Unveiling the First Nucleation and Growth Steps of Inorganic Solid

The SEI layer is composed of organic and inorganic species, resultant from the ... electrode as well as its ionic and electronic diffusion and transpo...
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C: Energy Conversion and Storage; Energy and Charge Transport

Unveiling the First Nucleation and Growth Steps of Inorganic Solid Electrolyte Interphase Components Asma Marzouk, Victor Ponce, Laura Benitez, Fernando A. Soto, Kie Hankins, Jorge M Seminario, Perla B. Balbuena, and Fedwa El-Mellouhi J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b08398 • Publication Date (Web): 21 Oct 2018 Downloaded from http://pubs.acs.org on October 22, 2018

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Unveiling the First Nucleation and Growth Steps of Inorganic Solid Electrolyte Interphase Components Asma Marzouk a, Victor Ponceb, Laura Benitezb,c, Fernando A. Sotob, Kie Hankinsb, Jorge M. Seminariob,c,d,*, Perla B. Balbuena b, d, e * and Fedwa El-Mellouhi a,* *[email protected], [email protected], [email protected]

a

Hamad Bin Khalifa University, Qatar Environment and Energy Reseach Institute, PO BOX 34110, Doha, Qatar b Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States c Department of Electrical and Computer Engineering, Texas A&M University College Station, Texas 77843, United States d Department of Materials Science and Engineering, Texas A&M University College Station, Texas 77843, United States e Department of Chemistry, Texas A&M University College Station, Texas 77843, United States

Abstract The complexity of the solid electrolyte interphase (SEI) in lithium-ion batteries with graphitic electrodes has triggered extensive research efforts due to its crucial role on the lifetime of the battery. The SEI layer is composed of organic and inorganic species, resultant from the electrolyte decomposition at the electrode-electrolyte interface upon the first cycles of the battery. A stable SEI layer is essential to maintain the chemical and mechanical stability of the electrode as well as the electrochemical stability of the electrolyte in order to prevent further irreversible capacity loss. This work uses computational crystal structure prediction genetic evolutionary algorithms to simulate the nucleation, growth, and aggregation of the inorganic products forming the SEI mosaic film. In depth investigation of the growth mechanisms of LiF and Li2CO3 starting from the first nucleation seeds is undertaken. The cluster-stacking and layer-by-layer SEI growth on the graphite surface as well as near shore SEI layer cluster aggregation growth mode are shown to be strongly dependent on the electrode degree of lithiation and nature of surface termination groups. Comparison among the various growth

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modes suggests that the most likely scenario is a mixed mode: small clusters may be formed in near shore locations and migrate toward the surface during cycling, while nucleation and growth at the surface may also exist. This mixed mode of growth is consistent with a heterogeneous “mosaic” SEI picture suggested in the literature.

Introduction The nucleation and growth of inorganic crystals have been the focus of a large number of experimental 1–6 and theoretical 6–13 investigations since the early eighties. Within the family of alkali halides, for example, the growth of LiF interested several research communities 14–17 due to its great potential in optics, optoelectronics, nuclear reactors and energy storage applications. Most importantly, LiF constitutes together with Li2CO3 the primary inorganic components of the solid electrolyte interphase SEI

18

which was initially introduced in the

seventies by Dey and Peled 19,20 as a protective layer formed during the first charge of a lithiumion battery that ensures ionic conduction and electronic insulation. Unveiling the first nucleation steps of the SEI layer is crucial for understanding its morphology, which governs its adhesion to the electrode as well as its ionic and electronic diffusion and transport properties. This knowledge is also important to understand and mitigate battery capacity degradation during cycling caused by the uncontrolled continuous growth or delamination of the SEI 21. Among the various SEI components, LiF has been suggested as one of the most promising candidates for artificial SEI layers or coatings on Li metal anodes

22

. However, since the

electrolyte contains a variety of components (solvent, salt, additives), the SEI is actually formed by a number of other products resulting from the decomposition of these species.23–25 How and when do these products nucleate and grow is still very much unknown and is one of the greatest challenges of battery materials research. SEI layer models suggest the presence of 2   

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a dense block of inorganic components forming a mosaic thin film found near the electrode (inner layer) followed by a porous organic layer

26

near the electrolyte/SEI interface (outer

layer).27–29 However this structure is highly dependent on the chemical nature of the electrode and the electrolyte. In general, thin film growth depends on several parameters such as the orientation and chemical reactivity of the surface but most importantly on the lattice mismatch between the substrate and the adsorbate which favors either the layer by layer growth, cluster growth, or a mixture of both

