![Simulation results from Xie et al. [47] (a) simulated Young's modulus of molecular models under different environments, and distinct details in blended models: (b) deformed cellulose amorphous model in electrolyte solvents and (c) generated hydrogen bonds between cellulose and lignin molecules.](https://www.researchgate.net/profile/Anthony-Chun-Yin-Yuen-2/publication/348579919/figure/fig1/AS:982433163931651@1611241727677/Simulation-results-from-Xie-et-al-47-a-simulated-Youngs-modulus-of-molecular-models_Q320.jpg)
![Representative images of the molecular assembly from Dhakane et al. [48]. (a) Molecular structure for simulation of a case with a bridging molecular layer (30 APTES molecules) at the LiCoO 2 -polyethylene interface. Hot reservoir (red rectangle on the left) and cold reservoir (blue rectangle on the right) maintained at 350 K and 250 K respectively are shown. (b) Schematics of the cathode-APTES interface for simulations with 10, 20, and 30 molecules.](https://www.researchgate.net/profile/Anthony-Chun-Yin-Yuen-2/publication/348579919/figure/fig2/AS:982433168125959@1611241728923/Representative-images-of-the-molecular-assembly-from-Dhakane-et-al-48-a-Molecular_Q320.jpg)
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molecules
Review
A Review on Lithium-Ion Battery Separators towards Enhanced
Safety Performances and Modelling Approaches
Ao Li 1, Anthony Chun Yin Yuen 1, * , Wei Wang 1, Ivan Miguel De Cachinho Cordeiro 1, Cheng Wang 1,
Timothy Bo Yuan Chen 1, Jin Zhang 1, Qing Nian Chan 1and Guan Heng Yeoh 1,2
Citation: Li, A.; Yuen, A.C.Y.; Wang,
W.; De Cachinho Cordeiro, I.M.;
Wang, C.; Chen, T.B.Y.; Zhang, J.;
Chan, Q.N.; Yeoh, G.H. A Review on
Lithium-Ion Battery Separators
towards EnhancedSafety Performances
and Modelling Approaches. Molecules
2021,26, 478. https://doi.org/10.3390/
molecules26020478
Academic Editor: Gaëlle Fontaine
Received: 14 December 2020
Accepted: 14 January 2021
Published: 18 January 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
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iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1School of Mechanical and Manufacturing Engineering, University of New South Wales,
Sydney, NSW 2052, Australia; ao.li@unsw.edu.au (A.L.); wei.wang15@unsw.edu.au (W.W.);
i.decachinhocordeiro@unsw.edu.au (I.M.D.C.C.); c.wang@unsw.edu.au (C.W.);
timothy.chen@unsw.edu.au (T.B.Y.C.); jin.zhang6@unsw.edu.au (J.Z.); qing.chan@unsw.edu.au (Q.N.C.);
g.yeoh@unsw.edu.au (G.H.Y.)
2Australian Nuclear Science and Technology Organization (ANSTO), Locked Bag 2001, Kirrawee DC,
NSW 2232, Australia
*Correspondence: c.y.yuen@unsw.edu.au
Abstract:
In recent years, the applications of lithium-ion batteries have emerged promptly owing
to its widespread use in portable electronics and electric vehicles. Nevertheless, the safety of the
battery systems has always been a global concern for the end-users. The separator is an indispensable
part of lithium-ion batteries since it functions as a physical barrier for the electrode as well as an
electrolyte reservoir for ionic transport. The properties of separators have direct influences on the
performance of lithium-ion batteries, therefore the separators play an important role in the battery
safety issue. With the rapid developments of applied materials, there have been extensive efforts
to utilize these new materials as battery separators with enhanced electrical, fire, and explosion
prevention performances. In this review, we aim to deliver an overview of recent advancements
in numerical models on battery separators. Moreover, we summarize the physical properties of
separators and benchmark selective key performance indicators. A broad picture of recent simulation
studies on separators is given and a brief outlook for the future directions is also proposed.
Keywords: lithium-ion battery; separator; numerical modelling; battery safety
1. Introduction
Pioneered by Yoshino in 1985 [
1
,
2
], lithium-ion (Li-ion) batteries have been commer-
cialized and used ever since in the industry as an alternative source of energy. It is usually
applied as an energy storage reservoir for renewable energies and commonly used in
portable electronics and electric vehicles. Nonetheless, a Li-ion battery is less thermally
stable in comparison with other battery systems. This has caused a significant amount
of battery fires in recent years, which occurred in mobile phones, electric vehicles, and
airplanes [
3
–
6
]. The Li-ion battery separator is one of the crucial factors affecting fire safety
performance since it directly contributes to the thermal stability of the entire battery system.
As one of the most important components in Li-ion batteries, the separator is placed
between the anode and cathode [
7
]. The schematic diagram about a common separator
applied in Li-ion batteries is shown in Figure 1, with the function of preventing physical
contact between electrodes while serving as the electrolyte reservoir to enable ionic trans-
port. There are no direct cell reactions in the separator, but the structure and properties
of the separator play an essential role in determining the battery performance, including
cycle life, safety, energy density, and power density, through influencing the cell kinetics [
8
].
A wide variety of factors should be considered while selecting appropriate separators
for use in Li-ion batteries. Table 1summarizes the general requirements that should be
considered for Li-ion battery separators, and the detailed discussion has been provided
Molecules 2021,26, 478. https://doi.org/10.3390/molecules26020478 https://www.mdpi.com/journal/molecules
Molecules 2021,26, 478 2 of 15
by previous studies, such as development of membrane separators by Lee et al. [
8
], pro-
duction process of separators by Deimede et al. [
9
], characterization and performance
evaluation of separators by Lagadec et al. [
10
], and so on. These early reviews focused
on the characterization methods for separator properties and manufacturing techniques
for separators through experimental methods. Moreover, the application of the separator
increases electrical resistance and takes up limited space inside the battery, which has a
negative impact on battery performance. Therefore, reasonable utilization of a separator is
of vital importance to improving the battery performance, which includes energy density,
cycle life, power density, and fire safety.
Molecules 2021, 26, x FOR PEER REVIEW 2 of 16
separators for use in Li-ion batteries. Table 1 summarizes the general requirements that
should be considered for Li-ion battery separators, and the detailed discussion has been
provided by previous studies, such as development of membrane separators by Lee et al.
[8], production process of separators by Deimede et al. [9], characterization and perfor-
mance evaluation of separators by Lagadec et al. [10], and so on. These early reviews fo-
cused on the characterization methods for separator properties and manufacturing tech-
niques for separators through experimental methods. Moreover, the application of the
separator increases electrical resistance and takes up limited space inside the battery,
which has a negative impact on battery performance. Therefore, reasonable utilization of
a separator is of vital importance to improving the battery performance, which includes
energy density, cycle life, power density, and fire safety.
