Yao
Liu
a,
Wen-Bei
Yu
*b and
Bai-Xiang
Xu
*a
aMechanics of Functional Materials Division, Department of Materials Science, TU Darmstadt, Otto-Berndt-Straße 3, Darmstadt 64287, Germany. E-mail: xu@mfm.tu-darmstadt.de
bState Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan 430070, China. E-mail: yuwenbei252302@163.com
First published on 12th November 2021
Understanding the effect of material properties on the interface impedance is crucial for high energy all-solid-state thin film lithium-ion battery design. Nevertheless, reaction kinetics determined by the free enthalpy difference at the interface and the vacancy effect in solids are always ignored or simplified when simulating battery impedance. In this work, we obtain the numerical impedance results by using an advanced electrochemical model (modified Planck–Nernst–Poisson model coupled with the new Frumkin–Butler–Volmer equation), whereby the mentioned issues are taken into account. More importantly, we derive a comprehensive equivalent circuit model from the electrochemical model, where all circuit elements are quantified from material properties. The results show that the high-frequency semicircle in the impedance spectrum is due to the bulk impedance and is associated with ion migration. Moreover, the plots at low and medium frequencies are assigned to the charge transfer resistance and the space charge layer capacitance. The results show that batteries with a higher free enthalpy difference lead to a significant decrease of the charge transfer resistance, but increase the electrostatic potential drop. Lithium-ion diffusivity has no impact on the interface impedance, but can dominantly reduce the bulk resistance. The simulation results were verified at the end against experimental impedance spectra.
The current state-of-the-art impedance modelling and simulations can be roughly classified into three categories, i.e., the electrochemical model,25 the equivalent circuit model,26,27 and the density functional theory (DFT) calculations.28 Electrochemical models are derived from basic thermodynamics, e.g., the electrochemical potential, and the numerical results of such models provide spatial and temporal distributions of the concentration and electrostatic potential. They can be used for the battery cell impedance calculation.29–31 However, the present work ignores or simplifies the lithium-ion kinetic reaction at the interface.30 As shown in Ref. 11, the interface impedance decreases from 1710 Ω cm2 to 1 Ω cm2 with the formation of an ultrathin Al2O3 layer, and the reason lies in the lithium-ion binding energy difference of materials (11.4 to 1.6 eV nm−2). Nevertheless, the energy parameters that appear in the Butler–Volmer (BV) equation are never addressed in current electrochemical impedance models. Moreover, the extensively employed Planck–Nernst–Poisson (PNP) model is mostly taken from the case of liquid electrolytes and the specific feature of solid materials is overlooked, e.g., the unoccupied regular lattice sites (or called vacancies). In comparison to the electrochemical model, the equivalent circuit model is more simple and is able to quantify the impedance of each part. However, this model fails to explain the physical origin of the battery impedance and different equivalent circuit models can produce the same results. As shown in ref. 27 and 32, two different equivalent circuit models are proposed to explain the thin film battery impedance but both produce the same spectroscopy results. Therefore, the electrochemical model and the corresponding equivalent circuit model are combined to analyse the battery impedance. The DFT calculations show an obvious advantage when explaining the interface impedance from material properties, i.e., the atomic structure11 and the activation energy. Unfortunately, this method cannot calculate the interface impedance directly and fails to estimate the overall impedance of batteries as well. Therefore, a methodology to include the information of the atomic structure and the energy barrier within the impedance calculation directly is still missing.
