Equilibrium structure and fluctuations of suspensions of colloidal dumbbells

Pre-trained artificial intelligence-aided analysis of nanoparticles using the segment anything model

Complex structures can be understood as compositions of smaller, more basic elements. The characterization of these structures requires an analysis of their constituents and their spatial configuration. Examples can be found in systems as diverse as galaxies, alloys, living tissues, cells, and even nanoparticles. In the latter field, the most challenging examples are those of subdivided particles and particle-based materials, due to the close proximity of their constituents. The characterization of such nanostructured materials is typically conducted through the utilization of micrographs. Despite the importance of micrograph analysis, the extraction of quantitative data is often constrained. The presented effort demonstrates the morphological characterization of subdivided particles utilizing a pre-trained artificial intelligence model. The results are validated using three types of nanoparticles: nanospheres, dumbbells, and trimers. The automated segmentation of whole particles, as well as their individual subdivisions, is investigated using the Segment Anything Model, which is based on a pre-trained neural network. The subdivisions of the particles are organized into sets, which presents a novel approach in this field. These sets collate data derived from a large ensemble of specific particle domains indicating to which particle each subdomain belongs. The arrangement of subdivisions into sets to characterize complex nanoparticles expands the information gathered from microscopy analysis. The presented method, which employs a pre-trained deep learning model, outperforms traditional techniques by circumventing systemic errors and human bias. It can effectively automate the analysis of particles, thereby providing more accurate and efficient results.

Group formation and collective motion of colloidal rods with an activity triggered by visual perception

We investigate the formation of cohesive groups and the collective diffusion of colloidal spherocylinders with a motility driven by a simple visual perception model. For this, we perform Brownian dynamics simulations without hydrodynamic interactions. The visual perception is based on sight cones attached to the spherocylinders and perception functions quantifying the visual stimuli. If the perception function of a particle reaches a predefined threshold, an active component is added to its motion. We find that, in addition to the opening angle of the cone of sight, the aspect ratio of the particles plays an important role for the formation of cohesive groups. If the elongation of the particles is increased, the maximum angle for which the rods organize themselves into such groups decreases distinctly. After a system forms a cohesive group, it performs a diffusive motion, which can be quantified by an effective diffusion coefficient. For increasing aspect ratios, the spatial expansion of the cohesive groups and the effective diffusion coefficient of the collective motion increase, while the number of active group members decreases. We also find that a larger particle number, a smaller propulsion velocity of the group members, and a smaller threshold for the visual stimulus increase the maximum opening angle for which cohesive groups form. Based on our results, we expect anisotropic particles to be of great relevance for the adjustability of visual perception-dependent motility.

Microscopic diffusion coefficients of dumbbell- and spherocylinder-shaped colloids and their application in simulations of crowded monolayers

We explore the diffusion properties of colloidal particles with dumbbell and spherocylinder shapes using a hydrodynamic bead-shell approach and additional Brownian dynamics (BD) simulations. By applying the bead-shell method, we determine empirical formulas for the microscopic diffusion coefficients. A comparison of these formulas and established experimental and theoretical results shows remarkable agreement. For example, the maximum relative discrepancy found for dumbbells is less than 5%. As an application example of the empirical formulas, we perform two-dimensional (2D) BD simulations based on a single dumbbell or spherocylinder in a suspension of spheres and calculate the resulting effective long-time diffusion coefficients. The performed BD simulations can be compared to quasi-2D systems such as colloids confined at the interface of two fluids. We find that the effective diffusion coefficient of translation mostly depends on the sphere area fraction ϕ, while the effective diffusion coefficient of rotation is influenced by the aspect ratio and ϕ. Furthermore, the effective rotational diffusion constant seems to depend on the particle shape with the corresponding implementation of the interactions. In the resolution limit of our methods, the shape-dependent differences of the microscopic diffusion coefficients and the long-time diffusion constant of translation are negligible in the first approximation. The determined empirical formulas for the microscopic diffusion coefficients add to the knowledge of the diffusion of anisotropic particles, and they can be used in countless future studies.

Phase behaviour in 2D assemblies of dumbbell-shaped colloids generated under geometrical confinement

The structure formation and the phase behaviour of monolayers of dumbbell-shaped colloids are explored. For this, we conduct Langmuir-Blodgett experiments at the air/water interface and conventional Brownian dynamic simulations without hydrodynamic interactions. Using Voronoi tessellations and the probability density of the corresponding shape factor of the Voronoi cells p(ζ), the influence of the area fraction φ on the structure of the monolayers is investigated. An increase of the area fraction leads to a higher percentage of domains containing particles with six nearest neighbours and a sharper progression of p(ζ). Especially in dense systems, these domains can consist of aligned particles with uniform Voronoi cells. Thus, the increase of φ enhances the order of the monolayers. Simulations show that a sufficient enhancement of φ also impacts the pair correlation function which develops a substructure in its first maxima. Furthermore, we find that reducing the barrier speed in the Langmuir-Blodgett experiments enhances the final area fraction for a given target surface pressure which, in turn, also increases the percentage of particles with six nearest neighbours and sharpens the progression of p(ζ). Overall, the experiments and simulations show a remarkable qualitative agreement which indicates a versatile way of characterising colloidal monolayers by Brownian dynamics simulations. This opens up perspectives for application to a broad range of nanoparticle-based thin film coatings and devices.

Micro-phase separation in two dimensional suspensions of self-propelled spheres and dumbbells

We use numerical simulations to study the phase behavior of self-propelled spherical and dumbbellar particles interacting via micro-phase separation inducing potentials. Our results indicate that under the appropriate conditions, it is possible to drive the formation of two new active states; a spinning cluster crystal, i.e. an ordered mesoscopic phase having finite size spinning crystallites as lattice sites, and a fluid of living clusters, i.e. a two dimensional fluid where each "particle" is a finite size living cluster. We discuss the dynamics of these phases and suggest ways of extending their stability under a wide range of active forces.

Nonequilibrium structure of colloidal dumbbells under oscillatory shear

We investigate the nonequilibrium behavior of dense, plastic-crystalline suspensions of mildly anisotropic colloidal hard dumbbells under the action of an oscillatory shear field by employing Brownian dynamics computer simulations. In particular, we extend previous investigations, where we uncovered nonequilibrium phase transitions, to other aspect ratios and to a larger nonequilibrium parameter space, that is, a wider range of strains and shear frequencies. We compare and discuss selected results in the context of scattering and rheological experiments. Both simulations and experiments demonstrate that the previously found transitions from the plastic crystal phase with increasing shear strain also occur at other aspect ratios. We explore the transition behavior in the strain-frequency phase and summarize it in a nonequilibrium phase diagram. Additionally, the experimental rheology results hint at a slowing down of the colloidal dynamics with higher aspect ratio.