30–32

. Nevertheless, other factors such as the

chemical/electrochemical stability of the nascent phases may also play a role 33,34. For example, the SEI layer formation on lithiated graphite anode constitutes a challenging case to the layer by layer growth mode of a crystal such as LiF because of the large lattice mismatch between the graphitic inter-sheet distance of about ~3.6 Å 35 and the Li-F bond length of ~2 Å 36. Thus, unveiling the interfacial phenomena remains a big challenge and the SEI nucleation and growth has not been fully understood, experimentally nor theoretically. The main obstacles for elucidation of this growth process arise from the complexity of the in-situ characterization coupled to the challenge of developing a descriptive model of the evolution of the dynamic SEI growth. Prior work addressed the first nucleation and growth steps of some of the main components of the SEI layer using electronic structure calculations revealing important features related to the electronic structure of the nascent layers33,37–42. For example, the electronic properties of 𝐿𝑖 𝐹 clusters reported by Lintuluoto 10 showed the lack of dependency between the cluster size and the corresponding Mulliken charges together with a large dissociation energy of the LiF monomer into 𝐿𝑖

and 𝐹

ions. Subsequent computational studies

8,10,12

investigated the

growth and stability of different isomers of LiF clusters by sequential stacking of cubic or ring building blocks leading to the formation of cuboid and ring-like structures. LiF growth mode using a chain building block has also been attempted leading to the formation of low

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dimensional nanocrystals 11. It is worth noting that bulk LiF crystalizes in the cubic NaCl type structure with a lattice parameter of 4.03 Å, leading to the speculation that a cuboid growth mode might be the most favorable. Interestingly, most of the previous investigations agreed that neutral isomers of 𝐿𝑖 𝐹 clusters prefer the ring-like growth mode with rare emergence of the cuboid structures at specific cluster sizes.43 This deviation from the bulk-like growth mode for alkali halide clusters is probably due to the interaction between the ions forming the cluster and the size of the constituents’ ionic radii

44

. In fact, LiF clusters prefer to form rings, a

configuration favored by the small ionic radius of the fluorine (147 pm) combined with the larger radius of the lithium (182 pm) 45. The energy difference between the ring-like and cuboid structures is found to vary between 0.12 and 0.2 eV depending on the level of electronic structure calculation employed 𝐿𝑖 𝐹 and 𝐿𝑖 𝐹

10

. According to Aguado et al.45 and Lintuluoto et al.10, the

clusters are found to be more stable with the ring-like structure, however

clusters starting from 𝐿𝑖 𝐹 become more stable 10 by adopting the bulk-like cuboid structure. Recent work by Ushirogata el al.46 focused on the growth/aggregation mechanism of the SEI components and suggested that the formation of the SEI layer does not take place at the interface of the anode and the electrolyte. Instead, the growth and coalescence of the SEI components was suggested to take place in the near-shore region of the electrode. This type of nucleation was also shown in recent reactive force-field based simulations.43 In this work, we unveil the first nucleation stages of some inorganic SEI layer components, namely LiF and Li2CO3, by employing a comprehensive structure prediction genetic algorithm USPEX

47–50

coupled with electronic structure calculations. Next, the resulting clusters of

different sizes adsorbed on a slab of fully lithiated graphite are used to explore the emergence of the near shore nucleation mechanism.46 This study reveals unreported low-energy clusters as well as intermediates that enable to map the nucleation and growth pathways of LiF and Li2CO3 clusters. Such analysis was followed by detailed investigation of the clusters stability 4   

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as well as their electrostatic, electronic and transport properties. We find that the isomerization of the (LiF)n=2-16 and (Li2CO3)

n=1-8

clusters leads to a progressive stabilization of the

aggregates.

Methods. We performed a systematic study of cluster structure prediction as implemented in the USPEX code interfaced with the Vienna Ab Initio Simulation Package (VASP) code 51–54. Genetic algorithms were firstly introduced in the 90th 55–58 proposing a revolutionary approach for structure prediction by exploring different possible arrangements of atoms and setting up “populations”. The USPEX code, developed by Oganov’s team in 2004, presented an improvement on the accuracy and the efficiency of previous genetic algorithms making possible the prediction of new crystals, surfaces, stable or meta-stable structures and molecules. 47–50

Starting from single atoms, the structure prediction method enables to sample a huge

configurational space allowing to assess the energetic competition between hundreds to thousands of cluster geometries without any bias caused by choosing predefined building blocks. Starting from single atom building blocks we modelled the formation of (LiF)n and (Li2CO3)n clusters up to n=16 and n=8 respectively reaching up to the formation of hexadecamer of LiF and octamer of Li2CO3. The algorithm generates hundreds to thousands of configurations for each cluster size, starting by a population of 25 individuals per generation. The genetic algorithm is subsequently used to produce the next generation either by random variation (10%) or from the retained structures from the previous generations using 80% heredity and 10% mutations (permutation and soft mutation) until convergence is reached. The resulting clusters are ranked according to their enthalpies. For each cluster size, analysis of the most stable structure as well as metastable cluster structures (within 200 meV/atom) is

