LiPO<sub>2</sub>F<sub>2</sub> As an Additive in Li[Ni<sub>0.5</sub>Mn<sub>0.3</sub>Co<sub>0.2</sub>]O<sub>2</sub>/Graphite Pouch Cells
Bibliographic record
Abstract
Lithium ion cells with longer lifetime, higher energy density and better rate capability are of interest for electric vehicle (EV) makers. The use of electrolyte additives is one of the most effective ways of improving cell performance1–3. In this work, LiPO2F2 was used as an electrolyte additive to promote the performance of Li[Ni0.5Co0.2Mn0.3]O2 (NMC532)/graphite pouch cells. LiPO2F2 was graciously provided by Guangzhou Tinci New Materials Technology Co. and Shenzhen Capchem Technology Co. Experiments were performed using a high temperature (60°C) storage system, the ultra high precision charger (UHPC) at Dalhousie University, electrochemical impedance spectroscopy (EIS), in-situ gas evolution measurements and long term cycling tests (40°C and 20°C). LiPO2F2 containing cells demonstrated excellent capacity retention at both 40°C and 20°C, better impedance control, gas reduction and good rate capability at room temperature. The results of advanced characterization methods such as XPS and NMR to elucidate the impact of LiPO2F2 on the solid electrolyte interface layers will be reported, if available. Figures 1a - 1c) show that LiPO2F2-containing NMC532/graphite pouch cells have better capacity retention, lower polarization growth and higher energy efficiency during long term cycling between 3.0 and 4.3 V at 40°C. Figures 1d - 1f) show that LiPO2F2-containing NMC532/graphite pouch cells have less voltage drop, less gas production and better impedance control during storage testing at high temperature (60°C). The results here suggest that LiPO2F2 is a very promising electrolyte additive for improving cell performance from many perspectives. The synergetic effect between LiPO2F2 and other useful electrolyte additives needs to be explored carefully. References: 1. M. Nie, J. Xia, L. Ma, and J. R. Dahn, J. Electrochem. Soc., 162, A2066–A2074 (2015). 2. D. Aurbach, K. Gamolsky, B. Markovsky, Y. Gofer, M. Schmidt, and U. Heider, Electrochimica Acta, 47, 1423–1439 (2002). 3. K. Xu, Chem. Rev., 114, 11503–11618 (2014). Figure 1(a-c) Normalized discharge capacity (a), the difference between average charge voltage and average discharge voltage (b) and energy efficiency versus cycle number for NMC532/graphite pouch cells with or without LiPO2F2 in 1.2M LiPF6 EC/EMC (3/7) during constant-voltage-constant-current (CCCV) cycling between 3.0 and 4.3 V at 40°C with a current corresponding to C/3 (cut-off current is C/20). Figures 1d – 1f show voltage versus time (d), gas production (e) and impedance change (f) during storage testing (500 hours) at 4.4 V for NMC532/graphite pouch cells with or without LiPO2F2 in 1.2M LiPF6 EC/DMC (3/7) at 60°C. In Figure 1f, the solid lines represent the results before storage and the dashed lines represent the results after storage. Figure 1
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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 | 0.000 |
| 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".