Table 1. General requirements for separators used in Li-ion batteries [8].
Parameter Requirement
Chemical and electrochemical stabilities Stable for a long period of time
Wettability Wet out quickly and completely
Mechanical property >1000 kg·cm−1 (98.06 MPa)
Thickness 20–25 µm
Pore size <1 µm
Porosity 40–60%
Permeability (Gurley) <0.025 s·µm−1
Dimensional stability No curl up and lay flat
Thermal stability <5% shrinkage after 60 min at 90 °C
Shutdown Effectively shut down the battery at
elevated temperatures
Figure 1. Schematic image of a separator in cylindrical Li-ion battery cell and a zoomed-in cross-
section of the layered structure.
Figure 1.
Schematic image of a separator in cylindrical Li-ion battery cell and a zoomed-in cross-
section of the layered structure.
Table 1. General requirements for separators used in Li-ion batteries [8].
Parameter Requirement
Chemical and electrochemical stabilities Stable for a long period of time
Wettability Wet out quickly and completely
Mechanical property >1000 kg·cm−1(98.06 MPa)
Thickness 20–25 µm
Pore size <1 µm
Porosity 40–60%
Permeability (Gurley) <0.025 s·µm−1
Dimensional stability No curl up and lay flat
Thermal stability <5% shrinkage after 60 min at 90 ◦C
Shutdown Effectively shut down the battery at
elevated temperatures
In view of battery safety, the separator must be able to act as a blocking interface be-
tween the electrodes when an internal short circuit occurs, so that the thermal runaway
is avoided [
11
]. Chemical and thermal stability, as well as shutdown function at the set
temperature, should be the requirement for the separator. Considering the material price,
current technology, and the trade-off relationship of the above properties, a comprehensive
evaluation of the separator properties is required for separator selection. In order to improve
the performance of separators and enhance the safety of Li-ion batteries, researchers have thus
performed a lot of research work in recent years [
12
–
14
]. Furthermore, numerical modelling
on the design and test of separators for improving battery abuse tolerance and performance
Molecules 2021,26, 478 3 of 15
is deemed a practical compromise in optimizing the separator in future battery systems.
Compared with the experimental investigation on separators, numerical modelling is treated
as an efficient and economic tool for the study of separators. Both the separator material
properties and the various performances of the separator are able to be simulated and pre-
dicted by numerical models. In this paper, the current numerical studies of separators will be
reviewed in terms of mathematical models, finite element analysis (FEA), and computational
fluid dynamic (CFD) models, and molecular dynamic (MD) models. From the perspective of
numerical study, we describe the separator performance based on its influence on the battery
performance, including microstructure of separators, stress analysis for the separators, ther-
mal and ion transport of separators, as well as degradation process of separators. Moreover,
the relationship between separator properties and battery safety will be discussed based on
the separator shutdown and separator breakdown. Based on this review, future research
directions on the Li-ion battery separators will be discussed in detail.
2. Numerical Study of Separators
Separators must be chemically and electrochemically stable to the electrolyte and
electrode materials in Li-ion batteries since the separator itself does not participate in any
cell reactions. As a critical component inside Li-ion batteries under strongly oxidizing and
reducing conditions when the battery is fully discharged and charged, separators should
also be mechanically strong to withstand the high tension during the battery assembly
operation. In terms of the properties and performances of the separator, related numer-
ical studies of battery fire safety can be divided into separator shutdown and separator
breakdown, which are reviewed in this section.
2.1. Numerical Methods
With the development of computer science, numerical simulations are gradually
applied in many assessments of separator safety designs. Compared to standard exper-
iments, numerical simulation validates experiment results with less physical resources
and also reveals in-depth key performance parameters including temperature, pressure,
electrochemical properties. Furthermore, we are able to visualize the battery system in-
ternally to effectively diagnose the problems that may lead to potential battery failures.
The development of numerical battery models has facilitated better understanding of the
underlying principles of the battery circuit and its associated influence towards the ambient
environment. Figure 2summarizes the reviewed numerical studies in this paper.
Molecules 2021, 26, x FOR PEER REVIEW 4 of 16
Figure 2. Summary of the reviewed papers for separators categorized by numerical methods and performances.
Mathematical models have been widely used in the battery property investigation
and battery working procedure [15–17]. The development of a detailed mathematical
model is important to design and optimize the batteries. Simulation results provide intu-
itive data on the performance of the battery. A suitable mathematical model can describe
a few parameters which are not known experimentally and regulate parameter adjust-
ment. For example, the direct experimental data for tortuosity or liquid-phase transport
resistance is lacking, which can be simulated from mathematical models [18,19].
Finite Element Analysis (FEA) theories and methods originate from the need to solve
complex elasticity and structural analysis problems in engineering [20]. This method has
been developed and applied in studying the mechanical properties, and many FEA pack-
ages such as ABAQUS, LS-DYNA, RADIOSS were used to model the material structure.
Computation fluid dynamics (CFD) is a practical tool to study different thermal fluid dy-
namic parameters and simulate multiple physics fields [21–23], and CFD makes it possible
to use the equations governing a fluid motion for an extensive range of complex situations,
providing both insight and quantitative predictions. CFD simulation can provide detailed
information about the electrical and thermal field inside the battery that is often difficult
to be assessed by experimental means. Model-based investigations promote theoretical
understanding of battery physics beyond what is possible from experiments only.
Molecular dynamics (MD) simulations have been applied to understand the proper-
ties at the molecular-level and design chemical structures with high performance. There
are variations of MD simulation models utilizing different chemical force-field based on
their characterizing phenomena, for instance, pyrolysis [24], nucleation [25], material ther-
mal/electrical properties [26], and so on. Moreover, MD simulations are used to predict
the chemical interactions between different materials and understand numerous mem-
brane properties. Table 2 summarized the numerical studies associated with separators,
which are applied with numerical simulations, including mathematical models, FEA and
CFD simulations, MD simulations, and so on.
Table 2. The summary of the reviewed numerical studies for separators with model parameters.
Numerical
Method Model Parameters Year Ref
Mathematical
model
Bruggeman exponent α 2003 [27]
Tortuosity 2009 [19]
Distance map, spatial distribution map, and histogram 2014 [28]
Capacity loss, temperatures, and SOC 2017 [29]
Figure 2. Summary of the reviewed papers for separators categorized by numerical methods and performances.
