The Impact of High-Voltage Electrolyte Additives and Solvents to 4.7 V Determined Using Isothermal Microcalorimetry
Bibliographic record
Abstract
The use of electrolyte additives in lithium ion batteries can extend cycle life, increase coulombic efficiency, and reduce parasitic reactions [1]. Here, high resolution isothermal microcalorimetry [2, 3] is used to determine the impact of high-voltage electrolyte additives and solvents as a function of voltage up to 4.7 V in Li[Ni 0.4 Mn 0.4 Co 0.2 ]O 2 (NMC442)/graphite pouch cells. Transitioning to increasingly higher upper cutoff voltages has proved difficult as many additives and solvents are unstable at such high potentials and the parasitic degradation of these components result in severely decreased lifetimes. The voltage-dependent impact of electrolyte additives, additive blends, and solvents that have shown to result in high coulombic efficiencies, reduced electrolyte oxidation, and other parasitic reactions, will be explored. Such components include additives such as vinylene carbonate (VC), methylene methanedisulfonate, ethylene sulfate, trimethylene sulfate, and others, as well as a variety of fluorinated solvents. By comparing the heat flow of cells that vary only in electrolyte composition during cycling and open circuit conditions, the effect of the additive on the parasitic heat during the entire potential range is obtained in a short, simple experiment. A TA instruments TAM III isothermal calorimeter equipped with twelve microcalorimeters was used for these measurements. The accuracy of the microcalorimeter used (< ±1 mW) allows for a highly sensitive differentiation between cells. Figure 1 shows the heat flow versus voltage for four machine-made 260 mAh NMC442/graphite pouch cells cycling at 10 mA (C/26) at 40 o C with different additive blends. At this current, the contributions of entropy and polarization to the total heat flow are nearly identical between cells, such that any differences in measured heat are attributable to differences in parasitic heat. Figure 1 shows exceptional differences in the heat flow between the first charge (left) and subsequent charges (the fourth charge is shown as an example, right). The cells which produce the most heat during the first charge to 4.7 V have the smallest heat flow at the same potential for subsequent cycles. This is attributed to passivation-type reactions which, while initially producing vast amounts of heat, result in a reduction of parasitic reactions over the remainder of the cell life. Figure 1 also shows that the electrolyte blends with sulfur-containing additives reduce parasitic reactions compared to 2% VC-containing cells above 4.4 V, and continue to reduce these reactions with increasing state of charge. Similar results will be presented for a variety of high-voltage additives and solvents. While these electrolyte additives and solvents can reduce the heat due to parasitic reactions, the overall parasitic heat is still substantial at high potentials, as seen in Figure 1 by the dramatically increasing heat flow above 4.4 V. The results presented here clearly show the impact of high-voltage electrolyte additives and solvents and directly determine their optimal potential ranges to minimize parasitic reactions and therefore extend cell lifetimes. References [1] J.C. Burns, et al., J. Electrochem. Soc. , 160 , A1451 (2013) [2] L. J. Krause, et al., J. Electrochem. Soc. , 159 , A937–A943 (2012). [3] L.E. Downie, et al., ECS Electrochem. Lett. , 2 , A106 (2013).
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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 | 0.001 |
| 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) | 0.000 | 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".