, Journal of Physics D: Applied Physics , 2008 , 41, 223001.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".