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undertaken. This allows drawing possible scenarios of the cluster evolution, nucleation, and growth as a function of the number of isomers. To simulate the molecular system within VASP periodic boundary conditions scheme, clusters were isolated from their periodic images using a vacuum of 10 Å in the three-dimensional space. The geometric optimization of the clusters was performed using the GGA PerdewBurke-Ernzerhof (PBE) DFT functional

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as implemented in the plane-wave based program

VASP 51–54. DFT has been shown to be a good tool for describing the nucleation and growth mechanism 60. The projector augmented wave (PAW) pseudopotentials were used 61 while the Brillouin Zone was sampled by the Gamma point. The structures were fully relaxed using the conjugate-gradient algorithm until reaching 10-4 eV/Å convergence criterion. Subsequent investigation using PBE and HSE06 were performed on the most stable structures of different sizes using the Gaussian-09 package.62 For further investigations on electronic properties of the clusters, GENIP (Generalized Electron Nano-Interface Program) 63 was used to determine the electron conductance through the clusters. Such study is carried out by calculating the current-voltage (I-V) characteristics. GENIP, which combines the results of DFT calculations with the Green’s Function formalism, has been previously used to calculate the I-V characteristics of cobalt phthalocyanine complexes,64 oligoglycines,65 molecular biosensors,66 etc. Details for GENIP can be found in other works.63,67–70 For each cluster structure, additional molecular geometry optimization was undertaken using PBE and HSE06 71

functional and 6-311+G basis set 72. Then single point (SP) calculations were performed on

each extended molecule which consists of the cluster structure attached to gold electrodes (Au nanocontacts). The choice of gold electrodes is practically a standard in nanotechnology for experiments on single molecules. The SP calculations were done using B3PW91 hybrid exchange-correlation functional

73

and 6-31G(d) basis set for Li, F, C, O and LANL2DZ for

Au. Then an external voltage was applied to the clusters through the Au nanocontacts while

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the generated electron transfer between them is measured. The DOS used in GENIP for the gold nano-contacts was previously obtained from ab initio DFT calculations on a periodic system of the bulk contact material (gold) with the program CRYSTAL.74 The calculations were done for different cluster sizes of (LiF)n for n = 1-16, and (Li2CO3)n for n = 1-8, representing various thicknesses of the SEI layer.

Results and Discussions 1. Nucleation and growth of Lithium fluoride. The modeling of the first nucleation stage of the SEI layer to reveal the initial growth pathways of the LiF clusters has been undertaken. A large set of low-energy clusters has been predicted and identified using the USPEX code revealing the presence of several metastable configurations for each size. Figure 1 shows the crystal structure of different (LiF)n=2-16 clusters with their corresponding energies (E). The calculated energy (E) is defined as the total energy of the cluster divided by the number of atoms in the cluster. The comparison between the energies reported in Figure 1, clearly reveals that within the same cluster size, different metastable clusters coexist with energy differences ∆E< 0.2 eV/atom. Other higher energy configurations, not shown in Figure 1, are considered as intermediate structures resulting from the addition of LiF monomers which might be involved during the cluster growth and nucleation. Depending on the cluster size there is a clear competition between the ring-like and cuboid growth modes; for example, at n=4 the ring-like structure is more favorable than the cuboid by 60 meV, while this difference falls to 20 meV in the case of the n=8.

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Figure 1. Predicted crystal structures and energy difference per atom (E) relative to (LiF)2 for neutral (LiF)n=2-16 clusters. For each size, the most stable clusters are shown followed by metastable configurations higher in energy by ∆E< 0.2 eV/atom.

The results obtained for the stable structures of (LiF)n=2-8 are in agreement with those reported by Doll et al.12 with the exception of (LiF)8 where the ring-like structure is more favorable than the cuboid one. Interestingly, by monitoring larger clusters’ growth up to (LiF)16, the “cage-like” structure starts to emerge at n=12 competing strongly with the ring-like and cuboid-like growth modes. This cage-like growth mode contradicts the common conclusion from previous works 10 suggesting the stability of the stacked ring-structures.

