# Detailed characterization of solid particles emitted during the thermal runaway of large-scale Lithium-ion cells

Thomas Grossetête, Sébastien Dubourg, Thibaut Rochard, Daniel Marteau, Alain Bengaouer

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Thomas Grossetête, Sébastien Dubourg, Thibaut Rochard, Daniel Marteau, Alain Bengaouer. Detailed characterization of solid particles emitted during the thermal runaway of large-scale Lithium-ion cells. Journal of Energy Storage, 2025, 124, pp.116666. 10.1016/j.est.2025.116666. cea-05068163

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Submitted on 14 May 2025

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# Detailed characterization of solid particles emitted during the thermal runaway of large-scale Lithium-ion cells

Grossetete Th.¹, Dubourg S.², Rochard T.², Marteau D.², Bengaouer A.¹,*

¹ Université Grenoble Alpes, CEA, LITEN, DEHT, F-38000 Grenoble, France

² CEA, DAM, Le Ripault, F-37260 Monts, France

*Corresponding author email: alain.bengaouer@cea.fr

## Abstract

Lithium-ion battery (LIB) technology provides high energy density, long cycle life and low self-discharge rates, thus it has become a popular choice for many applications. Despite this success, the safety of LIBs remains a major concern due to the potential risk of thermal runaway (TR), leading to the ejection of battery materials. In this work, the particle emissions, vented gas volume and energy released during the TR of a large prismatic lithium-ion NMC rich cell are characterized. Among the total energy released during thermal runaway (1.2 times the electrical energy stored in the cell), 78% is contained in the ejecta, which represent only 38% of the total mass of the initial cell. After thermal runaway, the particles were collected and analyzed. Sieving revealed that the majority of the particles were smaller than 75µm. The elemental quantifications conducted on each subsample revealed a decrease in the proportion of cathodic transition metals and an increase in the proportion of carbon, primarily graphite, as a function of particle size. Furthermore, stoichiometries of nickel, cobalt, and manganese remained constant across all the samples, indicating that TR did not alter the NMC arrangement. Particle density decreased with size, and the specific surface areas also highlighted the coarse and porous nature of the structures. The granulometry measurements enabled quantifying the degree of particle agglomeration relative to particle size. Finally, the analysis revealed that the agglomerates were mainly composed of three families of fine particles (NMC oxides and graphite carbon) which adhered to larger particles during TR.

## 1. Introduction

Increased environmental awareness has led to a shift from traditional gasoline-powered vehicles to electric vehicles as a way to reduce carbon emissions in transportation. As a result, there has been an exponential increase in the number of battery-powered electric vehicles and plug-in hybrid electric vehicles. According to the International Energy Agency, the total number of electric cars sold in the world rose from three million in 2020, to fourteen million in 2024 and is expected to reach more than forty million by the end of 2030 ¹. Thanks to its high energy density, long cycle life and low self-discharge rate, Lithium-ion battery (LIB) technology has become a popular choice for many applications other than electric mobility, ranging from consumer electronics with billions of smartphones with an embedded energy of a few kilojoules to large battery energy storage systems with storage capacities of billions of kilojoules.

However, despite this commercial success, the safety of Lithium-ion batteries remains a major concern due to the potential risk of thermal runaway, fire, and explosion. Thermal runaway (TR) may occur due to electrical, mechanical or thermal abuse of the cell. The result is a chain of exothermic decomposition reactions of the battery materials, leading to a rapid rise of the temperature and pressure in the cell. This pressure increase leads to the opening of the cell safety valve or to the cell's rupture, the release of gas and particles, and possible jet fire². Thermal runaway may propagate to the surrounding cells and pack modules if protection functions such as compartmentation, detection and suppression, fail to stop the propagation³. Ultimately, the
unburnt vent gases could mix with ambient air to form a flammable gas or vapor cloud. Obviously, safety concerns increase as the battery market moves toward larger batteries, higher volumetric energy density and higher gravimetric energy density. Therefore, the effective thermal management of Lithium-ion batteries is crucial to ensure their safe and reliable operation and requires deeper understanding of TR.

At the material scale, understanding of battery cells has evolved from the earlier DSC studies of Richard and Dahn on SEI degradation and anode-electrolyte reaction⁴ to more detailed mechanism descriptions of cell energy release⁵. At the cell scale, simulation models based on these mechanisms are now able to describe the heat release and temperature evolution of the cell during thermal runaway⁶. However, these models do not provide a mechanistic description of the vented material, i.e. gas and particle release, so an experimental approach is still needed.

Experimentally, the thermal runaway of lithium-ion cells is often characterized by ignition time, surface temperature, peak heat release rate (PHRR), total heat release (THR), mass loss, gas volume and flame size⁷. Solid particles not only significantly account for mass loss but also for heat transfer, as they can impact neighboring cells or structures, and react with the surrounding air. Furthermore emitted particles will modify the flammability characteristics and ignition of the gases released⁸.