To overcome this issue, an advanced electrochemical model and the corresponding equivalent circuit model for all-solid-state thin film battery impedance calculations are proposed in this work. The classical diffusion model can be extended to model ionic diffusion in solids, which describes ionic transport as the hopping of individual ions from one lattice site to the vacancies in the crystal structural framework.33,34 To consider this feature, the effect of vacancies in the framework of solids is concluded in the modified Planck–Nernst–Poisson (MPNP) model. Moreover, the lithium-ion kinetic reaction at the electrode/electrolyte interface is modelled by using the new Frumkin–Butler–Volmer (FBV) equation. Unlike the widely applied BV equation,35,36 in this equation, the standard activation energy of materials and the affordable lattice sites for lithium-ion transfer at the interface are taken into consideration. This work shows the possibility to calculate thin film battery impedance by considering the energy barrier for the specific material. On the other hand, we take a further step and propose a corresponding equivalent circuit model based on the advanced electrochemical model to gain deeper understanding of impedance spectroscopy. All the elements in the equivalent circuit model can be quantified from material properties and the related equilibrium quantities such as the exchange current and the bulk electrostatic potentials. This work is the first theoretical study that considers reaction kinetics in the battery impedance calculation. It provides a novel perspective on the microscopic origin of the interface resistance. The article is organized as follows: In Section 2, lithium-ion reaction kinetics at the solid/solid interface, the MPNP-FBV model, the impedance calculation methodology, and the novel equivalent circuit model are presented. Section 3 shows the calculated exchange current and the impedance spectroscopy results. Here, the impact of the free enthalpy difference, diffusivity, and the electric double layer structure on the impedance is investigated. A summary of this work and an outlook are shown in Section 4.
To deepen the understanding, the free enthalpy profile of the electrochemical reaction is depicted in Fig. 1c. Unless otherwise stated, the subscripts “c” and “e” in this work indicate the cathode and the electrolyte, respectively. Gc (Ge) denotes the corresponding actual free enthalpy and is determined by both the standard free enthalpy GcΘ (GeΘ) and the concentration cc (ce). In addition, ΔG is the free enthalpy difference of materials and is expressed as ΔG = Gc − Ge.
To take the vacancy effect into consideration, the modified FBV equation is employed to model the lithium-ion reaction at the cathode/electrolyte interface and is given by .17 It should be noted that the amount of vacancies, e.g., VLi+,(e) and VLi,(c), constrains the lithium-ion reaction rate at the interface. The partial flux of the reaction is given by the following equation:
(1) |
(2) |
(3) |
(4) |
Eqn (2) and (4) indicate that the charge transfer resistance is explicitly determined by the standard activation energy barrier ΔGiΘ (i indicating c or e) and the equilibrium concentrations cc and ce at the interface. The latter is also eventually determined by the other material parameters.
The two electrostatic potentials at the solid/solid interface can be related using the Gouy–Chapman–Stern model (or called the diffuse double layer model).38 Moreover, the experimental results15 also show the similar distribution of the electrostatic potential in solid-state batteries. Within the diffuse double layer model, the electrostatic potential drops both in the space charge layer and the Stern layer. Therefore, the potential distribution in the space charge layer should be numerically identified and the interface condition is defined as
Φc = Φe − λs∇Φc. | (5) |
(6) |
In addition, the relationship between the electric charge density and the electrostatic potential is denoted by the Poisson equation
(7) |
(8) |
In batteries, charges are prone to accumulate or deplete at the interface and form the space charge layer, however, lithium-ion concentrations remain almost homogeneous in the bulk. We first derive the bulk impedance of thin film batteries40
(9) |
(10) |
According to our previous investigation,17 the analytical concentration distribution in the MPNP model can be expressed as
(11) |
(12) |
The space charge layer capacitance is related to the charge density43 and the analytical solution is defined as
(13) |
(14) |