Mathematical models have been widely used in the battery property investigation and
battery working procedure [
15
–
17
]. The development of a detailed mathematical model
Molecules 2021,26, 478 4 of 15
is important to design and optimize the batteries. Simulation results provide intuitive
data on the performance of the battery. A suitable mathematical model can describe a few
parameters which are not known experimentally and regulate parameter adjustment. For
example, the direct experimental data for tortuosity or liquid-phase transport resistance is
lacking, which can be simulated from mathematical models [18,19].
Finite Element Analysis (FEA) theories and methods originate from the need to solve
complex elasticity and structural analysis problems in engineering [
20
]. This method
has been developed and applied in studying the mechanical properties, and many FEA
packages such as ABAQUS, LS-DYNA, RADIOSS were used to model the material structure.
Computation fluid dynamics (CFD) is a practical tool to study different thermal fluid
dynamic parameters and simulate multiple physics fields [
21
–
23
], and CFD makes it possible
to use the equations governing a fluid motion for an extensive range of complex situations,
providing both insight and quantitative predictions. CFD simulation can provide detailed
information about the electrical and thermal field inside the battery that is often difficult
to be assessed by experimental means. Model-based investigations promote theoretical
understanding of battery physics beyond what is possible from experiments only.
Molecular dynamics (MD) simulations have been applied to understand the properties
at the molecular-level and design chemical structures with high performance. There
are variations of MD simulation models utilizing different chemical force-field based on
their characterizing phenomena, for instance, pyrolysis [
24
], nucleation [
25
], material
thermal/electrical properties [
26
], and so on. Moreover, MD simulations are used to predict
the chemical interactions between different materials and understand numerous membrane
properties. Table 2summarized the numerical studies associated with separators, which
are applied with numerical simulations, including mathematical models, FEA and CFD
simulations, MD simulations, and so on.
Table 2. The summary of the reviewed numerical studies for separators with model parameters.
Numerical Method Model Parameters Year Ref
Mathematical model
Bruggeman exponent α2003 [27]
Tortuosity 2009 [19]
Distance map, spatial distribution map, and histogram 2014 [28]
Capacity loss, temperatures, and SOC 2017 [29]
FEA and CFD
Packing pattern, thickness variation, stress,
and viscoelastic relaxation 2010 [30]
Stress distribution, thermal effect, friction, particle radius, separator thickness 2011 [31]
Principal stresses and Von Mises stress 2014 [32]
Stress-strain curves and force-displacement curves 2016 [33]
Porosity ε, tortuosity τ,and effective
transport coefficient δ2016 [34]
Stress-strain curves, deformed shapes, and pores diameter 2017 [35]
Strain, stress, node angle, voltage drop, and C-rate 2018 [36]
Porosity, TP tortuosity, separator thickness,
and connectivity density 2018 [37]
Stress-strain curves 2019 [38]
Thickness, porosity, energy density, heat generation rate, temperature, thermal
conductivity, and heat capacity 2020 [39]
MD
Tip temperature, current density, and tip aspect ratio 2011 [40]
Li density, SEI thickness, component ratio 2011 [41]
Free energy, radial distribution functions, and proton transfer coordinate 2013 [42]
Young’s modulus and density 2014 [43]
Proton concentration (i.e., CH+) 2016 [44]
Proton conductivity and ion exchange
capacity value 2016 [45]
Temperature, density, heat flux, and thermal conductivity 2019 [46]
Young’s modulus 2020 [47]
Interfacial thermal conductance 2020 [48]
Molecules 2021,26, 478 5 of 15
2.2. Separator Shutdown
As shown in Figure 1, the location of the separator decides its primary function is to
separate the anode and the cathode. The mechanical properties of separators are therefore
very important for maintaining separation and Li-ion battery safety. Polyethylene (PE),
polypropylene (PP), and PE/PP separators with pore sizes in the range of micrometres have
been commercialized and widely used in Li-ion battery technology [
49
]. These microporous
separators play a protective role during cell abuse. For example, if the temperature of the
battery cell rises abnormally, separator shutdown occurs, which indicates that separators
can provide a margin of safety to the device instead of leading to thermal runaway caused
by the direct contact of electrodes. Numerical simulations can be carried out to study the
microstructure and mechanical properties of the separator and to predict battery safety.
2.2.1. Porous Structure
Microporous membranes are normally characterized by pore sizes in the micrometre scale
and are mainly manufactured based on polyolefin materials, such as PE, PP, and their blends
such as PE–PP, as they afford both excellent chemical stability and mechanical properties.
High-density polyethylene (HDPE) and ultrahigh molecular polyethylene (UHMWPE) are
also used for preparing microporous membranes [
50
]. Therefore, numerical study as a
simplified analysis has been employed to evaluate the effect of separators in practice [
16
]. In
mathematical modelling, the following empirical equation has been widely used.
Rs=ε−α·R0(1)
where R
s
is the resistance of the separator filled with liquid electrolyte, R
0
is the resistance
of the native liquid electrolyte,
ε
is the void volume fraction in a separator, and
α
is the
Bruggeman exponent. Separator morphology plays an important role in battery design
and battery safety; therefore, numerical studies can provide better justification for the
morphological parameters of separators for design and optimization.
Patel et al. [
27
] demonstrated models of porous networks to investigate the influence
of particle shape and overall porosity on the liquid phase conductivity inside electrodes
or separators used for Li-ion batteries. These models demonstrate that for batteries with
high-rate performance, spherical or slightly prolate ellipsoidal particles should be preferred.
Porous networks based on other particle morphologies however increase the tortuous path
for ionic conductivity and result in either a significant increase of the exponent
α
, or a
complete deviation from the power law.
Thorat et al. [
19
] applied a mathematical model for an empirical relationship between
porosity and the tortuosity of the porous structures. They concluded that the tortuosity-
dependent mass transport resistance in porous separators and electrodes is significantly
higher than that predicted by the often-used Bruggeman relationship. Moreover, Chen-
Wiegart et al. [
28
] proposed a distance propagation method for calculating tortuosity with
relatively low computation time from three-dimensional (3D) tomographic data.
Lagadec et al. [
34
] built an electrolyte-soaked separator model and studied the in-
fluences of the separator microstructure on the battery performance. The porosity
ε
and
tortuosity
τ
of the polyethylene separators directly influence the transport properties (the
concentration-dependent electrolyte D
l
and the concentration-dependent electrolyte
σl
,
calculated according to Nyman et al. [
51
]). The electrolyte conductivity decreased with
the separator microstructure, and the potential drop can be thereby increased across the
electrolyte-soaked separator. Based on their simulations, it is clearly illustrated that in-
creasing the electrolyte conductivity and the transference number in separator membranes
can improve the Li-ion battery performance, particularly at high current rates. Lagadec
et al. [
37
] delivered an analysis of tomographic data of commercial separators. They demon-
strated the extent to which Li-ion concentration gradients can be induced or smoothed by
the separator structure. This is linked to the pore space connectivity, i.e., a parameter that
can be determined by topological or network-based analysis of separators.
