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Application Note
Imaging the 4D Microstructure Evolutionof a Commercial 18650 Li-ion BatteryZEISS Xradia 520 Versa
Application Note
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Imaging the 4D Microstructure Evolutionof a Commercial 18650 Li-ion BatteryZEISS Xradia 520 Versa
Author: Jeff Gelb, Senior Applications Engineer ZEISS Microscopy, CA, USA
Date: May 2017
Lithium-ion batteries are of increasing importance in consumer technologies. In parallel with understanding the
performance characteristics throughout a battery’s life, it is equally important to understand when, why, and
how the batteries ultimately fail. Recent research has pointed toward microscopy as a beneficial tool for study-
ing battery microstructures to understand what – if any – aspects of the microstructure lead to certain perfor-
mance or failure characteristics. In order to better develop an image-based microstructure investigative work-
flow, this study utilized non-destructive X-ray microscopy (XRM) to perform a 4D imaging experiment over a
battery’s lifetime. A fresh battery was studied intact, then subjected to aging until failure and imaged again.
The results of electrochemically aged batteries were compared to those of temporally aged batteries, which
showed a systematic microstructural change uniquely in response to the electrochemical aging routine.
Introduction
Energy storage solutions are ubiquitous in the modern
world. From portable electronic devices to electric vehicles
and stationary power supplies, the demand for energy stor-
age devices is expected to increase for many years to come.
Many manufacturers are now using lithium-ion batteries to
satisfy consumer requirements, with technological
advancements being made at a rapid pace [1]. In spite
of this, the performance and degradation mechanisms
of Li-ion batteries remain sparsely understood [2].
Creating a successful battery product relies on working
within a few key constraints. The batteries should be
powerful enough to serve the intended applications,
safe to operate, and reliable over their expected lifetimes.
These high-level challenges, however, may have causes root-
ed in microstructure, as the particle/pore interactions may
influence the capacity and discharge characteristics [3,4].
In addition, cell safety engineering has been shown to
begin with understanding the real-time mechanisms
of failure [5] and cell reliabilities are difficult, if not
impossible, to predict using conventional means [6].
Recent work has identified X-ray microscopy (XRM) as a
viable solution for visualizing the interior microstructures
of Li-ion batteries [7]. X-ray imaging has the unique
advantage of being entirely non-destructive, which allows
battery interiors to be revealed in 3D without sectioning or
opening the packaging of the specimen [8]. This technique
has shown a unique versatility for characterizing battery
specimens, including cathode [9], anode [10], and separator [11],
as well as offering the advantage of probing evolutionary
characteristics [12,13] and generating microstructural
models for analysis via computer simulation [14].
In this study, an ensemble of commercial Li-ion batteries
were studied intact using ZEISS Xradia 520 Versa. Using the
non-destructive power of X-rays, coupled with the high-
resolution and flexibility of Xradia 520 Versa, the same re-
gions of the same specimens were imaged before and after
aging to failure, revealing microstructural changes as a func-
tion of battery operation. The results were placed alongside
similar results on unaged batteries, to establish a control
group for comparison. This 4D study points to valuable infor-
mation provided by XRM, particularly with respect to how
the structure of a battery changes after operation. These
Application Note
3
5 mm
Current – collecting tab
Active materials+ current collectors
X-ray source
Specimen
X-ray detector
Metalhousing
Cathode
+ Currentcollector (Al)
– Currentcollector (Cu)
Anode + Separator
Densecentral ring
5 mm
3 mm 100 µm
results further reinforce the power of image-based charac-
terization for understanding degradation mechanisms within
a battery and open the door to future studies where specific
battery systems and/or battery aging characteristics may be
of interest.
Methods & Results
The specimens used for this investigation were commercially-
sourced 18650 Li-ion batteries from a reputable manufactur-
er. All investigations were performed without opening – or
otherwise disturbing – the packaging, i.e., non-destructively
imaged (Figure 1).
3D Imaging Protocols
Initial inspection with 3D X-ray microscopy was performed
with 22 µm voxel size in order to capture the entire
diameter of the battery (Figure 2). Subsequent stitching of
several fields of view enabled the battery to be captured in
its entirety using the XRM technique, with a total acquisition
time of 5 hours.
The initial survey enabled identification of bulk components,
such as the central pin, the current-collecting tab, and the
different active layers within the spiral winding. One key
architectural feature of the Xradia Versa family, is the ability
to non-destructively zoom into a specific region of interest
(ROI) by changing the objective lens to provide additional
optical magnification. Applying this “scout and zoom”
approach to one region with higher resolution, (Figure 3)
enabled the individual layers to be identified, including the
cathode, anode, and current collectors.
Figure 1 Battery specimen installed in ZEISS Xradia 520 Versa, for initial inspection.