Characterizing the physical and chemical properties of the particles is thus of prime importance to understand and mitigate TR propagation and recent research has revealed important characteristics of these particles. For a 50-Ah commercial prismatic NMC622 cell at SoC 100%, Zhang et al.⁹,¹⁰ found that emissions of particles with a size below 0.5 mm accounted for 90% of the particle mass, with D90, D50 and D10 of 390 µm, 195 µm and 19 µm, respectively. The total mass balance of ejected material showed that dust (PM 10) and high boiling point vent gases (>90 °C) accounted for 25%wt., permanent gases accounted for 33% wt. and solid particles 17%. Wang et al.¹¹, quantified five metals (Al, Cu, Ni, Co, and Mn) on five particle samples using inductively coupled plasma mass spectrometry (ICP-MS), revealing that nickel and aluminum exhibited higher proportions compared to the others. The elemental distribution of these samples including other non-metallic elements (C, O, F, Si, P, and S) were also measured by scanning electron microscope and an electronic differential system (SEM-EDS), but this methodology involves local measurements and is not representative of the overall sample. Wang et al.⁹,¹², showed that 88%–90% of the total particles emitted by NMC prismatic cells (NMC622, NMC 523 and NMC 111) had a size less than or equal to 0.85 mm. The main phases identified by XRD analysis were graphite and LiF, followed by Ni/Co, Li₂CO₃, NiO, MnO, and LiNiO₂ in lower quantities. Li et al.¹³ conducted a literature review and summarized the properties of particles released upon the TR of LIBs (morphology, mass, size, thermal stability, chemical composition, spread and deposition, temperature, and eruption distance).

This study aimed to characterize particle emissions, vented gas volume and energy release during the TR of a large prismatic lithium-ion NMC rich cell. To achieve this goal, the thermal runaway of the cell at SoC 100% was triggered by overheating in a thermally insulated closed vessel under vacuum. Temperature and pressure were monitored for energy and gas volume assessment and particles were collected after TR. The mass and energy balance of the cell after TR is revealed as are the mass and size distribution, elemental and phase composition of the particles emitted.
## 2. Experimental settings

### 2.1. Battery sample

A commercial prismatic Li-ion cell with a rated capacity of 144 Ah was used. Table 1 presents the basic cell parameters.

<table><caption>Table 1: Basic parameters of the commercial cell.</caption><thead><tr><td>Parameters</td><td>Specifications</td></tr></thead><tbody><tr><td>Cell mass [kg]</td><td>2.011</td></tr><tr><td>Nominal capacity [Ah]</td><td>144</td></tr><tr><td>Cathode active material</td><td>Li(Ni<sub>x</sub>Mn<sub>y</sub>Co<sub>1-x-y</sub>)O<sub>2</sub></td></tr><tr><td>Anode active material</td><td>Graphite</td></tr><tr><td>Cathode current collector</td><td>Aluminum foil</td></tr><tr><td>Anode current collector</td><td>Copper foil</td></tr><tr><td>Shell material</td><td>Aluminum alloy</td></tr></tbody></table>

### 2.2. Equipment used to initiate thermal runaway

The cell is enclosed with two copper plates to homogenize the measured temperature and an electric heating element is placed against one of them. Insulation plates surround the assembly and compression plates hold the system together. The cell-holder system is then inserted into the 240 L test vessel with the cell vent oriented upward (Figure 1). Temperature measurement is ensured by 22 type K thermocouples of 1 mm diameter, four are located on the copper plates, one on the heating plate, sixteen on the outer wall of the vessel and four type K thermocouples of 0.075 mm diameter located inside the test vessel. The vessel outer wall is thermally insulated by a thermal blanket, and the internal pressure is measured by one pressure sensor.

<figure><img src="image_2.png" /><figcaption>Figure 1 Test set-up: Instrumented cell during assembly (left), cell-holder positioned in the test vessel (right).</figcaption></figure>

### 2.3. Experimental method

Factory-fresh cell were used, having neither undergone preliminary charge/discharge cycles nor been stored under conditions other than ambient temperature. The cell was charged to a potential of 4.3 V vs. Li/Li+, equivalent to a fully charged state (100% SOC). The pressure vessel was sealed
and the air in the enclosure evacuated by a vacuum pump until an absolute pressure of 10 mbar was reached. To trigger thermal runaway, the cell was heated using a heating plate with a constant power input, without temperature regulation. A power of 400 W was applied for the first 1020 seconds after the onset of thermal abuse, then increased to 700 W until thermal runaway was triggered. After the cell TR, the heater was turned off and the vessel cooled naturally. Twenty-four hours after TR, the vessel was opened and the particles were collected through a 3 µm filter connected to a vacuum pump. The particles were then divided by passing them through 5 sieves of sizes 75 µm, 150 µm, 500 µm, 1000 µm and 2500 µm. In order to characterize these samples, elemental quantification was conducted using both a CHNOS analyzer (Elementar Analysensyteme, Unicube) and an inductively coupled plasma optical emission spectrometer (Agilent Technologies Inc., Agilent 725 ICP-OES). Their densities and specific surface areas were measured using a pycnometer (Micrometrics Instrument Corporation, AccuPyc II 1340) and a Brunauer-Emmertt-Teller analyzer (Micromeritics Instrument Corporation, TriStar II 3020 BET) respectively. The particle size distributions were evaluated using a laser diffraction particle size analyzer (Malvern Panalytical, Hydro2000MU). Finally, SEM-EDS was used to analyze the sample of particles smaller than 75 µm (Carl Zeiss, Sigma 300 Gemini 1).

### 3. Results and discussion

In the following section, the thermodynamic characteristics of thermal runaway will be compared to those reported in the reference study by Hoelle et al.<sup>14</sup>, which investigates 86 cells, primarily NMC 622, with varying capacities.

