{'fraction_non_alphanumeric': 0.018670649738610903, 'fraction_numerical': 0.0, 'mean_word_length': 5.232558139534884, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Nucleation dynamics of active particles.

We present a model of a collection of active and adhesive Brownian particles that are capable of aggregation. Besides the mechanical interaction between particles, a simple active dynamics term (motility) is included to provide an active movement. At a given instant, each particle is either in an active (swim) or unanimated (stop) state, which is controlled by a random process. The model includes important features that are inspired by the phenomenon of biological cell-cell association. One feature is the mean motility that is related to the percentage of the particle being active and the maximum swimming speed. Another feature is the stochastic nature of switching between the swim and stop state. We explored how these key features affect the nucleation dynamics and the stability of the aggregates using simulations. Interestingly, particles can change their collective behavior by solely altering the frequency of switching between the swim and stop state while keeping the mean motility unchanged. These results provide insight into how motor-driven forces can be utilized by active biological systems to modulate the single-to-cluster transition efficiently. A dimensionless parameter is also proposed to measure the overall strength of the nonequilibrium effect on active particles.