Figure 2 The entire 18650 Li-ion battery was imaged using ZEISS Xradia 520 Versa with 22 µm voxel size and visualized in ORS Dragonfly Pro. This ren-dering shows a virtual cutaway of the full 3D dataset, revealing the interior structure. The results showed the overall assembly of the battery and the various layers within the jelly-roll.
Figure 3 ZEISS Xradia 520 Versa was used with 1.8 µm voxel size to optically enlarge a smaller section within the battery, allowing a more detailed inspection of the cell construction and identification of the different layers. These images represent virtual cross sections through the reconstructed 3D datasets.
Application Note
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1 mm
3.0
2.5
2.0
1.5
1.0
0.5
0 10 20 30 40 50
Sample 1Sample 2Sample 3
Cycle Number
Cap
acit
y (A
h)
A region in the center of the package was selected for non-
destructive, high-resolution investigation with 1.8 µm voxel
size. The results (Figure 4) showed the different layers of the
structure and no obvious defects were noted.
4D X-Ray Microscopy
Once the 3D imaging protocols had been established for
the specimen’s geometry, the study was extended to a 4D
investigation of the microstructure evolution in response
to aging. Six batteries were studied in total, within the con-
text of the present investigation. Three of those batteries
were imaged as received, cycled until failure at 1.5 oC, and
then imaged again. The other three batteries were imaged
as received, set next to the cycling apparatus (but not cy-
cled), and then imaged again in sequence with the other
three batteries. Thus, the study was divided into two groups:
an experimental group and a control, respectively. The
capacity vs. cycle number was logged for each battery
in the experimental group, which consistently exhibited
capacity fade from 3.2 V to 2.5 V (Figure 5).
Each battery exhibited a unique aging behavior, as may
be expected from more exhaustive studies documented
in the literature [6], but the aging routines were halted
when the battery either stopped charging or faded to
2.5 V capacity, whichever came first.
Figure 4 The XRM results non-destructively showed the different layers within the battery, as visualized here using ORS Dragonfly Pro. The different layers included the Al current collector (purple), cathode (orange), anode and separator (blue), and Cu current collector (white).
Figure 5 The capacity vs. cycle number was logged for each charge cycle of the experimental group. A capacity fade from 3.2 V to 2.5 V was observed over the lifetime of each battery.
Application Note
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200 µm
300 µm
The non-destructive 3D interior tomograms were then
compared to each other, using dispersed internal inclusions/
defects that were observed within the battery as registration
points to correlate the fresh and aged results. A path was
drawn along the same curved section of the jelly-roll in
the fresh and aged datasets from which the wraps of
positive electrode foil were virtually “unrolled”, enabling
visual inspection of each planar electrode (Figure 6). The im-
ages were examined for the presence of cracks or other mi-
crostructural defects which might affect the performance of
the battery. These cracks were identified with colored arrows
(Figure 7) and data interpretation was performed based on
the presence, appearance, and/or disappearance of cracks in
the 4D datasets. Cracks were observed to systematically de-
crease in detectability for the aged specimens (i.e., the ex-
perimental group) (Figure 7). In contrast, the control group,
did not show any significant or systematic microstructural
change.
While the microstructure observations were the primary
focus of this research project, a secondary question arose
with respect to the reasons or mechanisms for cell failure.
The cells were charged and discharged without any special
considerations; however, an in situ thermal monitoring
system revealed that the batteries routinely experienced
temperatures in excess of 50 °C. To understand what –
if any – impact this might have had on the reliability of
the batteries, the top cap assembly was inspected with
low-resolution XRM. A battery from the experimental
group was compared to one from the control group,
which resulted in a 3D visualization of the current
interrupt device (CID) engagement in the experimental
group battery (Figure 8). Thus, these results suggested that
thermal overload may have been the primary mechanism for
cell failure, though further research is needed to establish
this conclusion.
Figure 6 Example virtual slice, showing the “path“ (green curve) along which the battery foils were virtually unrolled.
Figure 7 Example virtual slices from the experimental (top) and control (bottom) group datasets. The experimental group batteries systematically showed a reduction in the presence/appearance of cracks, whereas the control group did not show a significant change between its initial and final images (to be expected, since there were no significant treatments applied to the control group specimens).
Experimental Group – Fresh
Control Group – Initial
Experimental Group – Aged
Control Group – Final
Application Note
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2 mm
Summary
A 4D study has been performed on a set of commercial Li-
ion batteries in 18650 cell geometries. The batteries were
first inspected in their entirety with low-resolution 3D X-ray
microscopy, to survey for bulk defects and to identify an ROI
for higher-resolution investigation. Without disturbing the
battery, a smaller region from each specimen was then opti-
cally enlarged using the non-destructive nature of X-rays
along with the uniquely high-resolution capabilities of ZEISS
Xradia 520 Versa. This multi-scale imaging approach was
then repeated after each battery had been cycled to failure,
and the results aligned to their corresponding “fresh” states.