#### 3.1. Thermal runaway

TR was observed when the heating plate temperature reached 304.4°C, at which time the average temperature of the hot copper plate was 290.9°C whereas the average temperature of the cold copper plate was as low as 93.1°C, reflecting a strong temperature gradient within the cell. At TR, the average temperature of the hot copper plate increased by 200°C in 35 s. Due to gas and particle ejections the average temperature of the inner vessel rose from 22.5 to 303.2°C in 8.5 s before heat exchanges with the vessel walls stabilized the internal temperature at 49°C. Consequently, the vessel temperature increased from 22.5 to ca. 37°C within a few seconds and then rose slowly due to heat exchanges with the cell body and copper plates (Figure 2).
<figure><img src="image_3.png" /><figcaption>Figure 2: Average temperature evolution of hot copper plate, cold copper plate, heating plate, inner vessel and outer vessel wall during TR.</figcaption></figure>

The maximum temperature was reached 10 s after TR for all the inner vessel thermocouples whereas the pressure increased until 20 s after TR and then decreased and stabilized at 1.1 bar (Figure 3). The amount of gas produced, evaluated assuming the ideal gas law based on the inner vessel temperature, pressure and a vessel volume of 0.24 m³, showed a continuous increase during approximately 50 s and then became constant (Figure 3).

<figure><img src="image_4.png" /><figcaption>Figure 3: Inner vessel average temperature, pressure, and calculated number of moles during TR</figcaption></figure>

## 3.2. Mass balance

The cell initial mass was 2.011 kg, after thermal runaway the cell mass was 1.128 kg and the particle mass collected was 0.516 kg. Assuming a molar mass of 25.8 g.mol⁻¹ (corresponding to a gas composition of CO₂ 41.2%, CO 13%, H₂ 30.8%, C₂H₄ 8.2% and CH₄ 6.8% as obtained by Golubkov et al.
for a NMC/Graphite cell¹⁵) the total gas mass was 0.248 kg. The non-recovered mass was 0.119 kg, so the mass error represents only 6% of the total initial mass. The mass balance is compared to the average trend reported in the reference study¹⁴, normalized to a cell with an equivalent capacity of 144 Ah, and an initial mass of 2.011 kg. (Table 2).

<table><caption>Table 2: Comparison of the mass balance after TR with the average trend reported by Hoelle et al.14, normalized to a cell with an equivalent capacity of 144 Ah with an initial mass of 2.011 kg.</caption><thead><tr><th rowspan="2"></th><th colspan="2">Mass (kg)</th><th colspan="2">Mass (%)</th></tr><tr><th>This study</th><th>Estimated from Hoelle et al.<sup>14</sup></th><th>This study</th><th>Estimated from Hoelle et al.<sup>14</sup></th></tr></thead><tbody><tr><td>Initial cell</td><td>2.011</td><td>2.011</td><td>100</td><td>100</td></tr><tr><td>Final cell mass</td><td>1.128</td><td>0.996</td><td>56</td><td>49.5</td></tr><tr><td>Cell mass loss</td><td>0.882</td><td>1.015</td><td>44</td><td>50.5</td></tr><tr><td>Particles</td><td>0.516</td><td>0.721</td><td>26</td><td>35.8</td></tr><tr><td>Estimated gas mass</td><td>0.248</td><td>0.294</td><td>12</td><td>14.6</td></tr><tr><td>Unrecovered mass</td><td>0.119</td><td>0</td><td>6</td><td>0</td></tr></tbody></table>

The mass loss of the studied cell is 6.5% lower than the trend reported in the reference study, yet remains within the same order of magnitude. Unlike Hoelle et al.¹⁴, who do not explicitly report the final mass of the cell, we have quantified the unrecovered material in the mass balance. This missing mass can reasonably be attributed to particles that were not collected, likely due to agglomeration on the chamber walls, cables, or thermocouples. By re-evaluating the mass of solid ejecta during thermal runaway, the fraction of vented particles is estimated at 31.6%, while gaseous emissions account for 12% (compared to 35.8% and 14.6%, respectively, in the reference study). These results align well with the trends reported by Hoelle et al.¹⁴

### 3.3. Energy balance

After TR, the electrical heater was shut-off, so no heat was added to the system. As the vessel was sealed and thermally insulated, the system only received heat from the electric heater. Considering the different components of the set-up separately we can express the thermal runaway energy $\Delta U_{TR}$ as:

$$|\Delta U_{TR}| = \Delta U_{cell+plates} + \Delta U_{vessel} + \Delta U_{gas} \quad (1)$$

For each solid component (cell+plate and vessel), the internal energy variation $\Delta U$ is calculated based on each temperature $T_k$ and the associated mass $m_k$ and heat capacity $C_{pk}$.

$$\Delta U = \sum_k m_k C_{pk} (T_k - T_0) \quad (2)$$

For the gas, the internal energy is evaluated assuming an ideal gas behavior.

$$\Delta U_{gas} = C_v PV/R \quad (3)$$

Where P is the vessel pressure, V the vessel pressure, R the ideal gas constant, and $C_v$ the gas heat capacity at constant volume, calculated assuming the same composition as for the gas mass.

For the first time, this experimental setup enables both the calculation of the total energy released and the partitioning of the contributions from the different transport vectors. According to Equation (1), the total TR energy includes the contribution from the cell and plates, the vessel, and the gas. 400 s after TR, the energy of the cell and plates reaches a maximum of 465 kJ whereas gas and particle
ejection raise the vessel's energy to 1629 kJ. Thus, 78% of the energy is contained in the ejecta, which represent only 38% of the total mass of the initial cell (Table 2). Total TR energy reaches 2260 kJ 1500 s after TR (15.7 kJ/Ah) and then decreases due to heat losses (Figure 4). Referring to the electrical energy at TR of 1865 kJ, an energy factor $\eta_E \approx 1.21$ is estimated.

