Interfacial Impedance Growth in Si-Alloy/Graphite Blended Electrodes
Bibliographic record
Abstract
Active material blended electrodes are comprised of physical mixtures of two or more lithium insertion compounds. Blended electrodes can have superior balanced performance compared to electrodes with an individual active compound. 1 For instance, Si and Si-based materials have been successfully blended into graphite electrodes in lithium-ion batteries. 2,3 Si-alloy/graphite blended electrodes result in higher cell energy density than graphite electrodes and pure Si-alloy electrodes and also have higher capacity retention than pure Si-alloy electrodes. 3 Some properties of active material blended electrodes are difficult to predict simply from the individual active materials, such as cell lifetime. 4 Electrochemical impedance spectroscopy (EIS) provides diagnostic information concerning the state of health of electrodes and properties of the solid-electrolyte interphase (SEI). 5 The electrode/electrolyte interfacial impedance growth of Si-alloy/graphite electrodes will be discussed here. Figure 1 (a-c) shows measured Nyquist plots of graphite, Si-alloy, and graphite/Si-alloy blended electrodes at different cycles. The interfacial resistance (R ir ) is highest for the graphite and Si-alloy electrodes and is lowest for the graphite/Si blended alloy electrode. Changes in R ir for these electrodes are not monotonic and do not at first seem related. The trends in R ir as a function of cycle number for these electrodes are summarized in Figure 1 (d), where the R ir data were normalized with respect to the first cycle. After normalization relationships between the coatings appear. For all three electrodes, R ir increases from the 1 st cycle to the 5 th cycle and then decreases from cycle 5 to 10. After 10 cycles, R ir increases for graphite electrodes, while Si-alloy and the blended electrodes have a constant R ir . The relative R ir values of the graphite/Si-alloy blended electrodes have very similar behavior to the pure Si-alloy electrode. Therefore, it appears that the Si-alloy component is dominant with regard to the behavior of R ir . To verify this, the relative R ir at the 20th cycle of electrodes with various ratios of Si-alloy/graphite blended electrodes are shown in Figure 2 . All blended electrodes have relative R ir values that are different from pure graphite, but have similar relative R ir values to pure Si-alloy electrodes, regardless of the graphite content. In this presentation, an explanation of this behavior in the interfacial resistance of graphite/alloy blended electrodes will be proposed. Reference S. B. Chikkannanavar, D. M. Bernardi, and L. Liu, J. Power Sources , 248 , 91–100 (2014). R. Petibon et al., J. Electrochem. Soc. , 163 , A1146–A1156 (2016). V. L. Chevrier et al., J. Electrochem. Soc. , 161 , A783–A791 (2014). H. Kitao, T. Fujihara, K. Takeda, N. Nakanishi, and T. Nohma, Electrochem. Solid-State Lett. , 8 , A87 (2005). M. Galeotti, L. Cinà, C. Giammanco, S. Cordiner, and A. Di Carlo, Energy , 89 , 678–686 (2015). Figure 1 Nyquist plots for (a) graphite, (b) Si-alloy, and (c) Si-alloy/graphite (60:28 wt/wt) blended electrodes measured at different cycles. (d) the relative interfaical resistance vs. cycle number of these three electrodes. Relative interfaical resistance values were measured as the diameter of the semicircles in the Nyquist plots, normalized on the basis of first cycle interfacial resistance. The error bars were calculated as the range of two samples. The cells were cycled at 30.0 ± 0.1 ºC and EIS spectra were measured at 10 ºC. Figure 2 The relative interfaical resistances of graphite/Si-alloy blended electrodes with various compositions, measured at 20 th cycle. The error bars were calculated as the range of two samples.The cells were cycled at 30.0 ± 0.1 ºC and EIS spectra were measured at 10 ºC. Figure 1
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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".