The charge transfer resistance Rct and the space charge layer capacitance can be calculated from eqn (4) and (13) as explained in the previous subsection. The anode has been overlooked in this study, thus, no lithium-ion reaction occurs at the right-hand side of the electrolyte. Consequently, the equivalent circuit model of the solid-state thin film battery is simplified and the blue elements cannot be taken into account. Based on Fig. 1b and the analytical results, the impedance of the proposed equivalent circuit model is given by
(15) |
(16) |
Z = Zc + Ze. | (17) |
In particular, Cini is the space charge layer capacitance at the interface, and Csuc is the charge accumulation at the cathode surface. Rini and Rsui are the space charge layer resistances, and are associated with the frequency dependent charge density in the space charge layer. In most studies, the Warburg impedance is widely applied to explain the diffusion induced impedance and the analytical results can be expressed as44Z = RTci(ω)/FI(ω)ceqi, where I(ω) and ci(ω) are the frequency dependent current and concentration. Therefore, the finite-length or the finite-space Warburg impedances are the results obtained with specific boundary conditions and electrochemical models. In this work, we followed the method introduced by Maier45,46 to investigate the space charge layer impedance and more details will be given in the following section. The charge transfer resistance in the cathode (or the electrolyte) is proportional to the concentration and is depicted by
(18) |
(19) |
Parameter | Unit | Value | Description |
---|---|---|---|
a Designed parameters. b Parameters taken from the literature.30,37,48 | |||
L e | nm | 50 | Thickness of the electrolytea |
L c | nm | 50 | Thickness of the cathodea |
λ s | nm | 0.3 | Thickness of the stern layerb |
D c | m2 s−1 | 10−14 | Diffusivity of lithium ions in the cathodea |
D e | m2 s−1 | 10−14 | Diffusivity of lithium ions in the electrolytea |
ΔGcΘ | eV | 0.5 | Activation energy barrierb |
ΔGeΘ | eV | 0.8 | Activation energy barrierb |
ε 0 | F m−1 | 8.85 × 10−12 | Vacuum permittivityb |
ε e | — | 80 | Relative permittivity of the electrolytea |
ε c | — | 80 | Relative permittivity of the cathodea |
c max | mol m−3 | 104 | Maximum lithium ion concentrationa |
c e | mol m−3 | 5 × 103 | Initial concentration in the electrolytea |
c c | mol m−3 | 5 × 103 | Initial concentration in the cathodea |
β | — | 0.5 | Symmetry factorb |
F | C mol−1 | 96485 | Faraday constantb |
T | K | 298.15 | Temperatureb |
R | J mol−1 K−1 | 8.314 | Gas constantb |
z + | — | 1 | Lithium-ion valenceb |
z − | — | −1 | Electron valenceb |
K o | m4 mol−1 s−1 | 100 | Oxidation reaction ratea |
K r | m4 mol−1 s−1 | 100 | Reduction reaction ratea |
A | m2 | 10−4 | Geometrical surfacea |
Fig. 2 depicts the resulting currents of the half cell as a function of time at two specific frequencies, i.e., ω = 1 and 106 Hz. The legends “Real” and “Imaginary” indicate the real and the imaginary parts of the total current, respectively. It should be noted that the half cell reaches a quasi-equilibrium state with the perturbation potential, and the amplitude of the resulting current is utilized for the battery impedance calculation, as shown in eqn (8). From Fig. 2a and b, we can conclude that the amplitude of current increases with increasing frequency. Therefore, this conclusion can explain that the impedance magnitude of batteries decreases at high frequencies.49
Moreover, to identify the impedance contribution, the faradaic current If and the maxwell displacement current Id, as well as the total current I are shown in Fig. 2c and d,. At frequency ω = 1 Hz, the displacement current equals zero and the plots of the faradaic current and the displacement current appear to be superimposed. The results show that the impedance associated with the lithium-ion migration plays an important role at low frequencies. However, in the high-frequency region, the maxwell current increases while the faradaic current decreases, which means that the applied potential plays a more important role. The reason is that lithium-ions cannot migrate inside materials because of the rapid frequency change. Therefore, thin film batteries are prone to exhibit dielectric properties at high frequencies.
(20) |
(21) |
It should be noted that the standard free enthalpy difference GcΘ − GeΘ numerically equals the standard activation energy difference −(ΔGcΘ − ΔGeΘ). To investigate the influence of the free enthalpy difference on the charge transfer resistance, the lithium-ion concentration and the standard activation energy are discussed here, respectively. The diffusion coefficients are De = Dc = 10−14 m2 s−1, and other parameters are shown in Table 1.
