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Characterization of porous structure of graphite electrode with different packing densities
Available online at www.sciencedirect.com
ScienceDirect Materials Today: Proceedings 18 (2019) 487–493
www.materialstoday.com/proceedings
AEM 2018
Characterization of porous structure of graphite electrode with different packing densities Assiya Yermukhambetovaa, Zhazira Berkinovab, Boris Golmana* a
School of Engineering, Nazarbayev Unibersity, Kabanbay batyr av. 53, 010000, Astana, Kazakhstan b National Laboratory Astana, Kabanbay batyr av. 53, 010000, Astana, Kazakhstan
Abstract Rechargeable lithium (Li)-ion batteries technology is found in numerous applications and is the leading contender for transportation applications. In these applications, high-power performance and low cost solutions are required. The most straightforward way to increase energy density is to raise the ratio of active material over the total battery weight by making the electrode thicker or denser. However, by packing more material in thick electrodes, the effect of the porous electrode morphology on power is very large, as it gives rise to the lithium-ion diffusion limitations across the porosity of the electrode. In order to optimize the electrode microstructure the deeper understanding on the effect of the porous electrode structure on electrochemical performance is required. Therefore, in this research the influence of the negative electrode morphology on its electrochemical performance with regard to Li insertion/de-insertion is discussed and analyzed. The aim of the present study is to investigate the performance of graphite electrodes of various packing densities. © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Third International Conference on Advanced Energy Materials. Keywords: lithium batteries; porous microstructure; graphite electrode; packing density.
1. Introduction Lithium batteries play significant role in advancing energy saving technologies due to their high energy and power densities and long cycle durability [1]. The main parts of lithium battery i.e. electrodes, separator are porous due to their high surface area, allowing enhanced electrochemical Faradaic transfer rates [1-3].
* Corresponding author. Tel.:+7-7172-709132; fax: +7-.7172 706054 E-mail address: [email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Third International Conference on Advanced Energy Materials.
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Nomenclature Ap ℎ ℎ x R1 R2 R3 Q2 Q3 W
the particle area measured by image analysis software mass of electrode mass of current collector thickness of electrode the thickness of current collector particle diameter internal resistance of the tested battery passivation film and charge-discharge transfer passivation film and charge-discharge transfer constant phase element responsible for the double layer capacitance constant phase element responsible for the double layer capacitance Warburg resistance
Typically, in commercially used electrodes, structural properties, i.e. porosity, average particle size, and electrode thickness have been used to specify the characteristics to minimize the macroscopic power density limitations. However, in recent works it was shown that by engineering the electrode microstructure, significant electrochemical performance improvement can be reached [4-5]; in particular, advanced particle morphological engineering [6], particle packing and polydispersity and its impact on the local tortuosity [7] have demonstrated its importance to maximize charge capacity and device reliability. In general the porosity of the electrodes is significant factor that influence the electrochemical performance, as accessible and interconnecting pores dictate the effectiveness of Li ion intercalation /de-intercalation processes. The effect of increasing density of composite anodes with natural graphite as the active materials was studied previously by [8] using electrochemical characterization, [9]. In these works it was shown that with increasing graphite electrode density the electrochemical capacity was reduced, whereas in the increased density by applying higher pressure demonstrated increased cycling performance while particles sizes of the graphite were smaller. That was attributed to the reduced solid electrolyte interface (SEI) and better connection between particles. This study presents the characterization of graphite composite electrodes for Li+ batteries of various packing density geometric characterization by applying void size distribution approach. 1. Experimental 1.1. Materials and sample preparation Electrode slurries were prepared with a fixed ratio between graphite (Sigma Aldrich, particle sizes of>10μm), and conductive additive (Super P, Timcal) of 90:5 and poly(vinylidene difluoride) (PVdF, Sigma Aldrich) content of 5 wt%. PVdF was dissolved beforehand in N-methylpyrrolidone (NMP, Sigma Aldrich) to yield a 5 wt% solution. The binder solution was added in the respective volumes to the graphite and carbon powders. The resulting slurry was further diluted with several mLs of NMP in order to adjust the viscosity. The suspension was mixed in a planetary ball mill for 30 min at 300 rpm (ZrO2ceramic jar and ceramic balls) and then bar casted on copper foil (MTI) using a doctor blade method. By controlling the setting of doctor blade different thicknesses were coated. After drying at 60◦C in air to remove the NMP, the electrodes were compacted by two roll compactor. The different line loads were applied by varying the gap size between the rolls to achieve the thickness of 100 µm. The thickness of the electrodes and current collector was measured by a tactile dial gauge (ID-C, Mitutoyo, Japan) with a resolution of 1 µm; the mass loading was measured by weighing the samples. The coating density of electrodes in the coin cell, , was calculated based on the mass of active material (Eq. 1) with an assumption of current collector incompressibility:
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
= where is the mass of electrode; ℎ is the thickness of current collector.
