A discrete-element approach is employed to model the transport, collision, adhesion, and deposition of small colloidal particles in a spin coating process. The computations are used to predict particle distribution and wall adhesion during the nonevaporative phase of spin coating of a thin film, which is important for controlling the abrasiveness, opacity, conductivity, and other properties of the film, as well as for using the deposited particles for growing new materials (e.g., nanotubes). The computations examine the particle distribution and the effect of particle adhesive force on particle deposition during spin coating. Particles are observed to preferentially collect within the film ridge just behind the moving contact line. An increase in the particle adhesive force is observed to lead to enhanced deposition of particles within an inner radius of the film and increase in the aggregate size.

Simulating general quantum processes that describe realistic interactions of quantum systems following a non-unitary evolution is challenging for conventional quantum computers that directly implement unitary gates. We analyze complexities for promising methods such as the Sz.-Nagy dilation and linear combination of unitaries that can simulate open systems by the probabilistic realization of non-unitary operators, requiring multiple calls to both the encoding and state preparation oracles. We propose a quantum two-unitary decomposition (TUD) algorithm to decompose a d-dimensional operator A with non-zero singular values as A=(U1+U2)/2 using the quantum singular value transformation algorithm, avoiding classically expensive singular value decomposition (SVD) with an O(d3) overhead in time. The two unitaries can be deterministically implemented, thus requiring only a single call to the state preparation oracle for each. The calls to the encoding oracle can also be reduced significantly at the expense of an acceptable error in measurements. Since the TUD method can be used to implement non-unitary operators as only two unitaries, it also has potential applications in linear algebra and quantum machine learning.

A computational study was performed both of a single agglomerate and of the collision of two agglomerates in a shear flow. The agglomerates were extracted from a direct numerical simulation of a turbulent agglomeration process, and had the loosely packed fractal structure typical of agglomerate structures formed in turbulent agglomeration processes. The computation was performed using a discrete-element method for adhesive particles with four-way coupling, accounting both for forces between the fluid and the particles (andvice versa) as well as force transmission directly between particles via particle collisions. In addition to understanding and characterizing the particle dynamics, the study focused on illuminating the fluid flow field induced by the agglomerate in the presence of a background shear and the effect of collisions on this particle-induced flow. Perhaps the most interesting result of the current work was the observation that the flow field induced by a particle agglomerate rotating in a shear flow has the form of two tilted vortex rings with opposite-sign circulation. These rings are surrounded by a sea of stretched vorticity from the background shear flow. The agglomerate rotates in the shear flow, but at a slower rate than the ambient fluid elements. In the computations with two colliding agglomerates, we observed cases resulting in agglomerate merger, bouncing and fragmentation. However, the bouncing cases were all observed to also result in an exchange of particles between the two colliding agglomerates, so that they were influenced both by elastic rebound of the agglomerate structures as well as by tearing away of particulate matter between the agglomerates. Overall, the problems of agglomerate–flow interaction and of the collision of two agglomerates in a shear flow are considerably richer in physical phenomena and more complex than can be described by the common approximation that represents each agglomerate by an ‘equivalent sphere’.

Gram-negative bacteria, as well as some Gram-positive bacteria, possess hair-like appendages known as fimbriae, which play an important role in adhesion of the bacteria to surfaces or to other bacteria. Unlike the sex pili or flagellum, the fimbriae are quite numerous, with of order 1000 fimbriae appendages per bacterial cell. In this paper, a recently developed hybrid model for bacterial biofilms is used to examine the role of fimbriae tension force on the mechanics of bacterial biofilms. Each bacterial cell is represented in this model by a spherocylindrical particle, which interact with each other through collision, adhesion, lubrication force, and fimbrial force. The bacterial cells absorb water and nutrients and produce extracellular polymeric substance (EPS). The flow of water and EPS, and nutrient diffusion within these substances, is computed using a continuum model that accounts for important effects such as osmotic pressure gradient, drag force on the bacterial cells, and viscous shear. The fimbrial force is modeled using an outer spherocylinder capsule around each cell, which can transmit tensile forces to neighboring cells with which the fimbriae capsule collides. We find that the biofilm structure during the growth process is dominated by a balance between outward drag force on the cells due to the EPS flow away from the bacterial colony and the inward tensile fimbrial force acting on chains of cells connected by adhesive fimbriae appendages. The fimbrial force also introduces a large rotational motion of the cells and disrupts cell alignment caused by viscous torque imposed by the EPS flow. The current paper characterizes the competing effects of EPS drag and fimbrial force using a series of computations with different values of the ratio of EPS to bacterial cell production rate and different numbers of fimbriae per cell.