Fig. 3 shows the plot of the charge transfer resistance and the total electrostatic potential drop with respect to the free enthalpy difference, e.g., the state of charge and the standard activation energy. The charge transfer resistance is calculated by using eqn (2) and (4), and the concentrations at the intrinsic equilibrium state are determined numerically by using the MPNP-FBV model. The total electrostatic potential drop equals to the difference of bulk potentials and is expressed by ΔΦtotal = Φbuc − Φbue. As can be seen in Fig. 3a and b, the lithium-ion concentration of the solid-state electrolyte is , and the standard activation energies are assumed to be ΔGcΘ = 0.5 eV and ΔGeΘ = 0.8 eV. It should be noted that the activation energies of materials can be identified through the DFT calculations.48 The initial concentrations of the cathode are , which represents that the theoretical state of charge (SOC) varies from 10% to 90%.
Fig. 3c and d show that lithium-ion concentrations are and the electrolyte standard activation energy remains ΔGeΘ = 0.8 eV, while the cathode activation energy varies from ΔGcΘ = 0.3–0.7 eV. Here, the free enthalpy difference ΔG is calculated by using eqn (21), Fig. 3a and c show that the charge transfer resistance decreases with increasing free enthalpy difference. In addition, ref. 50 and 51 show that the charge transfer resistance decreases with increasing concentration and verify the numerical results. Furthermore, Fig. 3b and d show the plot of the total electrostatic potential drop as a function of the free enthalpy difference. The results demonstrate that the potential drop is equal to the free enthalpy difference, i.e., ∣ΔΦtotal∣ = ΔG. It is evident that when the electrolyte free enthalpy remains stable, increasing the free enthalpy difference can significantly reduce the charge transfer resistance. Nevertheless, increasing the large free enthalpy difference also leads to a large electrostatic potential drop at the interface, which is harmful to the working potential. Therefore, the free enthalpy difference between the cathode and the electrolyte is a paradox criterion for high performance battery design and has to be optimized.
The initial normalized concentrations are fixed at , and lithium-ion diffusion coefficients are Dc = De = 10−14 m2 s−1. The effect of the free enthalpy difference is assessed by performing simulations for the cathode standard activation energies which are given as ΔGcΘ = 0.5 and 0.6 eV, while the electrolyte standard activation energy is given as ΔGeΘ = 0.8 eV. The considered frequency for the perturbation potential is from 1 ≤ ω ≤ 106 Hz, and other parameters are shown in Table 1. It should be noted that 50 samples of the corresponding current are recorded. Therefore each point in the impedance curves denotes a specific frequency.
Fig. 4a to c depict all-solid-state thin film battery impedance curves for the two different standard activation energies of the cathode, ΔGcΘ = 0.5 and 0.6 eV. The corresponding equilibrium states are shown in Fig. 4d to f. In the legend, “Num” denotes the impedance results calculated by using the MPNP-FBV model, and “Equ” represents the analytical results estimated by using the equivalent circuit model. Fig. 4a shows that the impedance plots of the half cell can be divided into two regions, “I” and “II”, and the intersection points with the real impedance are denoted by “A” and “B”, respectively. In addition, “I” is the high-frequency region, and the impedance results in the region “II” are calculated at the medium and low frequencies.
In the region “I”, the impedance curve shows an ideal semicircle and is assumed to be a resistor in series with a capacitor.30 It can be observed that the impedance plots are overlapped in the region “I” which means that the activation energy cannot influence the thin film battery impedance in the high-frequency region. According to the numerical calculations, the value of intersection point “A” equals to 5.4 Ω and the capacitance is calculated to be 2.84 × 10−6 F. Based on the analytical solution in eqn (9), the bulk impedances are Rbuc = Rbue = 2.66 Ω and Cbuc = Cbue = 1.42 × 10−6 F. The results indicate that the value of the intersection point “A” equals the total bulk resistance, e.g., Rbuc + Rbue, and the capacitance is associated with the bulk capacitor. From the discussion, it can be concluded that the region “I” shown in Fig. 4a is caused by the thin film battery bulk impedance.
The region “II” contributes to the interface and surface impedance, and is regarded as a capacitor in parallel with a resistor then in series with a capacitor. The shunt-wound resistor and capacitor attribute to the cathode/electrolyte interface impedance, i.e., the charge transfer resistance and the interface space charge layer capacitance. The series-wound capacitor is explained by the space charge layer at the cathode surface, as shown in Fig. 1b. The discrepancy between the impedance curves in the region “II” indicates that the lithium-ion kinetic reaction plays an important role in the charge transfer resistance.