<figure><img src="image_5.png" /><figcaption>Figure 4: Thermal runaway energy distribution</figcaption></figure>

## 3.4. Particle characterization

### 3.4.1. Mass distribution

Following thermal runaway, all the particles were collected by aspiration and subsequently sieved to obtain six samples of different particle sizes (0–75 µm, 75–150 µm, 150–500 µm, 500–1000 µm, 1000–2500 µm, and > 2500 µm). This approach enabled us to determine the mass distribution of particles based on their size (Table 3). Figure 5 displays photographs of the particles composing the six different samples.
<figure><img src="image_6.png" /><figcaption>Figure 5: Photograph of the six samples obtained after sieving.</figcaption></figure>

<table><caption>Table 3: Mass and mass fraction distribution of the samples.</caption><thead><tr><td>Sample</td><td>Mass (g)</td><td>Mass fraction (% wt)</td></tr></thead><tbody><tr><td>&lt; 75 µm</td><td>241.6</td><td>65.47</td></tr><tr><td>75 – 150 µm</td><td>53.0</td><td>14.36</td></tr><tr><td>150 – 500 µm</td><td>54.2</td><td>14.69</td></tr><tr><td>500 – 1000 µm</td><td>6.6</td><td>1.79</td></tr><tr><td>1000 – 2500 µm</td><td>7.4</td><td>2.01</td></tr><tr><td>&gt; 2500 µm</td><td>6.2</td><td>1.68</td></tr></tbody></table>
As shown in Table 3, samples with a diameter <75 µm represent more than 65% wt. of the particles. In the subsequent sections of the article, physicochemical characterizations are performed exclusively on the three samples: 0–75 µm, 75–150 µm and 150–500 µm. This decision was taken due to two main factors. Firstly, the sub-samples collected for the measurements were not representative of the initial population for larger particle size samples due to their significant heterogeneity. Secondly, the three samples selected for analysis represented 94.5% wt. of the total ejected particles from the cell.

### 3.4.2. Elemental quantification (CHNOS and ICP-OES)

The elemental mass balance for each sample is reported in Figure 6.a. The total mass fractions vary between 87.60 ± 3.73 %wt. for the sample < 75 µm, and 101.16 ± 4.45 %wt. for the sample of 150-500 µm, indicating that the majority of the sample compounds were identified.

<figure><img src="image_7.png" /><figcaption>Figure 6: Total elemental mass fraction per sample (6.a) and evolution of the elemental mass proportion in function of particle size (6.b).</figcaption></figure>

The mass proportions shown in Figure 6.a are rearranged by element in Figure 6.b in order to analyze how the elemental ratios change with varying particle sizes. Carbon and hydrogen were measured using CHNOS, while other elements were measured using ICP-OES. In contrast to the quantifications performed with SEM-EDS, this methodology does not involve local measurements but instead provides a representation of the overall sample.

Among the notable elemental trends, it is interesting to observe that as the particle size increases, the proportion of cathodic transition metals (nickel, cobalt, and manganese) decreases. The trend in molar proportions between these three transition metals is also noteworthy. By denoting %wt$_E^i$ (%) the mass fraction of element E in sample i, $m^i$ (g) the mass of sample i, and $M_E$ (g·mol⁻¹) the molar mass of element E, the quantity $n_E^i$ (mol) of element E in sample i is calculated using equation (4):

$$n_E^i = \frac{\%wt_E^i \cdot m^i}{100 \cdot M_E} \qquad (4)$$

where (E = Ni, Mn or Co | i = < 75 µm, 75 – 150 µm or 150 – 500 µm | $M_{Ni}$ = 58.69 g·mol⁻¹, $M_{Mn}$ = 54.94 g·mol⁻¹, $M_{Co}$ = 58.93 g·mol⁻¹).

The molar fraction $x_E^i$ of element E in sample i in the total quantity of the three transition metals studied is calculated using equation (5). Table 4 summarizes the evolution of these molar fractions for the samples studied.
$$x_E^i = \frac{n_E^i}{n_{Ni}^i + n_{Mn}^i + n_{Co}^i} * 100 \quad (5)$$

<table><caption>Table 4: Evolution of molar fraction of nickel, cobalt and manganese between each other in the samples studied.</caption><thead><tr><th>Sample</th><th>x<sub>Ni</sub><sup>i</sup> (%)</th><th>x<sub>Mn</sub><sup>i</sup> (%)</th><th>x<sub>Co</sub><sup>i</sup> (%)</th></tr></thead><tbody><tr><td>&lt; 75 µm</td><td>55.2</td><td>32.6</td><td>12.2</td></tr><tr><td>75 – 150 µm</td><td>55.1</td><td>32.7</td><td>12.2</td></tr><tr><td>150 – 500 µm</td><td>54.7</td><td>33.1</td><td>12.2</td></tr><tr><td>Mean</td><td>55.0</td><td>32.8</td><td>12.2</td></tr><tr><td>Standard deviation</td><td>0.26</td><td>0.26</td><td>0</td></tr></tbody></table>

