As each particle is registered carefully across all states of charge, we are able to track their damage trajectory on a particle-by-particle basis to truly understand how each particle is behaving. Figure shows that there is a number of possible damage trajectories that could be followed and that particles are following the different paths through their electrochemical journey. In Figure , we apply conditional analysis to each particle to understand fully how each particle is reacting to the applied potential (i.e., at what potential does a particular particle experience its minimum or maximum damage). Typically, we see that that particles in their least damaged state occur at pristine potential, when considering the mean pixel intensity of all the particles in the electrode (see Figure ). We observe a similar phenomenon here, where 34% of particles exhibit their minimum damage factor in the pristine state, and only 2% show their lowest damage at the top of charge (4.3 V and 4.4 V; see Figure ), indicating that particles are unlikely to remain undamaged at higher voltages. However, there is a multiplicity of different behaviours across the sample, with many particles showing their lowest damage factor at 4.0 V, 4.2 V DC, or 2.5 V DC. Notably, 15% of particles reach their minimum damage factor at 4.2 V DC. This aligns with observations of crack closure in the particle centres at 4.2 V DC, which we attribute to primary particles rapidly expanding within the core of secondary particles and filling voids created by cracking during delithiation (see Figure ). This may be intuitive, until we consider where particles display their most damaged state; we calculate that 35% of particles are most damaged at 4.2 V DC. We further examined how many particles sustained damage during charging to 4.4 V. Our analysis revealed that 92.1% of particles experienced some degree of damage during the charging process (see Figure ). This indicates that nearly all particles exhibited a damage factor higher than their pristine state at voltages between 4.0 V and 4.4 V, aligning with previous understanding. Next, we investigated how many particles showed a reduction in their damage factor at 2.5 V DC. Approximately 89% of particles became less damaged, compared to their damage factor at 4.4 V, after being fully discharged to 2.5 V and relithiated (see Figure ). While these qualitative observations confirm that the sample responds to voltage stimuli, they lack the granularity needed to fully capture all processes within the samples. To address this, we analysed the damage factor of the largest 50% of particles (Q3 and Q4) and tracked its evolution during charge-discharge cycles (see Figure ). Initially, 93.4% of particles became damaged when transitioning from the pristine state to 4.2 V, consistent with previous findings (see * in Figure ). A small subset, 6.6%, showed a reduction in damage, likely due to slight variability between scans. Focusing on the 3,420 particles that showed increased damage at 4.2 V, we observed that 2,008 became further damaged as the voltage increased to 4.4 V (see ** in Figure ). Meanwhile, 1,412 particles exhibited a slight reduction in damage during this voltage transition. Interestingly, nearly 90% of these 1,412 particles experienced significant increases in damage once discharge began (see *** in Figure ). These particles may represent a subset experiencing high levels of state-of-charge (SoC) heterogeneity, leading to variations in primary crystallite volumes. This heterogeneity likely creates strained particles prone to substantial damage. Between 4.2 V DC and 2.5V DC, a total of 2024 (55%) particles become less damaged, as might be expected. This, however, means that a significant number of particles actually become more damaged on discharge, although the magnitude of damage is very minimal as can be seen form the colour scale of the streams (orange denotes little change, and red paths would represent high changes in damage between states). The most populous path length is made up of 688 (18.8%) particles which follows a DDDH (damage, damage, damage, heals) pathway; however, many pathways are equally likely as shown by minimal changes in the severity of greyscale change along each path. However, when considered as an overall change in the electrode, the combined behaviour appears to show a reduction in cracking for the whole electrode. This again serves to highlight that within an electrode there are many complex mechanisms at play causing a variety of possible pathways for any one particle to be followed. This analysis is only possible due to the large number of particles evaluated here, and the advanced particle-tracking and grey-scale analysis approach used.