Molecules 2021,26, 478 6 of 15
2.2.2. Stress Analysis
It is well recognized by the Li-ion battery community that stress plays an essential role
in the performance of the separator. To enhance the battery separator’s performance, the
stresses upon the separator in situ must be fully understood. Young’s modulus, which is a
physical quantity parameter evaluating the anti-deformability of elastic materials subjected
to external force, is applied to evaluate the mechanical performance of separators. In view
of battery safety for Li-ion batteries, a larger elastic modulus enables the separator to sustain
internal or external pressure and local stress. In order to evaluate the intercalation and
thermal mismatch induced stresses in the separator, multi-scale multi-physics models have
been proposed and developed [
30
,
31
,
52
]. Testing the mechanical properties of a separator in
situ in a battery is one of the tasks in improving the performance of battery separators [
53
].
For an isotropic material, the mechanical stress has a constitutive relationship for the strain,
which is given as [30]:
εij =1
E(1+ν)σij −νσkkδij(2)
where
εij
is the strain component, Eis Young’s modulus,
ν
is the Poisson’s ratio of the
material, and
δij
is the Dirac delta function. Moreover, with the understanding of the
mechanical properties of separators, battery safety performance can be estimated and
optimized. Table 3summarizes the numerical stress analysis results in this section.
Table 3. Stress analysis summary for separators used in Li-ion batteries.
Materials Young’s Modulus (GPa) Poisson’s Ratio Average Strain (%) Ref.
Polyolefin
Poly(vinylidene fluoride) (PVDF)
0.2
0.05 0.35 −0.14
−0.035 [30]
A homogeneous solid medium 0.5 0.35 −0.40 [31]
PP separator Celgard 2400 0.1 - - [32]
PE microstructure
PP microstructure
1.2
1.5 0−0.40 [36]
PP
In vacuum/In DMC
Crystalline fiber: 43.4/46.5
Infinitely long chain fiber:
0.66/0.07
Finite chain fiber: 0.29/0.01
- - [43]
Cellulose/lignin
Dry/Wet
Pure cellu: 3.38/2.50
Lignin 2.5%: 3.90/3.58
Lignin 5%: 4.10/3.25
Lignin 7.5%: 4.23/2.98
Lignin 10%: 4.78/2.88
- - [47]
Xiao et al. [
30
] developed a multi-physics, multi-scale model of a lithium-ion battery
cell by using COMSOL. Their simulation results illustrate that the stress is affected by
Young’s modulus of the separator, electrode particle size, separator wrapping patterns, and
the pressure of the cell, and the local strain at the indented areas was much higher than the
nominal strain of the separator.
Shi et al. [
31
] investigated the influences of some adjustable design parameters, in-
cluding the effective friction, electrode particle radii, and thickness of the separator, on the
stresses in the separator. It is concluded that the maximum Von Mises stress increased as
increasing the thickness of the separator and the effective frictions between the separator
and its adjacent electrodes. The stress analysis showed that the maximum stress in the
separator always emerged at the area around the inner corner of the separator. In this
case, the cell voltage at 4.2 V was assumed to be fully charged. The schematic of the
structure represents the macro-scale 2D model with separator thickness of 25
µ
m and
Molecules 2021,26, 478 7 of 15
anode thickness of 45
µ
m. When the Li-ion battery was fully charged, the maximum stress
was wrapped around the edge of the anode, as shown in Figure 3. In addition, with the
same volume fractions of active materials, the particle radii had a negligible effect on the
stress in the separator.
Molecules 2021, 26, x FOR PEER REVIEW 7 of 16
Shi et al. [31] investigated the influences of some adjustable design parameters, in-
cluding the effective friction, electrode particle radii, and thickness of the separator, on
the stresses in the separator. It is concluded that the maximum Von Mises stress increased
as increasing the thickness of the separator and the effective frictions between the separa-
tor and its adjacent electrodes. The stress analysis showed that the maximum stress in the
separator always emerged at the area around the inner corner of the separator. In this case,
the cell voltage at 4.2 V was assumed to be fully charged. The schematic of the structure
represents the macro-scale 2D model with separator thickness of 25 µm and anode thick-
ness of 45 µm. When the Li-ion battery was fully charged, the maximum stress was
wrapped around the edge of the anode, as shown in Figure 3. In addition, with the same
volume fractions of active materials, the particle radii had a negligible effect on the stress
in the separator.
Figure 3. Schematic and contours of strain [m m−1] components in the separator near the corner [31].
A multi-physics model was built by Wu et al. [32] to analyze the stress in the PP
separator via COMSOL. The results showed that the effects of the intercalation and ther-
mal expansion are coupled summations and hence must be considered concurrently. The
type of the constitutive relationship of the separator affects the stress values. The calcu-
lated stresses in the separator with a viscoelastic material law were about a half of that
estimated with an elastic law.
Table 3. Stress analysis summary for separators used in Li-ion batteries.
Materials Young’s Modulus
(GPa)
Poisson’s
Ratio
Average
Strain (%) Ref.
Polyolefin
Poly(vinylidene fluo-
ride) (PVDF)
0.2
0.05 0.35 −0.14
−0.035 [30]
A homogeneous solid
medium 0.5 0.35 −0.40 [31]
PP separator Celgard
2400 0.1 - - [32]
PE microstructure
PP microstructure
1.2
1.5 0 −0.40 [36]
PP
In vacuum/In DMC
Crystalline fiber:
43.4/46.5
Infinitely long chain fi-
ber: 0.66/0.07
Finite chain fiber:
0.29/0.01
- - [43]
Figure 3. Schematic and contours of strain [m m−1] components in the separator near the corner [31].
A multi-physics model was built by Wu et al. [
32
] to analyze the stress in the PP
separator via COMSOL. The results showed that the effects of the intercalation and thermal
expansion are coupled summations and hence must be considered concurrently. The type
of the constitutive relationship of the separator affects the stress values. The calculated
stresses in the separator with a viscoelastic material law were about a half of that estimated
with an elastic law.