As can be seen from Fig. 4a the charge transfer resistance can be read as Rct = 2.9 Ω for the case of ΔGcΘ = 0.6 eV. The value of the intersection point “B” is 8.3 Ω, and equals the total thin film battery resistance, i.e., Rct + Rbuc + Rbue. A similar conclusion can be drawn when the standard activation energy is ΔGcΘ = 0.5 eV. The space charge layer capacitances at the interface and the surface are calculated by using eqn (13). Thus, the bulk electrostatic potential plays an important role in the capacitance calculation. In this study, the standard activation energies are ΔGcΘ = 0.5 and 0.6 eV, ΔGeΘ = 0.8 eV and the concentrations is equal to . Based on eqn (21), the free enthalpy differences are calculated to be ΔG = 0.3 and 0.2 eV, respectively. Moreover, the previous section indicates that the total electrostatic potential drop equals to the free enthalpy difference, as shown in Fig. 3b and d. Therefore, the total electrostatic potential drops lead to ΔΦtotal = −0.3 and −0.2 V. With the boundary conditions, e.g., Φbue = 0 and ∇Φbue = 0, the cathode bulk electrostatic potentials are equal to Φbuc = −0.3 and −0.2 V. Referring to eqn (13), the space charge layer capacitances at the interface are calculated to be Cinc = Cine = 1.52 × 10−4 and 1.90 × 10−4 F and the surface capacitances Csuc as 8.03 × 10−5 and 1.02 × 10−4 F, for the two cases ΔGcΘ = 0.5 and 0.6 eV, respectively. By using these results and eqn (17), the analytical impedance spectra are plotted and fit quite well with the numerical curves as predicted.
However, if we analyse in depth, the space charge layer cannot be simply regarded as an ideal capacitor. As shown in the citations,52–55 the real portion of the interface impedance involves two contributions: the charge transfer resistance and the space charge layer resistance. Therefore, the space charge layer impedance consists of a capacitance and a resistance. In addition, the space charge layer resistance is regarded as a constant ohmic resistance and is independent of the lithium-ion concentration.52 Nevertheless, Maier45,46 pointed out that the space charge layer resistance is caused by the deviation from the bulk contribution and is expressed as
(22) |
The parameter θ, which is called the degree of influence, expresses this in a straightforward way, where θ refers to the enrichment or depletion effect on the charge carrier number in the space charge layer regions. During the impedance measurement a perturbation potential is applied. Hence, the charge accumulation or depletion θ and the space charge layer resistance should be frequency dependent. The mobility in eqn (22) is taken as independent. However, lithium-ion diffusivity in the space charge layer is strongly dependent on the concentration and differs from the bulk according to the study.19 Therefore, to consider this effect, a frequency-dependent ohmic resistance is employed in the proposed equivalent circuit model, and is expressed as Rpi = Rsuc + Rinc + Rine. Adjusting with numerical results, it can be found that Rpi = Zre/ω, where ω indicates the applied frequency, and Zre is the real impedance of the battery system at ω = 1 Hz. Fig. 4b shows thin film battery conductivity with the proposed frequency-dependent resistance. “Equ (WO/Rpi)” denotes the equivalent circuit model without the space charge layer resistance. It can be concluded that the frequency-dependent ohmic resistance can well explain the tail of material conductivity in the low-frequency region, and this conclusion is also presented in our previous work.40 As expected, the analytical imaginary portion of the complex impedance fits well with the numerical results, as shown in Fig. 4c.
To explain the impedance results more clearly, the equilibrium states with the different standard activation energies are also presented in Fig. 4d to f. It shows that the bulk concentrations remain for both the standard activation energies ΔGcΘ = 0.5 and 0.6 eV. Therefore, we can conclude that the bulk resistance and the capacitance are not influenced by the activation energy, and the impedance results are also verified by the overlapped curves in the region “I”. However, the concentration distributions at the interface are different and indicate that the interface impedance in these two cases are different, as depicted in Fig. 4e. Hence, it can explain the diversity in the region “II” shown in Fig. 4a. Moreover, the similar conclusion about the cathode surface capacitance also can be drawn using Fig. 4d.