489
(1)
is the mass of current collector; ℎ is the thickness of electrode;
1.2. SEM Characterization SEM examination was conducted on laminates of electrode materials in field-emission scanning electron microscope of a Carl Zeiss (Carl Zeiss AG, Germany). The size distribution of voids among particles inside the film was examined by image analysis on the SEM micrographs. To observe films cross-sections by SEM, the sample films were mounted into resin separately for each X, Y, Z surfaces as described in [5]. 1.3. Electrochemical impedance spectroscopy The electrode laminates were punched into 16 mm discs and transferred to an Ar-filled glove box. The three different packing density electrodes were assembled using standard CR2032 coin cell by sandwiching a polypropylene separator (Celgard, USA) between the graphite electrode and lithium using liquid electrolyte. The electrochemical experiments were conducted vs. a lithium counter electrode (CE) in half-cell with copper foil as a current collector. The prepared coin cells were initially cycled three times between 1 - 0.05V (vs. Li+) at 0.1C for the formation and stabilization of SEI layer. AC impedance spectra were measured using a two-electrode system with Li as the counter electrode and graphite as the working electrode, therefore Li/Li symmetric cells were constructed to exclude the Electrochemical impedance spectroscopy (EIS) of Li/Graphite cells and EIS of symmetrical cells of Li to exclude contribution of Lithium electrode were conducted separately. EIS was used to qualitatively analyze the effect of packing densities on electron transport. The frequency of AC impedance was varied from 1 MHz to 1 Hz with applied voltage amplitude of 10 mV (VMP3, Biologic). All measurements were performed at room temperature 1.4. Image Analysis The void sizes and overall voidage of the electrode films were measured as macro-structural parameters from SEM micrographs. After region-of interest extraction and applying image filters for image smoothing and noise reduction, the reconstructed image sequences were binarized by threshold segmentation which utilizes the greyscale histogram of the images to separate the solid phase from the void phases. The particle size distribution was measured using the image analysis. The area occupied by each particle was determined by image analysis software ImageJ. The particle size was defined as an equivalent area circle diameter and calculated as:
x
4 Ap
(2)
where x - the particle diameter; Ap - the particle area measured by image analysis software. The distribution of void sizes in 2 D images were measured by randomly placing void circles of various sizes all over the binary image as illustrated in Fig. 1. The number of trials was increased from 10,000 to 50,000 for every size of void circle in order to fully cover the surface of the cross section. Afterwards, the existence probability of void size of particular size was estimated as the proportion of the number of successfully arranged voids to that of the total number of trials [10]. As it is shown in Fig.1 the void circle is assumed to be arranged successfully if it does not overlap with the other one.
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Fig. 1 - Schematic visualization of the measurement procedure of void size distribution.