A finite element model of PE separator was developed in LSDYNA by Zhang et al. [
33
]
based on the uniaxial tensile and through-thickness compression test data. The model
succeeded in predicting the response of PE separator under punch tests with different sizes
of punch head, including 1 inch (25.4 mm), 1/2 inch (12.6 mm), 1/4 inch (6.35 mm), and
1/8 inch (3.175 mm), which is shown in Figure 4. The model also correctly predicted the
effect of anisotropic material on the shape and curvature of deformation in two planes
of anisotropy. Furthermore, the anisotropic mechanical behaviour of the material can
be analyzed by FEA models as well. Bulla et al. [
54
] developed a model to predict the
anisotropic response of the PE separator due to deformation and failure by combining the
novel failure criterion with Hill’s yield surface and a Swift–Voce hardening rule.
Molecules 2021, 26, x FOR PEER REVIEW 8 of 16
Cellulose/lignin
Dry/Wet
Pure cellu: 3.38/2.50
Lignin 2.5%: 3.90/3.58
Lignin 5%: 4.10/3.25
Lignin 7.5%: 4.23/2.98
Lignin 10%: 4.78/2.88
- - [47]
A finite element model of PE separator was developed in LSDYNA by Zhang et al.
[33] based on the uniaxial tensile and through-thickness compression test data. The model
succeeded in predicting the response of PE separator under punch tests with different
sizes of punch head, including 1 inch (25.4 mm), 1/2 inch (12.6 mm), 1/4 inch (6.35 mm),
and 1/8 inch (3.175 mm), which is shown in Figure 4. The model also correctly predicted
the effect of anisotropic material on the shape and curvature of deformation in two planes
of anisotropy. Furthermore, the anisotropic mechanical behaviour of the material can be
analyzed by FEA models as well. Bulla et al. [54] developed a model to predict the aniso-
tropic response of the PE separator due to deformation and failure by combining the novel
failure criterion with Hill’s yield surface and a Swift–Voce hardening rule.
Figure 4. Punch test simulation with different punch sizes [33].
An image-based microstructure representative volume element (RVE) modelling
method was applied by Xu et al. [35], which facilitates the understanding of the separa-
tors’ complex macro mechanical behaviour as a result of microstructural features. The
proposed method successfully captures the anisotropic behaviour of the separator under
tensile test and provides insights into microstructure deformation, such as the growth of
voids. In this study, the imaging processing method and finite element simulation are
successfully coupled to analyze the stress-strain relation of battery separators. Further-
more, Xu et al. [55] developed a microstructure modelling method to investigate the de-
formation patterns of the battery separator. Based on their results, the reason why the
separator film turns transparent has two folds was explained. One is the material-level
instability, and the other is the structure-level instability.
Lagadec et al. [36] characterized how the microstructural properties (including po-
rosity, tortuosity, and permeability) of the separators change as a function of compressive
strain and predicted the influence of these changes on the Li-ion transport through the
separator by mechanical simulations. They also concluded that a given compressive strain
negatively impacts the microstructure of PE separator more than that of a PP separator,
because PE has a lower Young’s modulus, smaller pore sizes, and a more isotropic struc-
ture.
Xu and Bae [38] proposed a stochastic reconstruction algorithm to generate random
but statistically equivalent 3D microstructure models for mechanical property analysis
and uncertainty quantification. The proposed modelling method provides a tool to estab-
lish the “microstructure-property” relation, which can be considered as important sepa-
rator design variables.
In addition, from the molecular level, investigations of atomic interactions provide a
deep understanding of the stress of separators in Li-ion batteries. Yan et al. [43] mapped
the separator microstructure into discrete atomistic models of bulk crystalline phases and
Figure 4. Punch test simulation with different punch sizes [33].
An image-based microstructure representative volume element (RVE) modelling
method was applied by Xu et al. [
35
], which facilitates the understanding of the separators’
complex macro mechanical behaviour as a result of microstructural features. The proposed
method successfully captures the anisotropic behaviour of the separator under tensile test
and provides insights into microstructure deformation, such as the growth of voids. In
this study, the imaging processing method and finite element simulation are successfully
coupled to analyze the stress-strain relation of battery separators. Furthermore, Xu et al. [
55
]
developed a microstructure modelling method to investigate the deformation patterns
of the battery separator. Based on their results, the reason why the separator film turns
transparent has two folds was explained. One is the material-level instability, and the other
is the structure-level instability.
Lagadec et al. [
36
] characterized how the microstructural properties (including poros-
ity, tortuosity, and permeability) of the separators change as a function of compressive
Molecules 2021,26, 478 8 of 15
strain and predicted the influence of these changes on the Li-ion transport through the
separator by mechanical simulations. They also concluded that a given compressive strain
negatively impacts the microstructure of PE separator more than that of a PP separator,
because PE has a lower Young’s modulus, smaller pore sizes, and a more isotropic structure.
Xu and Bae [
38
] proposed a stochastic reconstruction algorithm to generate random
but statistically equivalent 3D microstructure models for mechanical property analysis and
uncertainty quantification. The proposed modelling method provides a tool to establish
the “microstructure-property” relation, which can be considered as important separator
design variables.
In addition, from the molecular level, investigations of atomic interactions provide a
deep understanding of the stress of separators in Li-ion batteries. Yan et al. [
43
] mapped
the separator microstructure into discrete atomistic models of bulk crystalline phases and
oriented amorphous nanofibers at different conditions such as in vacuum, water, and
dimethyl carbonate (DMC) by using MD (See Figure 5). The mechanical responses of a
porous PP separator in different media were found, which indicates that DMC can penetrate
into the amorphous nanofiber and result in Young’s modulus reduction to one-tenth of its
original value, while a polar solvent (e.g., water) can increase Young’s modulus by slightly
squeezing the amorphous fibre due to the repulsive interaction.
Molecules 2021, 26, x FOR PEER REVIEW 9 of 16
oriented amorphous nanofibers at different conditions such as in vacuum, water, and di-
methyl carbonate (DMC) by using MD (See Figure 5). The mechanical responses of a po-
rous PP separator in different media were found, which indicates that DMC can penetrate
into the amorphous nanofiber and result in Young’s modulus reduction to one-tenth of its
original value, while a polar solvent (e.g., water) can increase Young’s modulus by slightly
squeezing the amorphous fibre due to the repulsive interaction.
Figure 5. Relaxed structure for crystalline fibre, infinitely long chain fibre and finite chain fibre in vacuum, in DMC, and
in water at zero strain [43].
Xie et al. [47] successfully applied molecular simulation to unveil that the weakening
of cellulose separator submerged in the electrolyte results from the deformed cellulose
amorphous region and the promoting effect of adding lignin. The addition of lignin gen-
erates new hydrogen bonds between the cellulose and lignin molecules and subsequently
form a larger fibrous network. The weakening phenomenon of cellulose separator im-
mersed in the electrolyte is mainly caused by the deformation of the cellulose amorphous
region, shown in Figure 6.