As shown in Table 4, the molar fractions of nickel, cobalt, and manganese calculated from their total quantity remain constant across all the samples. The cathode stoichiometry prior to thermal runaway is unknown; however, the calculated molar fractions may align with the cathode stoichiometry $LiNi_{0.55}Mn_{0.33}Co_{0.12}O_2$. Moreover, the consistent molar fraction for these three metals across various particle sizes suggests that the initial arrangement of Nickel-Cobalt-Manganese was unaffected by thermal runaway, while remaining in oxide form. This important observation could provide deeper insight into the mechanisms and reaction pathways involved in thermal runaway, particularly when compared with the study on the thermal stability of NMC conducted by Duan *et al.*¹⁶. The study reveals a progressive phase transition from the lamellar form (space group R-3m) to spinel (Fm-3m), and ultimately to rock salt (Fd-3m) as temperature increases. When the temperature exceeds 500°C, as occurs during thermal runaway, NMC releases oxygen and transitions from a hexagonal (lamellar) to a cubic (rock salt) structure. As noted in the work of Jo *et al.*¹⁷, the oxygen released by the cathode reacts with the lithiated carbon in the anode, leading to the exothermic formation of $Li_2O$. Therefore, the destabilization of the cathode acts as the primary driver of thermal runaway.

However, the evolution of the proportion of oxygen does not follow the same trend as nickel, cobalt, and manganese but tends to remain constant regardless of particle size. This observation suggests that the decrease in NMC oxides with particle size must be compensated by the occurrence of other oxide phases with particle size.

In contrast to nickel, cobalt, and manganese, the proportion of carbon, primarily originating from the graphite anode, increased with particle size. Copper and aluminum, elements exclusively originating from current collectors, exhibited two different trends. The proportion of copper increased with particle size, while the maximum proportion of aluminum was observed in the intermediate-sized sample of 75-150 µm. Taking into account the temperatures reached during thermal runaway (Figure 2), it was observed that the maximum temperature measured on the copper plates during the event was 550°C. This measured maximum temperature was underestimated compared to the actual particle ejection temperature. However, the melting temperature of aluminum and copper are respectively 660°C and 1085°C. It is likely that aluminum may have completely melted during thermal runaway and been ejected as molten droplets out of the cell before solidifying again. In contrast, the copper may not have melted during the event and could have been ejected as solid debris of larger sizes.

### 3.4.3. Density and specific surface area

The evolution of density ($\rho$) and specific surface area (SSA) with particle size is reported in Table 5. The density of particles decreases as their size increases. This observation is consistent with the main
elemental changes occurring as particle size increases, which involves a decrease in transition metals and an increase in carbon (mainly graphite), as illustrated in Figure 6.

<table><caption>Table 5: Density and specific surface area evolution with particle size.</caption><thead><tr><th>Sample</th><th>ρ (kg.m<sup>-3</sup>)</th><th>SSA (m<sup>2</sup>.g<sup>-1</sup>)</th><th>SSA<sub>sphere fcc</sub> (m<sup>2</sup>.g<sup>-1</sup>)</th><th>R</th></tr></thead><tbody><tr><td>&lt; 75 μm</td><td>2958</td><td>6.621</td><td>4.88 10<sup>-2</sup></td><td>136</td></tr><tr><td>75 – 150 μm</td><td>2845</td><td>3.690</td><td>4.12 10<sup>-3</sup></td><td>897</td></tr><tr><td>150 – 500 μm</td><td>2689</td><td>2.131</td><td>1.68 10<sup>-3</sup></td><td>1267</td></tr></tbody></table>

In order to evaluate particle porosity, the measured SSA can be compared to the specific surface areas of an equivalent arrangement of solid spheres with a face-centered cubic structure for each sample *i* (SSA<sup>*i*</sup><sub>sphere fcc</sub>), calculated using equation (6). In the following equation, $V_{sphere}^i(m^3)$ and $S_{sphere}^i(m^2)$ are respectively the volume and surface of an equivalent sphere for sample *i*, evaluated by considering their diameter, corresponding to the median diameter $D50^i(m)$ measured, given in Table 6. The compactness of the face-centered cubic (fcc) arrangement, denoted $c_{fcc}$, is set at 0.74, and the density is denoted $ρ^i(g·m^{-3})$. Equation (7) introduces the ratio R to compare the measured specific surface area with that of the solid sphere model.

$$SSA_{sphere fcc}^{i} = \frac{S_{sphere}^{i} \cdot c_{fcc}}{V_{sphere}^{i} \cdot \rho^{i}} = \frac{6 \cdot c_{fcc}}{\pi \cdot D50^{i} \cdot \rho^{i}} \quad (6)$$

$$R^i = \frac{SSA^i}{SSA_{sphere fcc}^i} \quad (7)$$

As indicated in Table 5, the SSA increases as the particle size decreases. Ratio R indicates that the measured SSA are between 130 and 1270 times higher than those of the equivalent solid sphere model, highlighting the coarse and porous nature of the structures.

### 3.4.4. Particle size distribution

The particle size distribution of each sample was characterized using a laser particle size analyzer. Figure 7 illustrates the particle size distributions of each sample, measured both with and without prior ultrasonication. Table 6 exposes the median diameter (D50), and limits the diameters (D10, D90), where 10% of the sample is contained respectively below and above these values.