1.1. Clusters formation energy. The clusters formation energy as a function of their size is evaluated by calculating the binding energy (Ebind) per atom using the following equation: 𝐸

𝑛𝐸 𝐴

𝑚𝐸 𝐵

𝐸 𝐴 𝐵

,       (Eq. 1) 

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Where 𝐸 is the energy of the free ions and 𝐸 𝐴 𝐵

is the total energy of the cluster. Figure

represents the variation of the binding energy Ebind as a function of the cluster size. The binding energy increases as function of the cluster size suggesting an enhanced stability during the growth from n = 2 to n = 16. The only exception is a slight energy decrease of 7 meV/atom noticed for (LiF)14 cluster possibly due to the instability of the “incomplete” cage. The binding energy increases by about 1 eV/atom when the cluster grows from n=2 to n=8, followed by further stabilization (energy increase of about 100 meV/atom) for larger n=8 to n=16 clusters.

Figure

As 1.2.

Clusters growth. We subsequently investigated the possible growth pathway of the

(LiF)n clusters by inspecting the lowest 20 configurations of each isomer resulting from the USPEX method. These metastable LiF isomers might co-exist alongside with the most stable geometries at battery operation temperatures, usually between 280 and 330 K. Figure illustrates a suggested (LiF)n growth pathway facilitated by some metastable “intermediates” that are shown to play a key role in the cascade reaction upon isomerization; these are labelled as 31, 32, 33, 41, 42, 61 and 62. The calculated energy difference per atom (E) relative to (LiF)2 9   

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for the bulk LiF crystal is shown as a demarcation line indicative that clusters would continue to aggregate and grow beyond (LiF)16 before reaching the bulk LiF energetic stability.

Figure

In

2.

Nucleation and growth of Lithium carbonate. Similarly, several low energy

(Li2CO3)n clusters have been predicted and the presence of metastable configurations has been revealed. Figure shows (Li2CO3)n clusters and their calculated total energy per atom (E), revealing the coexistence of metastable clusters for the same cluster size with an energy differences less than 0.2 eV/atom. As for the LiF clusters, the growth mode depends on the cluster size. From n=2 to n=4, the ring-like structures are found to be more favorable than the linear or the cage-like structures, while for bigger clusters, from n=5, the cage-like growth mode seems to be the most favorable one. By comparing the energy per atom values, reported in Figure , we observe a slight instability of the pentamer (n=5) with respect to the tetramer (n=4), while the hexamer (n=6) is found to be much less stable. For bigger clusters, in the case

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of the heptamer (n=7) and octamer (n=8), the configurations become more and more compact, leading to a better stability of the clusters.

Figure

2.1. 𝐸 𝐴 𝐵

Clusters formation energies. We applied 𝐸𝑏𝑖𝑛𝑑= ,

𝑛𝐸 𝐴

𝑚𝐸 𝐵

(Eq. 1) to calculate the binding energy per atom of the most stable Li2CO3 cluster

for each size and evaluated their relative stability. Figure represents the variation of Ebind as a function of the cluster size. Similarly with the results in Figure 2, the energy increase by 300 meV with the cluster size (from n=1 to n=4) indicates the stable growth of the Li2CO3 clusters. From n=4 to 6, the binding energy per atom slightly decreases by some meV. Nevertheless, a remarkable gain on stability is observed for the heptamer ((Li2CO3)7 and octamer (Li2CO3)8. The stability observed for (Li2CO3)4 and (Li2CO3)8 occurs because these isomers have a more compact configuration, resulting in a decrease of the surface energy of the cluster, when compared to the isomers with an elongated structure, such as (Li2CO3)5 and (Li2CO3)6 with a higher surface energy. The energy gap between the HOMO and LUMO of the Li2CO3 clusters

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shown in Figure S3 indicates the existence of a large bandgap of about 6.8 eV for all the cluster sizes.

Figure 5. Calculated binding energy per atom as a function of the size n of Li2CO3 clusters (from n=1 to n=8)

2.2.

Clusters growth. The possible growth pathway was investigated based on the different

metastable configurations of Li2CO3 clusters generated by USPEX code. As for LiF growth, some intermediates issued from isomerization of Li2CO3 unit (named 21, 22, 23, 31,and 32 clusters as shown in Figure ) are predicted and found to play a key role on the stabilization of

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the cluster and the transition from an isomer to another. Figure

illustrates a possible

isomerization pathway of Li2CO3 clusters from n=1 to n=8.

Figure 6. Suggested (Li2CO3)n=1-8 clusters growth pathway and energy profile, energy reference corresponds to the energy per atom of Li2CO3 monomer. Dotted demarcation line refers to the calculated Li2CO3 bulk energy/atom. Configurations labelled 21, 22, 23, 24, 31, 32 and 33 refer to metastable intermediates facilitating the isomerization.