Figure 5.
Relaxed structure for crystalline fibre, infinitely long chain fibre and finite chain fibre in
vacuum, in DMC, and in water at zero strain [43].
Molecules 2021,26, 478 9 of 15
Xie et al. [
47
] successfully applied molecular simulation to unveil that the weakening
of cellulose separator submerged in the electrolyte results from the deformed cellulose
amorphous region and the promoting effect of adding lignin. The addition of lignin gener-
ates new hydrogen bonds between the cellulose and lignin molecules and subsequently
form a larger fibrous network. The weakening phenomenon of cellulose separator im-
mersed in the electrolyte is mainly caused by the deformation of the cellulose amorphous
region, shown in Figure 6.
Molecules 2021, 26, x FOR PEER REVIEW 10 of 16
Figure 6. Simulation results from Xie et al. [47] (a) simulated Young’s modulus of molecular mod-
els under different environments, and distinct details in blended models: (b) deformed cellulose
amorphous model in electrolyte solvents and (c) generated hydrogen bonds between cellulose and
lignin molecules.
2.3. Separator Breakdown
During the battery working progress, it is possible that due to thermal inertia the
temperature can continue to rise until the separator would melt and short the electrodes,
leading to violent reactions and heat generation [56]. This phenomenon is called separator
breakdown, which is one step of the Li-ion battery thermal runaway process. Therefore,
the thermal properties of separators have a strong influence on battery safety. Numerical
studies in this field can provide a better understanding of the separator breakdown mech-
anism and give reliable prediction results. Other related performances such as ion
transport and the solid electrolyte interphase (SEI) degradation can be modelled as well
by numerical methods.
2.3.1. Thermal Transport
As mentioned in the Introduction, the separator acts as an essential role in improving
battery safety performance. Low thermal transport in Li-ion cells and battery packs has
been widely recognized as a critical technological concern that limits the use of Li-ion
batteries [49,57,58]. Therefore, the focus for the current development of advanced Li-ion
battery separators is to enhance the safety performance of the separator and/or facilitate
the ionic flow through the separator during battery operation.
Standard MD simulation studies thermal transport and heat conduction across the
molecular interfaces at the given length-scales (~a few nms). For example, MD simulations
have been employed to model thermal transport across a variety of material pairs such as
Figure 6.
Simulation results from Xie et al. [
47
] (
a
) simulated Young’s modulus of molecular models under different
environments, and distinct details in blended models: (
b
) deformed cellulose amorphous model in electrolyte solvents and
(c) generated hydrogen bonds between cellulose and lignin molecules.
2.3. Separator Breakdown
During the battery working progress, it is possible that due to thermal inertia the
temperature can continue to rise until the separator would melt and short the electrodes,
leading to violent reactions and heat generation [
56
]. This phenomenon is called separator
breakdown, which is one step of the Li-ion battery thermal runaway process. Therefore,
the thermal properties of separators have a strong influence on battery safety. Numeri-
cal studies in this field can provide a better understanding of the separator breakdown
mechanism and give reliable prediction results. Other related performances such as ion
transport and the solid electrolyte interphase (SEI) degradation can be modelled as well by
numerical methods.
2.3.1. Thermal Transport
As mentioned in the Introduction, the separator acts as an essential role in improving
battery safety performance. Low thermal transport in Li-ion cells and battery packs has
been widely recognized as a critical technological concern that limits the use of Li-ion
batteries [
49
,
57
,
58
]. Therefore, the focus for the current development of advanced Li-ion
Molecules 2021,26, 478 10 of 15
battery separators is to enhance the safety performance of the separator and/or facilitate
the ionic flow through the separator during battery operation.
Standard MD simulation studies thermal transport and heat conduction across the
molecular interfaces at the given length-scales (~a few nms). For example, MD simulations
have been employed to model thermal transport across a variety of material pairs such
as graphene-semiconductor heterostructures [
59
], Si/Ge interfaces [
60
], silicene/silica
interfaces [
61
], graphene/phosphorene interfaces [
62
], etc. The thermal conductivity study
on the electrodes and solid electrolytes have also been carried out, including equilibrium
molecular dynamics [
63
] and nonequilibrium molecular dynamics simulation method [
64
].
Parviainen et al. [
40
] developed a new model, based on an existing MD code, to
include resistive heating and electronic thermal conduction. The model accounts for
dynamic changes of both tip geometry and temperature and gives an accurate and detailed
view of the temperature development, including the temperature gradient in tips. For
nanosized field emitters, it is critical to account for finite-size effects since both electric
and thermal conductivity have a strong size dependence at this scale (height 13.1 nm and
diameter 2 nm).
Non-equilibrium MD simulations were performed by Kawagoe et al. [
46
] on bulk
amorphous polyacrylic acid with three polymer chain lengths to investigate the molecular
mechanism of thermal energy transfer in heat conduction. The simulation results showed
that the dominant mechanism of thermal energy transfer in polyacrylic acid (PAA) was
intramolecular interaction. Consequently, the intramolecular interaction caused the thermal
conductivity to increase as the polymer chain length elongated, which also increased the
total thermal conductivity. The relation between thermal conductivity and the polymer
chain length results in a saturation curve, which will lead to the characterization of thermal
energy transfer in more complicated materials such as the layer-by-layer membranes.
Dhakane et al. [
48
] applied MD simulations for the calculation of thermal conductance
across the cathode-separator interface with the interface force field in Figure 7. It is shown
that molecular bridging at the interface results in up to 250% improvement in interfacial
thermal conductance for the 3-Aminopropyl triethoxysilane (APTES) case. These results
quantify the crucial role of the cathode-separator interface on thermal transport within
the Li-ion cell, as well as the potential improvement in interfacial thermal transport by
molecular bridging.
Molecules 2021, 26, x FOR PEER REVIEW 11 of 16
graphene-semiconductor heterostructures [59], Si/Ge interfaces [60], silicene/silica inter-
faces [61], graphene/phosphorene interfaces [62], etc. The thermal conductivity study on
the electrodes and solid electrolytes have also been carried out, including equilibrium mo-
lecular dynamics [63] and nonequilibrium molecular dynamics simulation method [64].
Parviainen et al. [40] developed a new model, based on an existing MD code, to in-
clude resistive heating and electronic thermal conduction. The model accounts for dy-
namic changes of both tip geometry and temperature and gives an accurate and detailed
view of the temperature development, including the temperature gradient in tips. For na-
nosized field emitters, it is critical to account for finite-size effects since both electric and
thermal conductivity have a strong size dependence at this scale (height 13.1 nm and di-
ameter 2 nm).
