Self-consistent description of electrokinetic phenomena in particle-based simulations

Self-organization of Janus particles: Impact of hydrodynamic interactions in substrate consumption for structure formation

We show that the formation of active matter structures requires them to modify their surroundings by creating inhomogeneities such as concentration gradients and fluid flow around the structure constituents. This modification is crucial for the stability of the ordered structures. We examine the formation of catalytic Janus particle aggregates at low volumetric fractions in the presence of hydrodynamic interactions (HIs). Our study shows the types of structures formed for various values of the kinetic constant of the catalytic reaction. The presence of HI causes the aggregate particles to have higher mobility than in the case of the absence of such interactions, which is reflected in the behavior of the pair distribution function. Although HI decreases energy conversion efficiency, they play a significant role in the formation of complex structures found in nature. Self-organization of these structures is driven by direct feedback loops between structure formation and the surrounding medium. As the structures alter the medium by consuming substrate and perturbing fluid flow, the substrate concentration, in turn, dictates the kinetics and configuration of the structures.

Structure and proton conduction in sulfonated poly(ether ether ketone) semi-permeable membranes: a multi-scale computational approach

The design of polymeric membranes for proton or ionic exchange highly depends on the fundamental understanding of the physical and molecular mechanisms that control the formation of the conduction channels. There is an inherent relation between the dynamical structure of the polymeric membrane and the electrostatic forces that drive membrane segregation and proton transport. Here, we used a multi-scale computational approach to analyze the morphology of sulfonated poly(ether ether ketone) membranes at the mesoscale. A self-consistent description of the electrostatic phenomenon was adopted, where discrete polymer chains and a continuum proton field were embedded in a continuum fluid. Brownian dynamics was used for the evolution of the suspended polymer molecules, while a convection-diffusion transport equation, including the Nernst-Planck diffusion mechanism, accounted for the dynamics of the proton concentration field. We varied the polymer concentration, the degree of sulfonation and the level of confinement to find relationships between membrane structure and proton conduction. Our results indicate that the reduced mobility of polymer chains, at concentrations above overlap, and a moderate degree of sulfonation - i.e., 30% - are essential elements for membrane segregation and proton domain connectivity. These conditions also ensure that the membrane structure is not affected by size or by potential gradients. Importantly, our analysis shows that membrane conductivity and current are linearly dependent on polymer concentration and quadratically dependent on the degree of sulfonation. We found that the optimal polymeric membrane design requires a polymer concentration above overlap and a degree of sulfonation around 50%. These conditions promote a dynamical membrane morphology with a constant density of proton channels. Our results and measurements agree with previous experimental works, thereby validating our model and observations.

Discrete and Continuum Models for the Salt in Crowded Environments of Suspended Charged Particles

Electrostatic forces greatly affect the overall dynamics and diffusional activities of suspended charged particles in crowded environments. Accordingly, the concentration of counter- or co-ions in a fluid-''the salt"-determines the range, strength, and order of electrostatic interactions between particles. This environment fosters engineering routes for controlling directed assembly of particles at both the micro- and nanoscale. Here, we analyzed two computational modeling schemes that considered salt within suspensions of charged particles, or polyelectrolytes: discrete and continuum. Electrostatic interactions were included through a Green's function formalism, where the confined fundamental solution for Poisson's equation is resolved by the general geometry Ewald-like method. For the discrete model, the salt was considered as regularized point-charges with a specific valence and size, while concentration fields were defined for each ionic species for the continuum model. These considerations were evolved using Brownian dynamics of the suspended charged particles and the discrete salt ions, while a convection-diffusion transport equation, including the Nernst-Planck diffusion mechanism, accounted for the dynamics of the concentration fields. The salt/particle models were considered as suspensions under slit-confinement conditions for creating crowded "macro-ions", where density distributions and radial distribution functions were used to compare and differentiate computational models. Importantly, our analysis shows that disparate length scales or increased system size presented by the salt and suspended particles are best dealt with using concentration fields to model the ions. These findings were then validated by novel simulations of a semipermeable polyelectrolyte membrane, at the mesoscale, from which ionic channels emerged and enable ion conduction.

Effects of Polymer Length and Salt Concentration on the Transport of ssDNA in Nanofluidic Channels

Electrokinetic phenomena in micro/nanofluidic channels have attracted considerable attention because precise control of molecular transport in liquids is required to optically and electrically capture the behavior of single molecules. However, the detailed mechanisms of polymer transport influenced by electroosmotic flows and electric fields in micro/nanofluidic channels have not yet been elucidated. In this study, a Langevin dynamics simulation was used to investigate the electrokinetic transport of single-stranded DNA (ssDNA) in a cylindrical nanochannel, employing a coarse-grained bead-spring model that quantitatively reproduced the radius of gyration, diffusion coefficient, and electrophoretic mobility of the polymer. Using this practical scale model, transport regimes of ssDNA with respect to the ζ-potential of the channel wall, the ion concentration, and the polymer length were successfully characterized. It was found that the relationship between the radius of gyration of ssDNA and the channel radius is critical to the formation of deformation regimes in a narrow channel. We conclude that a combination of electroosmotic flow velocity gradients and electric fields due to electrically polarized channel surfaces affects the alignment of molecular conformations, such that the ssDNA is stretched/compressed at negative/positive ζ-potentials in comparatively low-concentration solutions. Furthermore, this work suggests the possibility of controlling the center-of-mass position by tuning the salt concentration. These results should be applicable to the design of molecular manipulation techniques based on liquid flows in micro/nanofluidic devices.

Computational immuno-biology for organ transplantation and regenerative medicine

Organ transplantation and regenerative medicine are adopted platforms that provide replacement tissues and organs from natural or engineered sources. Acceptance, tolerance and rejection depend greatly on the proper control of the immune response against graft antigens, motivating the development of immunological and genetical therapies that prevent organ failure. They rely on a complete, or partial, understanding of the immune system. Ultimately, they are innovative technologies that ensure permanent graft tolerance and indefinite graft survival through the modulation of the immune system. Computational immunology has arisen as a tool towards a mechanistic understanding of the biological and physicochemical processes surrounding an immune response. It comprehends theoretical and computational frameworks that simulate immuno-biological systems. The challenge is centered on the multi-scale character of the immune system that spans from atomistic scales, during peptide-epitope and protein interactions, to macroscopic scales, for lymph transport and organ-organ reactions. In this paper, we discuss, from an engineering perspective, the biological processes that are involved during the immune response of organ transplantation. Previous computational efforts, including their characteristics and visible limitations, are described. Finally, future perspectives and challenges are listed to motivate further developments.