The investigations of the different metastable configurations of LiF and Li2CO3 help the prediction of the possible growth mechanism of the SEI layer components. Both LiF and Li2CO3 seem to promote the formation of highly stable and compacted cage-like clusters. We make the assumption that transformations between clusters of the same number of atoms, and growth of clusters via adding more LiF/Li2CO3 monomers, are kinetically allowed. We also assume that the spontaneous coalescence is probably driven by a favorable interaction between the already formed clusters and the nascent monomers at the surface of the electrode. Hence, we propose a kinetically favorable cluster nucleation mechanism facilitated by the presence of metastable intermediate clusters driving the nucleation by monomer addition. An important

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question is, where do they grow? In Li-ion batteries both LiF and Li2CO3 SEI components should grow while exposed both to the electrolyte and to the electrode surface. Thus, one possibility is that the reaction takes place at the surface, and the fragments nucleate and adsorb at the surface. Another possibility is that reduction takes place via radicals 75 in “near-shore” locations of the liquid phase. This is also suggested by recent classical MD simulations with a reactive force field.43 This second hypothesis is aligned with the growth of clusters as described in this and the previous section. Many factors, such as applied electric field, electrolyte composition, electrode composition and structure may favor one or another form of growth. Garofalini 76 highlighted the importance of the orientation of the surface on the growth mode of LiF blocks  at finite temperature. It appears that for a specific surface orientation, an amorphous structure could form upon the reaction between Li+ and FeF2 followed by the LiF crystallization. While we cannot rule out the possibility of forming amorphous LiF clusters near the surface of the electrode, the near shore growth mode by monomer addition gives a picture that amorphous LiF clusters are too high in energy to compete with crystallized clusters at finite temperature. Nevertheless, amorphous clusters have emerged as the most favorable structure at n=6 for Li2CO3 as could be clearly seen in figure 4. One could think about an energetic competition between the SEI components growth and evolution in the near shore region as described above versus another growth mode where the first SEI monomer clusters deposit and adsorb on the surface during the early growth stages agglomerating upon further electrolyte decomposition at the surface. Hence, the following section inspects the reactivity of some clusters and their ability to grow in the presence of active sites by studying their electrostatic potential surfaces and leakage current upon the application of an electrical field bias mimicking the battery charge/discharge processes. 3. Electrostatic and electronic properties of SEI components

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3.1. Electrostatic potential surfaces. Electrostatic potential surfaces (EPS) provide information about the charge distribution of a molecule. Thus, a low electrostatic potential (the most negative value) indicates the relative electron abundance and vice-versa. The main purposes of determining the EPS is to figure out the reactive sites of a molecule and then to be able to predict the growth mechanism and even the most reactive surface orientation of the cluster to be favorably adsorbed on the electrode surface or prone to attract other monomers or clusters thus favoring their nucleation.77

Figure 7. Calculated electrostatic potential surfaces (EPS) of some LiF and Li2CO3 clusters showing the most reactive sites. Green, gray, brown and red spheres represent Li, F, C and O atoms respectively. Only the negative EP isosurfaces are presented and generated with isovalue=0.08 a.u.

Figure shows a calculated three-dimensional electrostatic potential of open cage LiF and Li2CO3 clusters of various sizes. We considered only the negative electrostatic potential as it corresponds to the nucleophilic sites of the system 78. The size of the isosurface reflects the electron population and emphasizes the possible reactive sites prone to electrophilic attacks. For an isovalue=0.08 a.u. it is clear that the electrostatic potential isosurfaces shrink as the cluster size increases. This suggests a reduced reactivity of the clusters as they grow larger. Yet, the selected large open-cage structures such as (LiF)14 and (Li2CO3)5 display a non negligible number of nucleophilic sites favoring further growth in contact with SEI monomers 15   

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or clusters resulting from the electrolyte and salt decomposition at the surface. Further investigation of the reactivity and adsorption of these clusters on the graphite surfaces is discussed in a later section. Such electrophilic sites and the corresponding nucleophilic sites (not shown) should be able to attract radical (or ion radicals) species which may allow growth continuation in near-shore regions. Moreover, the reactive sites may also be able to attract ions different than those in the cluster and allow growth of an interface between two different species (example LiF and Li2CO3). This possibility will be examined in future work. 3.2. Electronic transport. As mentioned above, one of the major roles of an efficient SEI layer is to act as a passivation layer able to provide a barrier for electron leakage from the electrode surface thus slowing down any further electrolyte decomposition at the interface. Hence there is a strong correlation between the energetics of cluster growth determined above and the expected attenuation in electronic transport properties, both of which contribute to define the SEI layer growth. To determine the LiF and Li2CO3 electron transfer properties as function of their cluster sizes, an external voltage is applied and the corresponding leakage current is determined. This analysis helps to characterize the possibility of electron leakage through any of these clusters and the critical cluster size where such electron transfer might damp out. The simulated chemical structures are illustrated in Figure S4 and S5. It is clear from Figures S4 and S5 that the leakage current reduces dramatically as the cluster size increases, for both LiF and Li2CO3; although larger currents are observed for LiF clusters of the same size. Interestingly, Qi, el al. 21