<table><caption>Table 6: Median diameter (D50), first and last percentile (D10, D90) and degree of agglomeration of each sample.</caption><thead><tr><th>Sample</th><th>Prior ultrasonication</th><th>D10 (μm)</th><th>D50 (μm)</th><th>D90 (μm)</th><th>AD (%)</th></tr></thead><tbody><tr><td rowspan="2">&lt; 75 μm</td><td>No</td><td>3.38</td><td>9.79</td><td>20.96</td><td rowspan="2">0.91</td></tr><tr><td>Yes</td><td>3.23</td><td>9.70</td><td>21.25</td></tr><tr><td rowspan="2">75 – 150 μm</td><td>No</td><td>78.41</td><td>120.70</td><td>186.78</td><td rowspan="2">30.1</td></tr><tr><td>Yes</td><td>9.90</td><td>84.31</td><td>165.09</td></tr><tr><td rowspan="2">150 – 500 μm</td><td>No</td><td>165.10</td><td>312.47</td><td>572.27</td><td rowspan="2">27.2</td></tr><tr><td>Yes</td><td>21.92</td><td>227.53</td><td>479.63</td></tr></tbody></table>
<figure><img src="image_8.png" /><figcaption>Figure 7: Particle size distribution of sample 0–75 µm (a), 75–150 µm (b), 150–500 µm (c) and a reconstitution of sample 0–500 µm (d) with and without prior ultrasonication.</figcaption></figure>

The laser particle size analyzer measurements rely on Fraunhofer theory. Consequently, the distributions obtained are based on an equivalent sphere model, which may not precisely reflect the actual shapes of the particles analyzed. An aspect ratio factor emerges as the particle traverses the laser, depending on its orientation, causing variations in the measured diameter. Nevertheless, the D10 and D90 percentile values of the distributions without ultrasonication are close to the desired range of values, thus confirming the effectiveness of the sieving process.

Particles ejected during thermal runaway are inherently agglomerates of various cell components. Comparing the median diameters with and without ultrasonication (respectively $D_{50}^{US}$ and $D_{50}$) using equation (8), enables the calculation of the degree of agglomeration (AD) of the particles present in each sample.

$$AD = 100 \frac{D_{50} - D_{50}^{US}}{D_{50}} \qquad (8)$$

Table 6 shows the degree of agglomeration of each sample studied. Sample 0–75 µm is mainly composed of particles resistant to ultrasonication rather than agglomerates (AD = 0.91%). Conversely, ultrasonication applied to the 75–150 µm (AD = 30.1%) and 150–500 µm (AD = 27.2%) samples successfully disagglomerated the particles, revealing at least two new modes in the particle size distributions within the ranges [3µm–5µm] and [10µm–20µm] (Figure 7.b and Figure 7.c). These patterns also appear in the particle size distribution described in the article by Wang et al. article¹¹,
though the latter made no comment on the subject. A peak deconvolution was performed on the distribution <75 µm with ultrasonication, following the normal logarithmic function expressed by equation (9):

$$f(d) = \frac{A}{\sqrt{2\pi}\sigma d} \exp\left(-\frac{(\ln\frac{d}{d_m})^2}{2\sigma^2}\right) \qquad (9)$$

where A is the area under the curve, $d_m$ the median diameter and $\sigma$ is the standard deviation. Three log-normal curves, named mode A, B and C are employed to fit the particle size distribution drawn in Figure 6.a. The fitting parameters are shown in Table 7.

<table><caption>Table 7: Fitting parameters of the log-normal functions resulting from the peak deconvolution of the sample <75µm.</caption><thead><tr><th>Fitting parameters</th><th>Mode A</th><th>Mode B</th><th>Mode C</th></tr></thead><tbody><tr><td>A</td><td>18.98</td><td>77.71</td><td>49.49</td></tr><tr><td>σ</td><td>0.452</td><td>0.425</td><td>0.256</td></tr><tr><td>d<sub>m</sub> (µm)</td><td>4.60</td><td>12.45</td><td>19.73</td></tr><tr><td>R<sup>2</sup></td><td colspan="3">0.9974</td></tr></tbody></table>

The median diameters obtained from the peak deconvolution of the <75µm sample align with the median diameters of the modes observed after ultrasonication for the larger particle size samples (Figure 7.b and Figure 7.c). Therefore, the three families of fine particles present in the <75 µm sample agglomerated into larger particles during the thermal runaway. Furthermore, according to the elemental quantifications (Figure 6), the <75µm sample was predominantly composed of nickel, cobalt, manganese, oxygen and carbon. Mode A might correspond to secondary particles of NMC derived from the cathode, whereas modes B and C could represent two distinct populations of graphite carbon originating from the anode.

Finally, in order to obtain a continuous overview of the particle size of the parent population ejected from the cell, the global distribution was calculated by summing the particle size distributions of the samples <75 µm, 75–150 µm, 150–500 µm, weighted by their volumetric proportions (Figure 7.c). This method provides a more representative and reliable total particle size distribution compared to taking a single sample from the parent population. Such single sampling is prone to being unrepresentative due to the high heterogeneity of the parent population.