2. Results and Discussion The list of samples studied are summarized in the Table 1. Table 1. List of graphite electrodes An example of a column heading
Initial thickness (µm)
Coating density (g/cm3)
Sample 1
150
2.8
Sample 2
120
2.5
Sample 3
100
2.2
Fig. 2 (a-c) are SEM micrographs of the side surface layer of graphite electrode materials. The images reveal the morphology and size of the electrode particles. Most of the particles to be of similar size, distribution to be either elongated and rod-like ca. 30 µm long. Two-dimensional imaging using SEM not only provides ease of collection of image information but also a vast amount of qualitative information about particle morphology and material microstructure. The distributions of void sizes measured from the analysis of electrodes’ SEM micrographs are shown in Fig. 3. The measured void size distributions indicate that the total voidage is decreasing with increasing packing density, as could be seen from the Fig. 3, and has lower probability of void existence at zero point. Thus, we can conclude that in general, the number and size of voids are decreasing with higher packing density, as the void size distribution narrowed down respectively; and the void distribution of less packed sample is wider. As the compression progress, the volume of the particle is conserved, whereas that of the void space is reduced. This indicates a decrease in the porosity.
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
Fig.2 A grayscale image of SEM micrographs a) Sample 1; b) Sample 2; c) Sample 3.
Fig.3 Void size distribution of graphite electrodes of various packing density
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In addition EIS analysis was conducted to study the effect packing density on electron transport. All the Nyquist plots (Fig.4a) of the three different packing density electrodes show depressed semicircle in the high-to-mid frequency range. An equivalent circuit displayed in Fig. 4b was employed to analyze the data. The difference of the total surface area by the loadings was removed for the normalized R by multiplying the loading and divided by the maximum amounts (Fig. 4c). The electrical contact between the graphite particle and the carbon/binder matrix is the main reason for SEI layer change with different packing density electrodes. For the different packing density cells, the electrochemically active area is the only variable to define the exchange current densities at the same cell voltage. Both the normalized R2 and R3 show an increase with increasing packing density of the electrodes.
-Im[Z]/ Ohm/cm2
a
30
c Sample 1 Sample 2 Sample 3
20
10
0
10
20
Re[Z]/ Ohm/cm b
Q2
30 2
Q3
R1 R2
R3
W
Fig.4 a) AC impedance results of various packing density at 100 mV; b) electric-circuit model where R1 is the internal resistance of the tested battery; R2 and R3 represent the passivation film and charge-discharge transfer; Q1 and Q2 are the constant phase elements responsible for the double layer capacitance and W is the Warburg resistance related to the lithium diffusion process; c) normalized resistance per coating density of the electrodes.
3. Conclusion In this study, the methodology was developed for the quantitative characterization of the microstructure of porous materials utilizing the concept of void size distribution. Image analysis was applied to quantify the impact of precipitation induced volume change, pore morphology and confinement attributes in a Li–S cathode. The electrode microstructure was examined quantitatively by measuring the distribution of void sizes among the packed particle and by correlating it with packing density. Increased packing density can result in smaller void size and more uniform void size distribution. The EIS results show that the SEI layer resistance and the charge transfer resistance decrease with increasing packing density, thus