showing that for the same thickness of ~2 nm , an electronic leakage is observed with Li2CO3,

contrarily to LiF which totally blocks the electrons, in crystalline defect-free structure 79. This disagreement with the present work is probably due to the structural difference of our stable close shell SEI blocks compared to bulk-like structures.

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1

2

2

4

3

6 5

12

I (μA)

(LiF)n clusters’ I-V

8 14

1

10 16

Voltage(V) 0 -6

-4

-2

0

2

4

6

-1

-2 (a) 1

1

3 4

(Li2CO3)n clusters’ I-V 2

7 0.5 I (μA)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Voltage(V)

6

5 8 0

-4

-3

-2

-1

0

1

2

3

4

-0.5

-1 (b) 17   

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Figure 8. Current-voltage characteristics as function of SEI clusters sizes: (a) (LiF)n=1-16 (b) (Li2CO3)n=1-8 attached to two gold (Au) electrodes.

This is very evident in Figure , where a considerable electron transfer is observed during the initial stages of SEI formation (in the case of (LiF)2 and Li2CO3). However a significant drop of the current is observed as the clusters grow progressively bigger in good agreement with recent work by Seminario et al.80. Nevertheless, Figures S4 and S5 show that leakage currents remain non-negligible (between 0.5-1 µA at 4V) even for the largest clusters confirming the conclusion from the electrostatic potential about the non-negligible reactivity of the clusters and supporting their ability to grow beyond the cluster sizes investigated in the present study. 4. Adsorption of LiF clusters The analysis of current leakage in the previous section assumes the proximity of the electrode. Here we investigate the energetics of SEI cluster adsorption on the electrode surface that corresponds to the SEI surface growth. We considered graphitic anodes with distinct reactivity mainly based on a model of 1) fully prelithiated graphite with H terminations to passivate the edge dangling bonds 2) fully prelithiated graphite without H-termination. After a full relaxation of both models, the lithium ions are found to diffuse towards the surface while some C-C bond reconstruction occurs. The initial configuration of the adsorbed clusters on both surfaces was based on the “adsorption locator” module, as implemented in Materials studio software.

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   Figure 9. Fully prelithiated graphite slab  with H termination (left) selected open‐cage Gr‐(LiF)n clusters adsorbed on  graphite slabs. The color code is as follows: green, light purple, gray and white spheres represent Li, F, C and H atoms  respectively. 

The adsorption of all the stable LiF clusters for each size (n=2-16) was undertaken on top of fully prelithiated graphite slab models with and without H termination. Figure 9 illustrates only few selected cases of the adsorption of (LiF)5, (LiF)10, (LiF)14 and (LiF)16 on the surface of the H termination graphitic anode, featuring the formation of new Li-F bonds between the clusters and the Li atoms on the slab surface. The length of these formed Li-F bonds is almost the same for all the cases (~1.8 Å). The adsorption energy is calculated using the following equation: 𝐸 Where 𝐸

𝐸

𝐸

𝐸

(Eq. 2)

is the total energy of the full system (Graphite + cluster), 𝐸

and 𝐸

are the

total energy of the separated graphite and cluster, respectively. Figure 10 shows the evolution of the adsorption energy as a function of the cluster size adsorbed on both anode models. The negative values of the energy are indicative of chemisorption of the clusters however significant differences are observed depending on the anode model:

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For model 1, i.e. H-passivated substrate, adsorption energies vary between -1.7 and -2.9 eV giving rise to an oscillatory energy profile. On average such profile has a decreasing trend indicative of the weak stability of the adsorbed clusters as they grow larger on passivated surfaces. This suggests that a H-passivated graphite substrate does not offer a sufficiently large number of attractive sites to sustain the growth. In contrast, on model 2 (the non-passivated substrate) the adsorption energy strengths increase monotonically from -3 to -3.8 eV indicative of an increased stability of the chemisorbed clusters. The clear difference observed between both adsorption energy profiles as a function of the cluster size indicates that chemisorption profile is strongly dependent on the reactivity of the selected graphite surface.

