Smoothed particle hydrodynamics model for phase separating fluid mixtures. II. Diffusion in a binary mixture

Pizza3: A general simulation framework to simulate food-mechanical and food-deconstruction problems

Current mesh-based simulation approaches face significant challenges in continuously modeling the mechanical behaviors of foods through processing, storage, deconstruction, and digestion. This is primarily due to the limitations of continuum mechanics in dealing with systems characterized by free boundaries, substantial deformations, mechanical failures, and non-homogenized mechanical properties. The dynamic nature of food microstructure and the transformation of the food bolus, in relation to its composition, present formidable obstacles in computer-aided food design. In response, the Pizza3 project adopts an innovative methodology, utilizing an explicit microstructural representation to construct and subsequently deconstruct food products in a modular, Lego-like fashion. Central to this simulation approach are "food atoms", conceptualized from the principles of smoothed particle hydrodynamics. These units are significantly larger than actual atoms but are finely scaled to represent both solid and liquid states of food faithfully. In solid phases, food atoms interact via pairwise forces akin to bond-peridynamic methods, thus extending the capabilities of continuum mechanics to encompass large deformations and fracturing phenomena. For liquids, the model employs artificial conservative and dissipative forces, enabling the simulation of a variety of phenomena within the framework of partial compressibility. The interaction dynamics between rigid and soft objects and fluids are accurately captured through Hertzian contact mechanics, offering a versatile parameterization applicable to impermeable (but possibly penetrable) surfaces and enforcing no-slip conditions. The efficacy of this framework is showcased through the successful modeling of three time-dependent 3D scenarios, each rigorously validated against established analytical and experimental models. Advancing beyond these initial applications, the framework is further extended to more intricate cases inadequately addressed in current literature. This extension sheds light on the underlying mechanisms of in-mouth texture perception, offering new insights and tools for food engineering and design.

Definitions of local density in density-dependent potentials for mixtures

Density-dependent potentials are frequently used in materials simulations because of their approximate description of many-body effects at minimal computational cost. However, in order to apply such models to multicomponent systems, an appropriate definition of total local particle density is required. Here, we discuss two definitions of local density in the context of many-body dissipative particle dynamics. We show that only a potential which combines local densities from all particle types in its argument gives physically meaningful results for all composition ratios. Drawing on the ideas from metal potentials, we redefine local density such that it can accommodate different intertype interactions despite the constraint to keep the main interaction parameter constant, known as Warren's no-go theorem, and generalize the many-body potential to heterogeneous systems. We then show via simulation how liquid-liquid and liquid-solid coexistence can arise just by tuning the interaction parameters.

Multiscale simulation of ideal mixtures using smoothed dissipative particle dynamics

Smoothed dissipative particle dynamics (SDPD) [P. Español and M. Revenga, Phys. Rev. E 67, 026705 (2003)] is a thermodynamically consistent particle-based continuum hydrodynamics solver that features scale-dependent thermal fluctuations. We obtain a new formulation of this stochastic method for ideal two-component mixtures through a discretization of the advection-diffusion equation with thermal noise in the concentration field. The resulting multicomponent approach is consistent with the interpretation of the SDPD particles as moving volumes of fluid and reproduces the correct fluctuations and diffusion dynamics. Subsequently, we provide a general multiscale multicomponent SDPD framework for simulations of molecularly miscible systems spanning length scales from nanometers to the non-fluctuating continuum limit. This approach reproduces appropriate equilibrium properties and is validated with simulation of simple one-dimensional diffusion across multiple length scales.

Discrete Boltzmann modeling of multiphase flows: hydrodynamic and thermodynamic non-equilibrium effects

A discrete Boltzmann model (DBM) is developed to investigate the hydrodynamic and thermodynamic non-equilibrium (TNE) effects in phase separation processes. The interparticle force drives changes and the gradient force, induced by gradients of macroscopic quantities, opposes them. In this paper, we investigate the interplay between them by providing a detailed inspection of various non-equilibrium observables. Based on the TNE features, we define TNE strength which roughly estimates the deviation amplitude from the thermodynamic equilibrium. The time evolution of the TNE intensity provides a convenient and efficient physical criterion to discriminate the stages of the spinodal decomposition and domain growth. Via the DBM simulation and this criterion, we quantitatively study the effects of latent heat and surface tension on phase separation. It is found that the TNE strength attains its maximum at the end of the spinodal decomposition stage, and it decreases when the latent heat increases from zero. The surface tension effects are threefold, prolong the duration of the spinodal decomposition stage, decrease the maximum TNE intensity, and accelerate the speed of the domain growth stage.

Modeling multiphase flow using fluctuating hydrodynamics

Fluctuating hydrodynamics provides a model for fluids at mesoscopic scales where thermal fluctuations can have a significant impact on the behavior of the system. Here we investigate a model for fluctuating hydrodynamics of a single-component, multiphase flow in the neighborhood of the critical point. The system is modeled using a compressible flow formulation with a van der Waals equation of state, incorporating a Korteweg stress term to treat interfacial tension. We present a numerical algorithm for modeling this system based on an extension of algorithms developed for fluctuating hydrodynamics for ideal fluids. The scheme is validated by comparison of measured structure factors and capillary wave spectra with equilibrium theory. We also present several nonequilibrium examples to illustrate the capability of the algorithm to model multiphase fluid phenomena in a neighborhood of the critical point. These examples include a study of the impact of fluctuations on the spinodal decomposition following a rapid quench, as well as the piston effect in a cavity with supercooled walls. The conclusion in both cases is that thermal fluctuations affect the size and growth of the domains in off-critical quenches.

Phase separation of binary fluids with dynamic temperature

Phase separation of binary fluids quenched by contact with cold external walls is considered. Navier-Stokes, convection-diffusion, and energy equations are solved by lattice Boltzmann method coupled with finite-difference schemes. At high viscosity, different morphologies are observed by varying the thermal diffusivity. In the range of thermal diffusivities with domains growing parallel to the walls, temperature and phase separation fronts propagate toward the inner of the system with power-law behavior. At low viscosity hydrodynamics favors rounded shapes, and complex patterns with different length scales appear. Off-symmetrical systems behave similarly but with more ordered configurations.

Spatially resolved simulations of membrane reactions and dynamics: multipolar reaction DPD

Biophysical chemistry of mesoscale systems and quantitative modeling in systems biology now require a simulation methodology unifying chemical reaction kinetics with essential collective physics. This will enable the study of the collective dynamics of complex chemical and structural systems in a spatially resolved manner with a combinatorially complex variety of different system constituents. In order to allow a direct link-up with experimental data (e.g. high-throughput fluorescence images) the simulations must be constructed locally, i.e. mesoscale phenomena have to emerge from local composition and interactions that can be extracted from experimental data. Under suitable conditions, the simulation of such local interactions must lead to processes such as vesicle budding, transport of membrane-bounded compartments and protein sorting, all of which result from a sophisticated interplay between chemical and mechanical processes and require the link-up of different length scales. In this work, we show that introducing multipolar interactions between particles in dissipative particle dynamics (DPD) leads to extended membrane structures emerging in a self-organized manner and exhibiting the necessary mechanical stability for transport, correct scaling behavior, and membrane fluidity so as to provide a two-dimensional self-organizing dynamic reaction environment for kinetic studies in the context of cell biology.