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the internal resistance has reduced, that might be due to the increased contact between particles and carbon/binder matrix and enhanced electrical connection of the electrode at higher packing density. In future work, the effect mass loads and operating parameters on the compaction resistance will be determined to find an optimal point of compaction (maximal density or minimal porosity), as well as the mechanical properties of electrodes to learn more about the deforming impact. Acknowledgements Funding is acknowledged by the targeted state programs BR05236524 “Innovative Materials and Systems for Energy Conversion and Storage” of the Ministry of Education and Science of the Republic of Kazakhstan for 20182020. References [1] H. Kawamoto, “Trends of R & D on Materials for High-power and Large-capacity Lithium-ion Batteries for Vehicles Applications,” Sci. Technol. Trends, vol. 106, pp. 19–33, 2010. [2] J. M. Tarascon and M. Armand, “Issues and challenges facing rechargeable lithium batteries.,” Nature, vol. 414, no. 6861, pp. 359–67, Nov. 2001. [3] D. Andre, M. Meiler, K. Steiner, C. Wimmer, T. Soczka-Guth, and D. U. Sauer, “Characterization of high-power lithium-ion batteries by electrochemical impedance spectroscopy. I. Experimental investigation,” J. Power Sources, vol. 196, no. 12, pp. 5334–5341, Jun. 2011. [4] P. R. Shearing, L. E. Howard, P. S. Jørgensen, N. P. Brandon, and S. J. Harris, “Characterization of the 3-dimensional microstructure of a graphite negative electrode from a Li-ion battery,” Electrochem. commun., vol. 12, no. 3, pp. 374–377, Mar. 2010. [5] P. R. Shearing, “Batteries: Imaging degradation,” Nat. Energy, vol. 1, no. 11, pp. 1–2, 2016. [6] D.-W. Chung, P. R. Shearing, N. P. Brandon, S. J. Harris, and R. E. Garcia, “Particle Size Polydispersity in Li-Ion Batteries,” J. Electrochem. Soc., vol. 161, no. 3, pp. A422–A430, 2014. [7] B. H. Yang, A. X. Wu, X. X. Miao, and J. Z. Liu, “3D characterization and analysis of pore structure of packed ore particle beds based on computed tomography images,” Trans. Nonferrous Met. Soc. China English Ed., 2014. [8] Shim, J., Striebel, K.A., Effect of electrode density on cycle performance and irreversible capacity loss for natural graphite anode in lithium ion batteries. J. Power Sources 119–121, 934–937, 2003. [9] K.A.Striebel, A.Sierra, J.Shim, C.-W.Wang, A.M. Sastry, The effect of compression on natural graphite anode performance and matrix conductivity. J. Power Sources 134, 241–251, 2004. [10] K. Ohzeki, K. Seino, T. Kumagai, B. Golman, and K. Shinohara, “Characterization of packing structure of tape cast with non-spherical natural graphite particles,” Carbon N. Y., 2006. [11] B. Golman, K. Seino, K. Shinohara, and K. Ohzeki, “Liquid permeation through cast tape of graphite particles based on non-uniform packing structure,” J. Power Sources, 2006.
ScienceDirect Materials Today: Proceedings 18 (2019) 487–493
www.materialstoday.com/proceedings
AEM 2018
Characterization of porous structure of graphite electrode with different packing densities Assiya Yermukhambetovaa, Zhazira Berkinovab, Boris Golmana* a
School of Engineering, Nazarbayev Unibersity, Kabanbay batyr av. 53, 010000, Astana, Kazakhstan b National Laboratory Astana, Kabanbay batyr av. 53, 010000, Astana, Kazakhstan
Abstract Rechargeable lithium (Li)-ion batteries technology is found in numerous applications and is the leading contender for transportation applications. In these applications, high-power performance and low cost solutions are required. The most straightforward way to increase energy density is to raise the ratio of active material over the total battery weight by making the electrode thicker or denser. However, by packing more material in thick electrodes, the effect of the porous electrode morphology on power is very large, as it gives rise to the lithium-ion diffusion limitations across the porosity of the electrode. In order to optimize the electrode microstructure the deeper understanding on the effect of the porous electrode structure on electrochemical performance is required. Therefore, in this research the influence of the negative electrode morphology on its electrochemical performance with regard to Li insertion/de-insertion is discussed and analyzed. The aim of the present study is to investigate the performance of graphite electrodes of various packing densities. © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Third International Conference on Advanced Energy Materials. Keywords: lithium batteries; porous microstructure; graphite electrode; packing density.
1. Introduction Lithium batteries play significant role in advancing energy saving technologies due to their high energy and power densities and long cycle durability [1]. The main parts of lithium battery i.e. electrodes, separator are porous due to their high surface area, allowing enhanced electrochemical Faradaic transfer rates [1-3].
* Corresponding author. Tel.:+7-7172-709132; fax: +7-.7172 706054 E-mail address: [email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Third International Conference on Advanced Energy Materials.