### 3.4.5. SEM-EDS analysis

SEM-EDS analysis was conducted on the <75 µm sample (Figure 8) to visualize the distinct modes identified by laser granulometry (Figure 7). A distribution of particles ranging from 10 to 30 µm (Modes B and C) is observed, with grains ranging from 1 to 10 µm (Mode A) agglomerated on them. EDS point analyses were performed on these grains to determine their composition (Table 8).
<figure><img src="image_9.png" /><figcaption>Figure 8: SEM image of a particle from the <75 µm sample, with EDS point analyses performed on particles classified as Mode A and Modes B or C.</figcaption></figure>

<table><caption>Table 8: Element distributions of EDX quantification on Mode A and Modes B-C.</caption><thead><tr><td>Element</td><td>Mode A (% at)</td><td>Mode B-C (% at)</td></tr></thead><tbody><tr><td>C</td><td>44.8</td><td>100</td></tr><tr><td>O</td><td>37.1</td><td>-</td></tr><tr><td>Ni</td><td>10.7</td><td>-</td></tr><tr><td>Mn</td><td>4.7</td><td>-</td></tr><tr><td>Co</td><td>2.7</td><td>-</td></tr></tbody></table>

The EDS quantifications confirm that Modes B-C, identified by laser granulometry (Figure 7), primarily consist of carbon grains originating from the anode. These grains are agglomerated with finer particles corresponding to Mode A, which are mainly composed of transition metals from the cathode (rock-salt). From Table 8, the stoichiometry of the NMC rock-salt particle is Ni<sub>0.59</sub>Mn<sub>0.26</sub>Co<sub>0.15</sub>O, showing a composition comparable to the initial lamellar NMC LiNi<sub>0.55</sub>Mn<sub>0.33</sub>Co<sub>0.12</sub>O<sub>2</sub> calculated Table 4 (The carbon detected in Mode A is attributed to the contribution of the supporting carbon particle within the interaction volume.).

## Conclusions

In this study, a thermal abuse experiment for a large NMC prismatic 140 Ah Li-ion cell at SoC 100% was performed in a thermal insulated closed vessel, in order to carry out an accurate energy and mass balance evaluation. The total energy released during thermal runaway was measured as 1.2 times the electrical energy stored in the cell. Moreover, 78% of the energy was contained in the ejecta (particles and gas), which represented only 38% of the total mass of the initial cell. The study included a detailed examination of the particles, which act as carriers of a considerable amount of energy. Sieving revealed that the majority of the particles emitted during thermal runaway were smaller than 75µm. The Elemental quantifications conducted on each subsample revealed a decrease in the proportion of
cathodic transition metals and an increase in the proportion of carbon, primarily graphite, as a function of particle size. Furthermore, the measured stoichiometries of nickel, cobalt, and manganese remained constant across all the samples, indicating that thermal runaway did not alter the NMC arrangement. The stoichiometry of the cathode was thus determined. Particle density decreased with size, which was consistent with the elemental quantifications. The measurements of specific surface areas also highlighted the coarse and porous nature of the structures. The granulometry measurements conducted using laser granulometry, both with and without ultrasonication, enabled the quantification of the degree of particle agglomeration relative to particle size. Furthermore, it was highlighted that the agglomerates were mainly composed of three families of fine particles (<20 µm) that adhered to larger particles during thermal runaway. According to elemental quantifications, these families corresponded to NMC oxides from the cathode, and graphite carbon from the anode. Finally, the total particle size distribution was calculated by weighing the granulometric distributions of the various samples.

## Abbreviations

<table><tr><td>AD</td><td>Agglomeration degree</td><td>LIB</td><td>Lithium-ion battery</td></tr><tr><td>Al</td><td>Aluminum</td><td>Mn</td><td>Manganese</td></tr><tr><td>BET</td><td>Brunauer-Emmertt-Teller</td><td>Ni</td><td>Nickel</td></tr><tr><td>C</td><td>Carbon</td><td>O</td><td>Oxygen</td></tr><tr><td>Co</td><td>Cobalt</td><td>P</td><td>Phosphorus</td></tr><tr><td>Cu</td><td>Copper</td><td>S</td><td>Sulfur</td></tr><tr><td>F</td><td>Fluorine</td><td>SEM-EDS</td><td>Scanning electron microscope and electronic differential system</td></tr><tr><td>Fcc</td><td>Face-centered cubic</td><td>Si</td><td>Silicon</td></tr><tr><td>ICP-MS</td><td>Inductively coupled plasma mass spectrometry</td><td>SoC</td><td>State of charge</td></tr><tr><td>ICP-OES</td><td>Inductively coupled plasma optical emission spectrometer</td><td>SSA</td><td>Specific surface area</td></tr><tr><td>Li</td><td>Lithium</td><td>TR</td><td>Thermal runaway</td></tr></table>

## Acknowledgments

The authors thank ACC, Automotive Cells Company for its financial support of this work. They also wish to thank Sandrine Barthélemy and Séverine Ebelé from CEA/Liten for their help in the characterizations.

## Conflicts of Interest

The authors declare no conflict of interest
References

(1) International Energy Agency. *Global EV Outlook 2024: Moving towards Increased Affordability*; Global EV Outlook; OECD, 2024.

(2) Feng, X.; Ouyang, M.; Liu, X.; Lu, L.; Xia, Y.; He, X. Thermal Runaway Mechanism of Lithium Ion Battery for Electric Vehicles: A Review. *Energy Storage Materials* **2018**, *10*, 246–267.
https://doi.org/10.1016/j ensm.2017.05.013.

(3) Bravo Diaz, L.; He, X.; Hu, Z.; Restuccia, F.; Marinescu, M.; Barreras, J. V.; Patel, Y.; Offer, G.; Rein, G. Review—Meta-Review of Fire Safety of Lithium-Ion Batteries: Industry Challenges and Research Contributions. *J. Electrochem. Soc.* **2020**, *167* (9), 090559.
https://doi.org/10.1149/1945-7111/aba8b9.