The impedance curves and the equilibrium states with different concentrations are compared for the two cases as shown in Fig. 5. Fig. 5a shows that the intersection point “A” of the semi-circle in the region “I” increases with concentration. This phenomenon can be explained by using eqn (9). The analytical results for the total bulk resistances Rbuc + Rbue are 7.1 and 5.4 Ω for and 0.5, respectively. They are very well verified by the numerical results as shown in Fig. 5a. In addition, the charge transfer resistances can be determined from the figure: Rct = 2 and 1.53 Ω, which can be confirmed from the intersection point “B”. Referring to eqn (21), the free enthalpy differences are obtained as ΔG = 0.278 and 0.3 eV, respectively. Thus, the bulk electrostatic potentials in the cathode at the equilibrium state should be Φbuc = −0.278 and −0.3 V, and the cathode surface space charge capacitances are Csuc = 6.43 × 10−5 and 8.03 × 10−5 F, respectively. The capacitance is calculated from C = − ∂Q/∂Φ, and is determined by the electric field and the charge density. As shown in eqn (13), the space charge layer capacitance is related to the initial concentration. Thus, the analytical interface capacitances are Cinc = 1.08 × 10−4 F and Cine = 1.7 × 10−4 F when the cathode concentration is . For the case of , the charge densities are equal and the capacitances are calculated to be Cinc = Cine = 1.51 × 10−4 F. A comparison between Fig. 4 and 5 shows that the lithium-ion concentration has relatively smaller influence on the interface impedance than the standard activation energy. Nevertheless, the concentration plays a comparatively more important role in the bulk resistance.
Fig. 6a to c depict the impedance plots for the two cases with different lithium-ion diffusion coefficients of the solid-state electrolyte. The analytical impedance curves again fit very well with the numerical results and show the applicability of the proposed equivalent circuit model for all-solid-state thin film batteries. Fig. 6a shows that the intersection point “A” decreases if the lithium-ion diffusivity is increased, while the charge transfer resistances in these two cases are numerically equal. By using eqn (9), the electrolyte analytical bulk resistances are calculated to be Rbue = 0.27 and 2.7 Ω, for De = 10−13 and 10−14 m2 s−1, respectively. Thus, the total bulk resistances are 2.97 and 5.4 Ω, and confirm the numerical results. The charge transfer resistance can be clearly explained by using the half cell at the equilibrium state, as depicted in Fig. 6d to f. The results show that the charge density and the electrostatic potential are not influenced by the lithium-ion diffusion coefficient. Therefore, the space charge layer resistance and the space charge layer capacitance remain the same for the two cases under comparison. From these results, it can be concluded that increasing the lithium-ion diffusion coefficients may not help to reduce the interface impedance, but it can play an important role in the bulk resistance.
Fig. 7a to c present the half cell impedance spectroscopy results for the above two cases, namely the diffuse double layer model and the compact double layer model. Note that the analytical results fit well with the numerical results based on the electrochemical model, and confirms the applicability of the proposed equivalent circuit model. As shown in Fig. 7a, the Nyquist plots nearly overlap on the same line in the region “I” regardless of the electrical double layer (EDL) structural changes. In other words, the interface structure has no significant effects on the impedance plots at medium and high frequencies. By contrast, it is interesting to note that the semicircle caused by the charge transfer resistance and the interface capacitance in the region “II” vanishes in the compact double layer model. To further explore the reason for this phenomenon, the concentration and the potential distributions at the intrinsic equilibrium state are plotted. Fig. 7e shows that no charge density formation or depletion occurs at the interface in the case of the compact double layer structure. The space charge layer capacitance is associated with the redox reaction and is determined by the charge density, referring to eqn (13). Thus, the interface capacitance Cini can be ignored under this circumstance. The charge transfer resistance of the diffuse double layer structure is equal to Rct = 1.53 Ω and is much larger than that of the compact double layer case, i.e., Rct = 0.10 Ω. The surface concentration distributions with different EDL structures appear to be superimposed as shown in Fig. 7d and indicates that the surface capacitance Csuc is not influenced by the EDL structure when the material thickness is much larger than that of the surface space charge layer, i.e., Ls ≪ L. Based on these results, we can conclude that all-solid-state thin film batteries with a large potential drop in the Stern layer lead to a relatively high charge transfer resistance and the space charge layer capacitance.