488
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
Nomenclature Ap ℎ ℎ x R1 R2 R3 Q2 Q3 W
the particle area measured by image analysis software mass of electrode mass of current collector thickness of electrode the thickness of current collector particle diameter internal resistance of the tested battery passivation film and charge-discharge transfer passivation film and charge-discharge transfer constant phase element responsible for the double layer capacitance constant phase element responsible for the double layer capacitance Warburg resistance
Typically, in commercially used electrodes, structural properties, i.e. porosity, average particle size, and electrode thickness have been used to specify the characteristics to minimize the macroscopic power density limitations. However, in recent works it was shown that by engineering the electrode microstructure, significant electrochemical performance improvement can be reached [4-5]; in particular, advanced particle morphological engineering [6], particle packing and polydispersity and its impact on the local tortuosity [7] have demonstrated its importance to maximize charge capacity and device reliability. In general the porosity of the electrodes is significant factor that influence the electrochemical performance, as accessible and interconnecting pores dictate the effectiveness of Li ion intercalation /de-intercalation processes. The effect of increasing density of composite anodes with natural graphite as the active materials was studied previously by [8] using electrochemical characterization, [9]. In these works it was shown that with increasing graphite electrode density the electrochemical capacity was reduced, whereas in the increased density by applying higher pressure demonstrated increased cycling performance while particles sizes of the graphite were smaller. That was attributed to the reduced solid electrolyte interface (SEI) and better connection between particles. This study presents the characterization of graphite composite electrodes for Li+ batteries of various packing density geometric characterization by applying void size distribution approach. 1. Experimental 1.1. Materials and sample preparation Electrode slurries were prepared with a fixed ratio between graphite (Sigma Aldrich, particle sizes of>10μm), and conductive additive (Super P, Timcal) of 90:5 and poly(vinylidene difluoride) (PVdF, Sigma Aldrich) content of 5 wt%. PVdF was dissolved beforehand in N-methylpyrrolidone (NMP, Sigma Aldrich) to yield a 5 wt% solution. The binder solution was added in the respective volumes to the graphite and carbon powders. The resulting slurry was further diluted with several mLs of NMP in order to adjust the viscosity. The suspension was mixed in a planetary ball mill for 30 min at 300 rpm (ZrO2ceramic jar and ceramic balls) and then bar casted on copper foil (MTI) using a doctor blade method. By controlling the setting of doctor blade different thicknesses were coated. After drying at 60◦C in air to remove the NMP, the electrodes were compacted by two roll compactor. The different line loads were applied by varying the gap size between the rolls to achieve the thickness of 100 µm. The thickness of the electrodes and current collector was measured by a tactile dial gauge (ID-C, Mitutoyo, Japan) with a resolution of 1 µm; the mass loading was measured by weighing the samples. The coating density of electrodes in the coin cell, , was calculated based on the mass of active material (Eq. 1) with an assumption of current collector incompressibility:
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
= where is the mass of electrode; ℎ is the thickness of current collector.