Non-equilibrium MD simulations were performed by Kawagoe et al. [46] on bulk
amorphous polyacrylic acid with three polymer chain lengths to investigate the molecular
mechanism of thermal energy transfer in heat conduction. The simulation results showed
that the dominant mechanism of thermal energy transfer in polyacrylic acid (PAA) was
intramolecular interaction. Consequently, the intramolecular interaction caused the ther-
mal conductivity to increase as the polymer chain length elongated, which also increased
the total thermal conductivity. The relation between thermal conductivity and the poly-
mer chain length results in a saturation curve, which will lead to the characterization of
thermal energy transfer in more complicated materials such as the layer-by-layer mem-
branes.
Dhakane et al. [48] applied MD simulations for the calculation of thermal conduct-
ance across the cathode-separator interface with the interface force field in Figure 7. It is
shown that molecular bridging at the interface results in up to 250% improvement in in-
terfacial thermal conductance for the 3-Aminopropyl triethoxysilane (APTES) case. These
results quantify the crucial role of the cathode-separator interface on thermal transport
within the Li-ion cell, as well as the potential improvement in interfacial thermal transport
by molecular bridging.
A two-dimensional electrochemical-thermal coupled model was developed by Li and
Tan [39] for a 38120-type LiFePO4 Li-ion battery. Modeling results showed that the sepa-
rator thickness strongly impacted battery energy density: the battery energy density
dropped from 148.8 W h/kg to 110.6 W h/kg, while the separator thickness increased from
5 µm to 100 µm. The battery temperature rise and temperature difference dropped when
both the separator thermal conductivity and heat capacity increased to 1 W m−1 K−1 and
3500 J kg−1 K−1, respectively.
Figure 7.
Representative images of the molecular assembly from Dhakane et al. [
48
]. (
a
) Molecular
structure for simulation of a case with a bridging molecular layer (30 APTES molecules) at the
LiCoO
2
-polyethylene interface. Hot reservoir (red rectangle on the left) and cold reservoir (blue
rectangle on the right) maintained at 350 K and 250 K respectively are shown. (
b
) Schematics of the
cathode-APTES interface for simulations with 10, 20, and 30 molecules.
Molecules 2021,26, 478 11 of 15
A two-dimensional electrochemical-thermal coupled model was developed by Li
and Tan [
39
] for a 38120-type LiFePO
4
Li-ion battery. Modeling results showed that the
separator thickness strongly impacted battery energy density: the battery energy density
dropped from 148.8 W h/kg to 110.6 W h/kg, while the separator thickness increased from
5
µ
m to 100
µ
m. The battery temperature rise and temperature difference dropped when
both the separator thermal conductivity and heat capacity increased to 1 W m−1K−1and
3500 J kg−1K−1, respectively.
2.3.2. Ion Transport
During the working procedure of the Li-ion batteries, the transportation of ions plays
an important role in battery performance. A separator membrane offers ion-conducting
routes between electrodes and also electronically isolates the electrodes to prevent internal
short-circuit failure, which eventually results in cell fire or explosion [
65
]. MD simulations
have been developed in this area to explore the transport mechanisms and previous
numerical studies investigated ion transport in the solid electrolyte [
66
], cathodes [
67
],
and SEI [
68
,
69
]. The numerical simulations applied for separators will be reviewed in this
section.
Vilˇciauskas et al. [
42
] performed first-principles MD simulations to study proton
conductivity at the fundamental molecular level, which represents a first step towards a
more detailed understanding of the proton conduction mechanisms in realistic phosphoric
acid-based polymer electrolyte materials. The solvation shell characteristics of the H-bond
network are significantly over coordinated as compared to those in pure phosphoric acid.
However, the lower density of H-bonds slightly increases the local molecular mobilities
and artificially increases the proton diffusion coefficient.
Xu et al. [
44
] investigated ionic microporous zeolite membranes to overcome the chal-
lenge of the trade-off between ion selectivity and conductivity associated with conventional
polymeric ion separators. They used the open-source software Packmol to construct the
model and applied the LAMMPS package for running the simulations. The proton concen-
tration in the zeolite structure (i.e., C
H+
) was determined to assist with understanding ion
diffusion behaviour in the zeolite pores since the equilibrium values of C
H+
are difficult to
measure experimentally. This type of separator showed the ability to drastically reduce the
self-discharge rates and enhance energy efficiencies.
Kim et al. [
45
] demonstrated the effect of the functional groups on the hydronium and
hydroxide ions in hydrated poly(ether ether ketone) (PEEK) using MD simulations. The hy-
dronium ion and hydroxide conductivity of the PEEK ion exchange membranes increased
as the mole ratio of the functionalized moiety in PEEK increased. The diffusivity of the
hydronium and hydroxide ions were calculated using their mean squared displacement in
the simulation process via the COMPASS force field.
2.3.3. Degradation
The most popular separator materials for Li-ion batteries with organic electrolytes
are polyolefin materials [
70
]. However, the low melting point of polyolefins (135
◦
C for
PE and 165
◦
C for PP) qualifies their utilization as a thermal fuse to shut down the cell
by losing porosity and permeability if an over-temperature condition occurs. The main
causes regarding separator degradation are typically traced to the lithium dendrite growth
caused by separator pores, attack through the electrolyte, blockage of passageways in the
separator over cycling, and structural degradation arising from elevated temperature or
high cycle number [71].
A reduced-order capacity-loss model was applied by Jin et al. [
29
] to improve compu-
tational efficiency without sacrificing model fidelity. This model captures the two primary
degradation mechanisms that occur in the graphite anode of a typical Li-ion cell: (a) capac-
ity loss due to SEI layer growth, and (b) capacity loss due to isolation of active material.
The model matches experimental capacity degradation results within a 20% error and
2400×faster
than currently existing more complex physically-based electrochemical models.
Molecules 2021,26, 478 12 of 15
Kim et al. [
41
] studied the formation and growth of SEI for the case of ethylene carbon-
ate (EC), DMC, and mixtures of these electrolytes using molecular dynamics simulations.
The simulation studied the distribution of organic and inorganic salts as a function of the
distance from the anode surface in Figure 8, and the results show that inorganic salts are
found closer to the anode surface while the region near the electrolyte–SEI interface is rich
in organic salts.
Molecules 2021, 26, x FOR PEER REVIEW 13 of 16
Kim et al. [41] studied the formation and growth of SEI for the case of ethylene car-
bonate (EC), DMC, and mixtures of these electrolytes using molecular dynamics simula-
tions. The simulation studied the distribution of organic and inorganic salts as a function
of the distance from the anode surface in Figure 8, and the results show that inorganic
salts are found closer to the anode surface while the region near the electrolyte–SEI inter-
face is rich in organic salts.