Fig. 8 shows the charge transfer resistance curves for the experimental and numerical results. As shown in Fig. 8a and b, Rct decreases with increasing battery temperature or increasing SOC. The same tendency is also observed in our numerical results. More specifically, the experimental value of the charge transfer resistance at 318 K is reduced to 1/10 of that at 278 K, and the measured Rct at a SOC of 90% decreases to 1/3 of that at 10%. As can be seen, the calculated charge transfer resistance at SOC = 10% and SOC = 90% reads Rct = 1.53 mΩ and 0.41 mΩ, respectively. In other words, similar conclusions can also be derived from our numerical model. Because of the ideal assumption and the realistic situation, the calculated results show deviations at certain points from the corresponding experimental data, particularly at 278 K. This is attributed to parameter deviations at different temperatures such as permittivity. Nevertheless, it is still sufficient to demonstrate the applicability of the MPNP-FBV model for the charge transfer resistance calculation.
Fig. 8 The experimental and calculated charge transfer resistance Rct at different temperatures (a) and states of charge (b). Reproduced with permission from Xueyuan Wang et al.50 Copyright 2019 Elsevier. |
Fig. 9 shows the numerical and the experimental impedance spectroscopy results of the LiCoO2/LiPON/Li thin film battery. Even though a slight difference exists, it can be concluded that the equivalent circuit model makes it possible to estimate the impedance of the thin-film battery at the solid-state. Similar to the experimental data, two semicircles appear in the numerical impedance spectra, and the semicircular arcs in the high frequency region are due to lithium-ion conduction in the LiPON bulk. Another semicircle is due to the charge transfer reaction at the LiCoO2/LiPON interface, and the same conclusion is also drawn in Fig. 4. The tail in the low-frequency region originates from the charge accumulation in the space charge layer as expected. Therefore, the charge transfer resistance and the thin film battery impedance verification can still demonstrate the applicability of the proposed equivalent circuit model.
Fig. 9 Impedance spectroscopy of the LiCoO2/LiPON/Li all-solid-state thin film battery. Reproduced with permission from Yasutoshi Iriyama et al.61 Copyright 2005 Elsevier. |
Since in the MPNP-FBV model, the vacancy effect in solids is included, we could obtain reasonable results for the concentration and the electrostatic potential distributions in the space charge layer region. In addition, we derived successfully the analytical results for the MPNP-FBV model. Thereafter, we take a further step and introduce a methodology to identify the bulk electrostatic potential which is critical for the space charge layer capacitance calculation. Thus, all the circuit elements in the proposed model are quantified based on the analytical solutions and stem closely from material properties. To deepen the understanding of battery impedance, the influence of different material parameters on the battery impedance has been investigated. The results show that the thin film battery with a large free enthalpy difference will lead to a large potential drop across the interface, and is unfavorable for battery applications. Nevertheless, it has a low charge transfer resistance. On the other hand, increasing the electrolyte conductivity cannot help to reduce the interface impedance, but reduces the bulk resistance. Since the solid/solid interface model is still unsettled, different EDL structures have also been discussed comparatively in this work. We observe that the impedance associated with the space charge layer capacitance vanishes when the diffuse double layer model is applied. Interestingly, under this circumstance, impedance spectroscopy is unusual in comparison to the experimental results. Therefore, our work provides an easy way to quantify the battery impedance from the fundamental material properties and also shows the perspective to optimize the solid–solid interface. As future work, the MPNP-FBV model can make use of the DFT results in the calculation of the activation energy for specific systems. In this sense a multiscale modeling of impedance can be expected.
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