489
(1)
is the mass of current collector; ℎ is the thickness of electrode;
1.2. SEM Characterization SEM examination was conducted on laminates of electrode materials in field-emission scanning electron microscope of a Carl Zeiss (Carl Zeiss AG, Germany). The size distribution of voids among particles inside the film was examined by image analysis on the SEM micrographs. To observe films cross-sections by SEM, the sample films were mounted into resin separately for each X, Y, Z surfaces as described in [5]. 1.3. Electrochemical impedance spectroscopy The electrode laminates were punched into 16 mm discs and transferred to an Ar-filled glove box. The three different packing density electrodes were assembled using standard CR2032 coin cell by sandwiching a polypropylene separator (Celgard, USA) between the graphite electrode and lithium using liquid electrolyte. The electrochemical experiments were conducted vs. a lithium counter electrode (CE) in half-cell with copper foil as a current collector. The prepared coin cells were initially cycled three times between 1 - 0.05V (vs. Li+) at 0.1C for the formation and stabilization of SEI layer. AC impedance spectra were measured using a two-electrode system with Li as the counter electrode and graphite as the working electrode, therefore Li/Li symmetric cells were constructed to exclude the Electrochemical impedance spectroscopy (EIS) of Li/Graphite cells and EIS of symmetrical cells of Li to exclude contribution of Lithium electrode were conducted separately. EIS was used to qualitatively analyze the effect of packing densities on electron transport. The frequency of AC impedance was varied from 1 MHz to 1 Hz with applied voltage amplitude of 10 mV (VMP3, Biologic). All measurements were performed at room temperature 1.4. Image Analysis The void sizes and overall voidage of the electrode films were measured as macro-structural parameters from SEM micrographs. After region-of interest extraction and applying image filters for image smoothing and noise reduction, the reconstructed image sequences were binarized by threshold segmentation which utilizes the greyscale histogram of the images to separate the solid phase from the void phases. The particle size distribution was measured using the image analysis. The area occupied by each particle was determined by image analysis software ImageJ. The particle size was defined as an equivalent area circle diameter and calculated as:
x
4 Ap
(2)
where x - the particle diameter; Ap - the particle area measured by image analysis software. The distribution of void sizes in 2 D images were measured by randomly placing void circles of various sizes all over the binary image as illustrated in Fig. 1. The number of trials was increased from 10,000 to 50,000 for every size of void circle in order to fully cover the surface of the cross section. Afterwards, the existence probability of void size of particular size was estimated as the proportion of the number of successfully arranged voids to that of the total number of trials [10]. As it is shown in Fig.1 the void circle is assumed to be arranged successfully if it does not overlap with the other one.
490
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
Fig. 1 - Schematic visualization of the measurement procedure of void size distribution.
2. Results and Discussion The list of samples studied are summarized in the Table 1. Table 1. List of graphite electrodes An example of a column heading
Initial thickness (µm)
Coating density (g/cm3)
Sample 1
150
2.8
Sample 2
120
2.5
Sample 3
100
2.2
Fig. 2 (a-c) are SEM micrographs of the side surface layer of graphite electrode materials. The images reveal the morphology and size of the electrode particles. Most of the particles to be of similar size, distribution to be either elongated and rod-like ca. 30 µm long. Two-dimensional imaging using SEM not only provides ease of collection of image information but also a vast amount of qualitative information about particle morphology and material microstructure. The distributions of void sizes measured from the analysis of electrodes’ SEM micrographs are shown in Fig. 3. The measured void size distributions indicate that the total voidage is decreasing with increasing packing density, as could be seen from the Fig. 3, and has lower probability of void existence at zero point. Thus, we can conclude that in general, the number and size of voids are decreasing with higher packing density, as the void size distribution narrowed down respectively; and the void distribution of less packed sample is wider. As the compression progress, the volume of the particle is conserved, whereas that of the void space is reduced. This indicates a decrease in the porosity.
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
Fig.2 A grayscale image of SEM micrographs a) Sample 1; b) Sample 2; c) Sample 3.
Fig.3 Void size distribution of graphite electrodes of various packing density
491
492
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
In addition EIS analysis was conducted to study the effect packing density on electron transport. All the Nyquist plots (Fig.4a) of the three different packing density electrodes show depressed semicircle in the high-to-mid frequency range. An equivalent circuit displayed in Fig. 4b was employed to analyze the data. The difference of the total surface area by the loadings was removed for the normalized R by multiplying the loading and divided by the maximum amounts (Fig. 4c). The electrical contact between the graphite particle and the carbon/binder matrix is the main reason for SEI layer change with different packing density electrodes. For the different packing density cells, the electrochemically active area is the only variable to define the exchange current densities at the same cell voltage. Both the normalized R2 and R3 show an increase with increasing packing density of the electrodes.
-Im[Z]/ Ohm/cm2
a
30
c Sample 1 Sample 2 Sample 3
20
10
0
10
20
Re[Z]/ Ohm/cm b
Q2
30 2
Q3
R1 R2
R3
W
Fig.4 a) AC impedance results of various packing density at 100 mV; b) electric-circuit model where R1 is the internal resistance of the tested battery; R2 and R3 represent the passivation film and charge-discharge transfer; Q1 and Q2 are the constant phase elements responsible for the double layer capacitance and W is the Warburg resistance related to the lithium diffusion process; c) normalized resistance per coating density of the electrodes.