   Figure 10 Calculated adsorption energy of the stable LiF clusters of each size (n=2‐16) adsorbed on the surface slab model 1  : fully lithiated graphite with H termination (black ) and model2: without H termination (red) 

The adsorption on a non-passivated graphite shows that the larger is the cluster, the more strongly it adsorbs to the surface. However, the adsorption of LiF clusters on H-terminated substrates is found to be less conclusive due its oscillating energy profile as function of the cluster size. Interestingly, the open-cage clusters such as (LiF)2, (LiF)5, (LiF)10 (LiF)14 seem to 20   

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be more strongly absorbed than their closed structure counterparts probably because of their larger number of active sites able to interact with the H-terminated surface slab. Adsorption on oxidized or partially oxidized graphite surfaces. We also investigated the interfacial structure and electrostatic potential at the interface between bare and oxidized LiC6 slabs and SEI blocks by DFT calculations. The graphite partially oxidized models have the bottom surface edges saturated with H atoms, and the top surface saturated with oxygen atoms. The fully oxidized model has oxygen atoms saturating the top and bottom edges. The SEI model is built by sequentially adding SEI components ( Li2CO3 monomers or LiF pairs) to the slab’s surface mimicking a) the layer-by-layer and b) 3D growth modes. These modes of growth assume that monomers or pairs of the main SEI components are formed near or at the surface and sequentially nucleate then adsorb on the surface. Contrary to the SEI clusters growth mode on graphite slabs investigated above, the layer-bylayer and 3D growth modes lead to the formation of aggregates of monomers that are only stable in conjunction with the surface slab. Hence, we evaluate the adhesion of the SEI layer components among each other and to the slab by computing the binding energy using the following equation: 𝐸 Where 𝐸

𝐸

𝐸

𝑛∗ 𝐸

/𝑛

(Eq. 4)

is the total energy of the full system (anode + monomers), 𝐸

and 𝐸

are the total energy of the separated graphite and one SEI component ( Li2CO3 monomers or LiF pairs), respectively. This calculated binding energy defines at the same time the cohesion among the SEI components in addition to their adsorption energy (adhesion) to the surface. Our simulations for the LiF growth reveal the following interesting features: a) When LiF pairs were added in layer by layer growth mode, the final optimized structure shows that a defective overlayer forms on top of the oxidized graphite surface (Figure S6a), b) The binding energy 21   

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strength increases with each LiF pair addition the layer by layer mode approaches a plateau at -2.5 eV per LiF pair (Figure S7a). On the other hand, the binding energy of a 3D growth mode of defective LiF cluster (see Figure S6b) constructed from LiF pairs also reaches a plateau at 2.5 eV (Figure S7b). When the LiC6 slab is not passivated with hydrogen atoms (fully oxidized model), the binding energy per LiF pair shows a slightly stronger interaction when compared to the partially-oxidized model (-2.7 eV vs. -2.5 eV). It is interesting that the limiting binding energy as the cluster size grows bigger is independent of the mode of growth (planar vs. 3D structures). However, similar to the case of the (LiF)n clusters on H-passivated graphite discussed earlier (Figure 10), the interaction between the (LiF)n clusters and the graphite’s surface becomes weaker as the size of the cluster grows larger. In addition, we compared the interfacial structure between a fully/partially oxidized LiC6 slab and an SEI block of 15 Li2CO3 monomers sequentially placed on top of the slab (Figure S8). In both models, Li ions from LiC6 tend to diffuse to the graphite’s surface. The Li2CO3 monomers are closer to the graphite’s edge in the partially oxidized model. The planar average electrostatic profile shows that the electrostatic build up at the partially oxidized model is approximately 2 eV smaller than in the fully oxidized model. Several interesting observations are worth noting: a) The majority of Li2CO3 monomers adsorb with a flat orientation in the fully oxidized model while a mixed orientation is observed in the partially oxidized model, b) Even though Li-ions move from the bulk to the edge region, they do not diffuse into the SEI block (at least without an applied electric field) and do not appear to induce decomposition of the Li2CO3 monomers. Furthermore, the binding energy per monomer for the partially oxidized model shows that the energies of the adsorbed monomer fall between -4.06 eV and -2.78 eV (Figure S9). That is, as the SEI block grows, the weaker adsorbed the monomer is. We computed the binding energy per monomer as a function of Li content, and we found that the binding strength varies,

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in the majority of the cases the monomer-surface interaction strength decreases as the Li content increases. In most cases, the binding energies approach a plateau as the layer is being completed and a 2nd monomer layer starts to form on the slab. An explanation for this change in the interaction strength is the increased monomer-monomer interaction or cohesiveness that competes with the monomer-surface interactions. This adsorbate-surface and adsorbateadsorbate interaction energy trends were also shown in a recent DFT-based simulation of the oligomer-Li13Si4 interaction.75 Overall, the calculations for the Li2CO3 monomers show that the monomers adsorb strong enough to form an overlayer on top of the graphite surface. However, as the SEI block grows, a less compact film may grow due to the weaker monomersurface interaction. A general trend of energy drop is observed concluding a weak interaction with the bigger structures. This could be explained, as the SEI block grows, a less compact film may grow due to the weaker monomer-surface interaction, probably due to the increase of a competitive monomer-monomer interaction.

