Flash Point of Gel-Polymer Electrolytes: Effect of the Molecular Interaction between Nitrile (HNBR) and Carbonyl (PC)
Bibliographic record
Abstract
Gel-polymer electrolytes are receiving increasing attention as they compromise between a good ionic conductivity (10 -3 S/cm) [1, 2] and good safety features. The solvent trapped into the polymeric matrix increases the ionic conductivity while the polymeric matrix enhances safety due to its mechanical strength repressing dendrite growth [3, 4]. Gel polymer electrolytes are almost universally presumed to be less flammable than current commercialize battery (organic liquid electrolyte) [5, 6]. However, there is no universal test to compare the flammability of a liquid and the flammability of a gel. Our work focuses on the flash point measurement of gel-polymer electrolytes. The flash point temperature is a standardized test and is one of the top experiments to measure flammability [7]. The Flash point temperature is well studied for liquid electrolytes [7, 8] but had never been conducted for gel-polymers. We developed a method to analyze the flash point of gel-polymer electrolytes by pairing the closed-cup flash point tester with a thermal imaging camera. This new apparatus was used it to analyze a promising system: HNBR with different grade of nitrile doped with PC. The goal is to find the relation between the flash point and the nitrile contains in the polymeric matrices. Our research sheds light on the effect of molecular interactions between the nitrile of HNBR and the carbonyl of PC on the flammability of the overall gel-polymer electrolyte with FT-IR. The study has also been conducted adding a lithium salt (LiTFSI) to be representative of real battery application. Agrawal, R.C. and G.P. Pandey, Solid polymer electrolytes: materials designing and all-solid-state battery applications: an overview. J. Phys. D: Appl. Phys., 2008. 41 (22): p. 223001-223019. Cheng, X., et al., Gel Polymer Electrolytes for Electrochemical Energy Storage. Advanced Energy Materials, 2018. 8 (7). Hassouna, J. and B. Scrosati, Review—Advances in Anode and Electrolyte Materials for the Progress of Lithium-Ion and beyond Lithium-Ion Batteries. Journal of The Electrochemical Society, 2015. 162 p. A2582-A2588. Ren, W., et al., Advanced gel polymer electrolytes for safe and durable lithium metal batteries: Challenges, strategies, and perspectives. Energy Storage Materials, 2021. 34 : p. 515-535. Castillo, J., et al., Safe, Flexible, and High-Performing Gel-Polymer Electrolyte for Rechargeable Lithium Metal Batteries. Chemistry of Materials, 2021. 33 (22): p. 8812-8821. Li, Q., et al., Progress in electrolytes for rechargeable Li-based batteries and beyond. Green Energy & Environment, 2016. 1 (1): p. 18-42. Liu, X.S. and Z.Y. Liu, Research Progress on Flash Point Prediction. Journal of Chemical and Engineering Data, 2010. 55 (9): p. 2943-2950. Catoire, L., S. Paulmier, and V. Naudet, Experimental determination and estimation of closed cup flash points of mixtures of flammable solvents. Process Safety Progress, 2006. 25 (1): p. 33-39.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".