(4) Richard, M. N.; Dahn, J. R. Accelerating Rate Calorimetry Study on the Thermal Stability of Lithium Intercalated Graphite in Electrolyte. *Journal of The Electrochemical Society* **1999**, *11*.

(5) Ren, D.; Liu, X.; Feng, X.; Lu, L.; Ouyang, M.; Li, J.; He, X. Model-Based Thermal Runaway Prediction of Lithium-Ion Batteries from Kinetics Analysis of Cell Components. *Applied Energy* **2018**, *228*, 633–644. https://doi.org/10.1016/j.apenergy.2018.06.126.

(6) Ostanek, J. K.; Li, W.; Mukherjee, P. P.; Crompton, K. R.; Hacker, C. Simulating Onset and Evolution of Thermal Runaway in Li-Ion Cells Using a Coupled Thermal and Venting Model. *Applied Energy* **2020**, *268*, 114972. https://doi.org/10.1016/j.apenergy.2020.114972.

(7) Rappsilber, T.; Yusfi, N.; Krüger, S.; Hahn, S.-K.; Fellinger, T.-P.; Krug von Nidda, J.; Tschirschwitz, R. Meta-Analysis of Heat Release and Smoke Gas Emission during Thermal Runaway of Lithium-Ion Batteries. *Journal of Energy Storage* **2023**, *60*, 106579.
https://doi.org/10.1016/j.est.2022.106579.

(8) Wang, Y.; Song, Z.; Wang, H.; Li, H.; Zhang, Y.; Li, C.; Zhang, X.; Feng, X.; Lu, L.; Ouyang, M. Experimental Research on Flammability Characteristics and Ignition Conditions of Hybrid Mixture Emissions Venting from a Large Format Thermal Failure Lithium-Ion Battery. *Journal of Energy Storage* **2023**, *59*, 106466. https://doi.org/10.1016/j.est.2022.106466.

(9) Zhang, Y.; Wang, H.; Li, W.; Li, C.; Ouyang, M. Size Distribution and Elemental Composition of Vent Particles from Abused Prismatic Ni-Rich Automotive Lithium-Ion Batteries. *Journal of Energy Storage* **2019**, *26*, 100991. https://doi.org/10.1016/j.est.2019.100991.

(10) Zhang, Y.; Wang, H.; Li, W.; Li, C. Quantitative Identification of Emissions from Abused Prismatic Ni-Rich Lithium-Ion Batteries. *eTransportation* **2019**, *2*, 100031.
https://doi.org/10.1016/j.etran.2019.100031.

(11) Wang, Y.; Wang, H.; Zhang, Y.; Cheng, L.; Wu, Y.; Feng, X.; Lu, L.; Ouyang, M. Thermal Oxidation Characteristics for Smoke Particles from an Abused Prismatic Li(Ni0.6Co0.2Mn0.2)O2 Battery. *Journal of Energy Storage* **2021**, *39*, 102639. https://doi.org/10.1016/j.est.2021.102639.

(12) Wang, H.; Wang, Q.; Jin, C.; Xu, C.; Zhao, Y.; Li, Y.; Zhong, C.; Feng, X. Detailed Characterization of Particle Emissions Due to Thermal Failure of Batteries with Different Cathodes. *Journal of Hazardous Materials* **2023**, *458*, 131646. https://doi.org/10.1016/j.jhazmat.2023.131646.

(13) Li, W.; Xue, Y.; Feng, X.; Rao, S.; Zhang, T.; Gao, Z.; Guo, Y.; Zhou, H.; Zhao, H.; Song, Z.; Shi, J.; Wang, H.; Wang, D. Characteristics of Particle Emissions from Lithium-Ion Batteries during Thermal Runaway: A Review. *Journal of Energy Storage* **2024**, *78*, 109980.
https://doi.org/10.1016/j.est.2023.109980.

(14) Hoelle, S.; Scharner, S.; Asanin, S.; Hinrichsen, O. Analysis on Thermal Runaway Behavior of Prismatic Lithium-Ion Batteries with Autoclave Calorimetry. *J. Electrochem. Soc.* **2021**, *168* (12), 120515. https://doi.org/10.1149/1945-7111/ac3c27.

(15) Golubkov, A. W.; Fuchs, D.; Wagner, J.; Wiltsche, H.; Stangl, C.; Fauler, G.; Voitic, G.; Thaler, A.; Hacker, V. Thermal-Runaway Experiments on Consumer Li-Ion Batteries with Metal-Oxide and Olivin-Type Cathodes. *RSC Adv.* **2014**, *4* (7), 3633–3642. https://doi.org/10.1039/C3RA45748F.

(16) Duan, Y.; Chen, S.-P.; Zhang, L.; Guo, L.; Shi, F.-N. Review on Oxygen Release Mechanism and Modification Strategy of Nickel-Rich NCM Cathode Materials for Lithium-Ion Batteries: Recent
Advances and Future Directions. *Energy Fuels* **2024**, *38* (7), 5607–5631.
https://doi.org/10.1021/acs.energyfuels.3c04636.

(17) Jo, S., Seo, S., Kang, S. K., Na, I., Kunze, S., Song, M., San, H., Woo, S. P., Kim, S., Kim, W. B., & Lim, J. Thermal Runaway Mechanism in Ni-Rich Cathode Full Cells of Lithium-Ion Batteries: The Role of Multidirectional Crosstalk. *Advanced materials* **2024**, *36* (31).
https://doi.org/10.1002/adma.202402024.