Conclusions. Our detailed and comprehensive investigation of the growth of two main inorganic components of the SEI layer namely LiF and Li2CO3 clusters helps elucidating their first nucleation/isomerization steps. Using a genetic algorithm-based procedure (USPEX), we identified several metastable configurations that can play an essential role for the nucleation and cluster growth and the most stable configurations for each isomer size. Small size LiF clusters (up to n=8) have low-lying minima with ring-like structure, in agreement with previously reported calculations, while larger isomers stabilize with cage-like structure. The proposed isomerization pathway of Li2CO3 clusters reveals the presence of some values of n for which the cluster is especially stable (n = 4 and n = 8), corresponding to their magic numbers. 23   

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Analyses of the electrostatic properties of the studied clusters identifies the reactive sites and regions of negative electrostatic potential isosurfaces give insights on electronic population or depletion upon growth. This enabled to pinpoint the most favorable atomic sites that are prone to 1) electrophilic attack leading to further isomerization resulting into near-shore cluster growth, 2) highly reactive atomic sites favoring the reaction and adsorption on electrodes such as graphite, 3) mixed clusters may also be formed at the highly active sites by attracting ions (or radical ions) of different species. On the other hand, the electronic conductance (currentvoltage characteristics) as function of the clusters size showed considerable electron transfer during the initial stages of SEI formation followed by a significant drop to non-negligible values of the current as the clusters grow progressively. Finally, examining the adsorption of the SEI components (LiF and Li2CO3) on the surface of various terminations graphitic anodes allows to investigate the competition among SEI clusterstacking, layer-by-layer growth, and near shore SEI layer cluster aggregation growth modes. It is concluded that clusters may grow in near-shore regions provided that other electron carriers (example radical anions) may be able to continue the reduction of additional electrolyte molecules in the proximity of the clusters. However, small fragments (example LiF monomers) resulting from electrolyte decomposition can be generated at the surface and migrate toward the nascent clusters in the near-shore region. Since most of the literature suggest the inorganic phases to be located at the “inner” part of the SEI (close to the electrode surface), then there appears to be a limit for the cluster size in near-shore regions that could be followed by migration to the near-surface inner SEI layer. Thus, we conclude that the most likely scenario is a mixed mode: small clusters may be formed in near shore locations and migrate toward the surface during cycling, while nucleation and growth at the surface may also exist. This is supported by recent molecular dynamics simulations43 including the electrolyte that have shown evidence of LiF and other clusters formation due to the combined effect of Li metal

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dissolution and migration into the electrolyte phase coupled to anion decomposition. LiF clusters were detected to form in “near shore locations” and presumably can migrate toward the surface as the mosaic phase is forming. Thus the presence of the electrolyte (solvent and salt) are crucial for the proposed events.

Moreover, this mixed mode of growth is consistent with a heterogeneous “mosaic” SEI picture suggested in the literature. On the other hand, our study indicates that the graphite surface termination i.e. reactivity has an important impact on the growth mode of the interphase and its interaction strength. The adsorption of the LiF clusters on a non-passivated anode seems to be more favorable compared to the adsorption on the less reactive H-terminated anode. On the other hand, for the layer- by-layer growth mode on fully/partially oxidized slab, the investigation reveals an increase on the binding energy with each LiF pair addition approaching a plateau. Comparison of the various SEI growth modes investigated demonstrates a strong dependence on the degree of lithiation of the electrode and surface termination states. Some aspects still need to be further elucidated, for example what is the effect of the applied field especially in the cluster migration toward the surface, and in the fragments migration toward the clusters, where each of these migration events may occur under different cycling stages (charge or discharge).

Supporting Information Series of figures detailing additional energetic and electronic properties of the LiF and Li2CO3 clusters. Growth mode of defective clusters on oxidized or partially oxidized graphite surfaces. Acknowledgment. This paper was possible by grant NPRP 7-162-2-077 from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are

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solely the responsibility of the authors. Computational resources are provided by research computing at Texas A&M, University at Qatar and the TAMU HPRC at College Station.

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