Subsequent failure analysis scans focused on the current in-
terrupt device, to investigate the mechanism for cell failure.
The XRM results indicated that microstructural changes re-
sulted after aging in a systematic fashion, and that thermal
overload did, indeed, lead to the engagement of a current
interrupt device. This study represents an important path to-
ward understanding how batteries change with operation,
to elucidate the relationship between microstructure,
performance, and failure modes.
Acknowledgements
The author wishes to thank Dr. Paul Shearing and Prof. Dan
Brett at University College London, as well as, Dr. Donal
Finegan at National Renewable Energy Laboratory, for their
help with battery cycling and data interpretation. Funding
from ZEISS and research guidance from Dr. Melanie McNeil
and Dr. Craig England at San Jose State University is also
gratefully acknowledged.
Figure 8 Examining the top cap of (top) one control group battery and comparing it to (bottom) an experimental group battery, a microstructural difference was observed that corresponds to engagement of the CID, shown with an arrow on the figure. This indicated that thermal overload may have been a fundamental cause for early cell failure.
Application Note
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References
[1] J.M. Tarascon and M. Armand, “Issues and challenges facing rechargeable lithium batteries,” Nature. (2001).
[2] P.R. Shearing, D.S. Eastwood, R.S. Bradley, J. Gelb, S. Cooper, F. Tariq, et al., “Exploring electrochemical devices using X-ray microscopy:
3D micro-structure of batteries and fuel cells,” Microscopy and Analysis. 1–4 (2013).
[3] D. Kehrwald, P.R. Shearing, N.P. Brandon, P.K. Sinha and S.J. Harris, “Local Tortuosity Inhomogeneities in a Lithium Battery Composite
Electrode,” J. Electrochem. Soc. 158 A1393–7 (2011).
[4] M. Ebner, D.-W. Chung, R.E. Garcia and V. Wood, “Tortuosity Anisotropy in Lithium-Ion Battery Electrodes,” 4 n/a–n/a (2013).
[5] D.P. Finegan, M. Scheel, J.B. Robinson, B. Tjaden, M. Di Michiel, G. Hinds, et al., “Investigating lithium-ion battery materials during over
charge-induced thermal runaway: an operando and multi-scale X-ray CT study,” Phys Chem Chem Phys. (2016).
[6] S.J. Harris, D.J. Harris and C. Li, “Failure statistics for commercial lithium ion batteries: A study of 24 pouch cells,” Journal of Power
Sources. 342 589–597 (2017).
[7] 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,” Electrochemistry Communications. 12 374–377 (2010).
[8] A.P. Merkle and J. Gelb, “The Ascent of 3D X-ray Microscopy in the Laboratory,” Micros. Today. 21 10–15 (2013).
[9] C. Weisenberger, A. Kopp, T. Bernthaler, V. Knoblauch, G. Schneider, H. Stegmann, et al., “Multi-scale characterization of a lithium ion
battery cathode material by correlative X-ray and FIB-SEM microscopy,” Microscopy and Analysis. 17–19 (2015).
[10] F. Tariq, V. Yufit, M. Kishimoto, P.R. Shearing, S. Menkin, D. Golodnitsky, et al., “Three-dimensional high resolution X-ray imaging and
quantification of lithium ion battery mesocarbon microbead anodes,” Journal of Power Sources. 248 1014–1020 (2014).
[11] D.P. Finegan, S.J. Cooper, B. Tjaden, O.O. Taiwo, J. Gelb, G. Hinds, et al., “Characterising the structural properties of polymer separators
for lithium-ion batteries in 3D using phase contrast X-ray microscopy,” Journal of Power Sources. 333 184–192 (2016).
[12] J. Nelson, S. Misra, Y. Yang, A. Jackson, Y. Liu, H. Wang, et al., “In Operando X-ray Diffraction and Transmission X-ray Microscopy of
Lithium Sulfur Batteries,” J. Am. Chem. Soc. 134 6337–6343 (2012).
[13] Y.-C.K. Chen-Wiegart, P. Shearing, Q. Yuan, A. Tkachuk and J. Wang, “3D morphological evolution of Li-ion battery negative electrode
LiVO2 during oxidation using X-ray nano-tomography,” Electrochemistry Communications. 21 58–61 (2012).
[14] B. Yan, C. Lim, L. Yin and L. Zhu, “Simulation of heat generation in a reconstructed LiCoO2 cathode during galvanostatic discharge,”
zElectrochimica Acta. 100 171–179 (2013).
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