3. Conclusion In this study, the methodology was developed for the quantitative characterization of the microstructure of porous materials utilizing the concept of void size distribution. Image analysis was applied to quantify the impact of precipitation induced volume change, pore morphology and confinement attributes in a Li–S cathode. The electrode microstructure was examined quantitatively by measuring the distribution of void sizes among the packed particle and by correlating it with packing density. Increased packing density can result in smaller void size and more uniform void size distribution. The EIS results show that the SEI layer resistance and the charge transfer resistance decrease with increasing packing density, thus
A. Yermukhambetova et al. / Materials Today: Proceedings 18 (2019) 487–493
493
the internal resistance has reduced, that might be due to the increased contact between particles and carbon/binder matrix and enhanced electrical connection of the electrode at higher packing density. In future work, the effect mass loads and operating parameters on the compaction resistance will be determined to find an optimal point of compaction (maximal density or minimal porosity), as well as the mechanical properties of electrodes to learn more about the deforming impact. Acknowledgements Funding is acknowledged by the targeted state programs BR05236524 “Innovative Materials and Systems for Energy Conversion and Storage” of the Ministry of Education and Science of the Republic of Kazakhstan for 20182020. References [1] H. Kawamoto, “Trends of R & D on Materials for High-power and Large-capacity Lithium-ion Batteries for Vehicles Applications,” Sci. Technol. Trends, vol. 106, pp. 19–33, 2010. [2] J. M. Tarascon and M. Armand, “Issues and challenges facing rechargeable lithium batteries.,” Nature, vol. 414, no. 6861, pp. 359–67, Nov. 2001. [3] D. Andre, M. Meiler, K. Steiner, C. Wimmer, T. Soczka-Guth, and D. U. Sauer, “Characterization of high-power lithium-ion batteries by electrochemical impedance spectroscopy. I. Experimental investigation,” J. Power Sources, vol. 196, no. 12, pp. 5334–5341, Jun. 2011. [4] P. R. Shearing, L. E. Howard, P. S. Jørgensen, N. P. Brandon, and S. J. Harris, “Characterization of the 3-dimensional microstructure of a graphite negative electrode from a Li-ion battery,” Electrochem. commun., vol. 12, no. 3, pp. 374–377, Mar. 2010. [5] P. R. Shearing, “Batteries: Imaging degradation,” Nat. Energy, vol. 1, no. 11, pp. 1–2, 2016. [6] D.-W. Chung, P. R. Shearing, N. P. Brandon, S. J. Harris, and R. E. Garcia, “Particle Size Polydispersity in Li-Ion Batteries,” J. Electrochem. Soc., vol. 161, no. 3, pp. A422–A430, 2014. [7] B. H. Yang, A. X. Wu, X. X. Miao, and J. Z. Liu, “3D characterization and analysis of pore structure of packed ore particle beds based on computed tomography images,” Trans. Nonferrous Met. Soc. China English Ed., 2014. [8] Shim, J., Striebel, K.A., Effect of electrode density on cycle performance and irreversible capacity loss for natural graphite anode in lithium ion batteries. J. Power Sources 119–121, 934–937, 2003. [9] K.A.Striebel, A.Sierra, J.Shim, C.-W.Wang, A.M. Sastry, The effect of compression on natural graphite anode performance and matrix conductivity. J. Power Sources 134, 241–251, 2004. [10] K. Ohzeki, K. Seino, T. Kumagai, B. Golman, and K. Shinohara, “Characterization of packing structure of tape cast with non-spherical natural graphite particles,” Carbon N. Y., 2006. [11] B. Golman, K. Seino, K. Shinohara, and K. Ohzeki, “Liquid permeation through cast tape of graphite particles based on non-uniform packing structure,” J. Power Sources, 2006.