Figure 8. Distribution of the SEI components for different electrolytes (left chart). Atomic configurations from MD simu-
lations; the components of the SEI are identified (right) [41].
3. Summary and Outlook
The separator is a crucial component in Li-ion batteries with the function of prevent-
ing physical contact between the positive and negative electrodes of the battery and stop-
ping internal short while serving as the electrolyte reservoir to enable ionic transport. The
ideal separator should not only have large electrolyte uptake for lowering the cell internal
resistance but also have extremely thin thickness with strong mechanical strength, being
electrochemically and structurally stable, as well as having a highly porous structure with
great tortuosity to prevent the growth of dendritic lithium. In addition, the separator
should be able to shut the battery down when overheating occurs for battery safety, as
well as being cost-effective through the manufacturing process. However, it is challenging
for practical separators to possess these ideal properties simultaneously, and therefore it
becomes essential to balance different separator properties to achieve high-performance
batteries. Moreover, the safety issue is still another obstacle for the separator and Li-ion
battery applications.
In this paper, we have reviewed the recent numerical model advancements for Li-ion
battery separators. It included mathematical and mechanical analytical-based simulation
approaches such as FEA, CFD, and MD models. Through our summary, numerical simu-
lation can be applied in the investigation of the properties of a separator and the predic-
tion for the performance of the separators. Meanwhile, numerical studies not only provide
a time-efficient and cost-effective way but also show a comprehensive understanding of
the primary mechanism of the separator performance. Mathematical models describe cer-
tain parameters which are not known experimentally and provide the capacity of param-
eter adjustment. Mechanical models show a detailed microstructure of separators, and
combining with FEA and CFD models, the properties of separators can be simulated and
predicted. MD models demonstrate a more detailed view of the mechanisms, such as ther-
mal propagation, ion transportation, and degradation. Furthermore, key mechanical de-
sign parameters such as Young’s modulus and average strain rate for various types of
separator materials (i.e., polyolefin, PVDF, PP, PE, Cellulose/lignin, homogeneous solid
medium) were analyzed through numerical simulation and characterization approaches.
The development of robust, effective numerical tools to address the needs of fire safety of
Figure 8.
Distribution of the SEI components for different electrolytes (
left
chart). Atomic configurations from MD
simulations; the components of the SEI are identified (right) [41].
3. Summary and Outlook
The separator is a crucial component in Li-ion batteries with the function of preventing
physical contact between the positive and negative electrodes of the battery and stopping
internal short while serving as the electrolyte reservoir to enable ionic transport. The
ideal separator should not only have large electrolyte uptake for lowering the cell internal
resistance but also have extremely thin thickness with strong mechanical strength, being
electrochemically and structurally stable, as well as having a highly porous structure with
great tortuosity to prevent the growth of dendritic lithium. In addition, the separator
should be able to shut the battery down when overheating occurs for battery safety, as
well as being cost-effective through the manufacturing process. However, it is challenging
for practical separators to possess these ideal properties simultaneously, and therefore it
becomes essential to balance different separator properties to achieve high-performance
batteries. Moreover, the safety issue is still another obstacle for the separator and Li-ion
battery applications.
In this paper, we have reviewed the recent numerical model advancements for Li-ion
battery separators. It included mathematical and mechanical analytical-based simulation
approaches such as FEA, CFD, and MD models. Through our summary, numerical simula-
tion can be applied in the investigation of the properties of a separator and the prediction
for the performance of the separators. Meanwhile, numerical studies not only provide
a time-efficient and cost-effective way but also show a comprehensive understanding of
the primary mechanism of the separator performance. Mathematical models describe
certain parameters which are not known experimentally and provide the capacity of pa-
rameter adjustment. Mechanical models show a detailed microstructure of separators,
and combining with FEA and CFD models, the properties of separators can be simulated
and predicted. MD models demonstrate a more detailed view of the mechanisms, such as
thermal propagation, ion transportation, and degradation. Furthermore, key mechanical
design parameters such as Young’s modulus and average strain rate for various types of
separator materials (i.e., polyolefin, PVDF, PP, PE, Cellulose/lignin, homogeneous solid
medium) were analyzed through numerical simulation and characterization approaches.
The development of robust, effective numerical tools to address the needs of fire safety of
Molecules 2021,26, 478 13 of 15
separators will be beneficial to the battery industry, providing a complementary design
tool for safety engineering design and performance studies.
With the increasing demand of Li-ion batteries with high charge/discharge efficiency
and energy density in the future, battery separators with high performances are required
for both industrial and research purposes. Currently, the investigation on the separator
materials and performances is mainly based on experiments. Numerical simulations can
provide reliable results compared to experiments and contribute to study the mechanism
of some effects, meanwhile, numerical simulations provide an efficient and economical
way to develop the separator and battery system. To provide safer, more functional, and
powerful separators, developing a novel Li-ion battery or battery system and optimiz-
ing the manufacturing process is critical. The following numerical investigations and
development of models are recommended in the future: (i) an effective pre-system failure
numerical tool that is able to diagnose the thermal propagation, short-circuiting, separator
degradation; (ii) a novel thermal-runaway model for Li-ion battery systems that is able to
incorporate multiple battery separator materials with different mechanical and physical
properties; (iii) coupling of multi-scale simulation models to study the all-inclusive coupled
internal/external phenomena of Li-ion battery fires; and (iv) the simulation findings can be
inputted as useful parameters for machine learning algorithms.
Author Contributions:
Conceptualization, A.L. and A.C.Y.Y.; methodology, A.L. and W.W.; formal
analysis, C.W.; investigation, I.M.D.C.C.; resources, T.B.Y.C.; writing—original draft preparation,
A.L.; writing—review and editing, A.C.Y.Y., Q.N.C. and J.Z.; visualization, A.L.; supervision, G.H.Y.;
project administration, A.C.Y.Y.; funding acquisition, G.H.Y. All authors have read and agreed to the
published version of the manuscript.
Funding:
This research was funded by the Australian Research Council (ARC Industrial Trans-
formation Training Centre IC170100032), the Australian Government Research Training Program
Scholarship and the Tactical Research Fund, Bushfire and Natural Hazard Cooperative Research
Centre in Australia. All financial and technical supports are deeply appreciated by the authors.
Acknowledgments:
The author sincerely thank Hu Long for assisting with the image format suggestions.
Conflicts of Interest: The authors declare no conflict of interest.
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