The fluid dynamics of a viscoelastic fluid dripping onto a substrate.

Extensional flows of complex fluids play an important role in many industrial applications, such as spraying and atomisation, as well as microfluidic-based drop deposition. The dripping-on-substrate (DoS) technique is a conceptually-simple, but dynamically-complex, probe of the extensional rheology of low-viscosity, non-Newtonian fluids. It incorporates the capillary-driven thinning of a liquid bridge, produced by a single drop as it is slowly dispensed from a syringe pump onto a solid partially-wetting substrate.

Determining interfacial tension and critical micelle concentrations of surfactants from atomistic molecular simulations.

Hypothesis Atomistically-detailed models of surfactants provide quantitative information on the molecular interactions and spatial distributions at fluid interfaces. Hence, it should be possible to extract from this information, macroscopical thermophysical properties such as interfacial tension, critical micelle concentrations and the relationship between these properties and the bulk fluid surfactant concentrations. Simulations and Experiments Molecular-scale interfacial of systems containing n-dodecyl β-glucoside (APG) are simulated using classical molecular dynamics.

Liquid-Liquid Dispersion Performance Prediction and Uncertainty Quantification Using Recurrent Neural Networks.

We demonstrate the application of a recurrent neural network (RNN) to perform multistep and multivariate time-series performance predictions for stirred and static mixers as exemplars of complex multiphase systems. We employ two network architectures in this study, fitted with either long short-term memory and gated recurrent unit cells, which are trained on high-fidelity, three-dimensional, computational fluid dynamics simulations of the mixer performance, in the presence and absence of surfactants, in terms of drop size distributions and interfacial areas as a function of system parameters; these include physicochemical properties, mixer geometry, and operating conditions. Our results demonstrate that while it is possible to train RNNs with a single fully connected layer more efficiently than with an encoder-decoder structure, the latter is shown to be more capable of learning long-term dynamics underlying dispersion metrics.

Applying Convolutional Neural Networks to data on unstructured meshes with space-filling curves.

This paper presents the first classical Convolutional Neural Network (CNN) that can be applied directly to data from unstructured finite element meshes or control volume grids. CNNs have been hugely influential in the areas of image classification and image compression, both of which typically deal with data on structured grids. Unstructured meshes are frequently used to solve partial differential equations and are particularly suitable for problems that require the mesh to conform to complex geometries or for problems that require variable mesh resolution.

Atomic Force Microscopy and Molecular Dynamic Simulation of Adsorption of Polyacrylamide with Different Chemistries onto Calcium Carbonate.

This study investigates the interaction of polyacrylamide (PAM) of different functional groups (sulfonate vs. carboxylate) and charge density (30% hydrolysed vs. 10% hydrolysed) with calcium carbonate (CaCO) via atomic force microscopy (AFM) and partly via molecular dynamic (MD) simulations.

Atomic Force Microscopy of Hydrolysed Polyacrylamide Adsorption onto Calcium Carbonate.

In this work, the interaction of hydrolysed polyacrylamide (HPAM) of two molecular weights (F3330, 11-13 MDa; F3530, 15-17 MDa) with calcium carbonate (CaCO) was studied via atomic force microscopy (AFM). In the absence of polymers at 1.7 mM and 1 M NaCl, good agreement with DLVO theory was observed.

Molecular Dynamics Simulation of Polyacrylamide Adsorption on Calcite.

In poorly consolidated carbonate rock reservoirs, solids production risk, which can lead to increased environmental waste, can be mitigated by injecting formation-strengthening chemicals. Classical atomistic molecular dynamics (MD) simulation is employed to model the interaction of polyacrylamide-based polymer additives with a calcite structure, which is the main component of carbonate formations. Amongst the possible calcite crystal planes employed as surrogates of reservoir rocks, the (1 0 4) plane is shown to be the most suitable surrogate for assessing the interactions with chemicals due to its stability and more realistic representation of carbonate structure.

Analyzing drop coalescence in microfluidic devices with a deep learning generative model.

Predicting drop coalescence based on process parameters is crucial for experimental design in chemical engineering. However, predictive models can suffer from the lack of training data and more importantly, the label imbalance problem. In this study, we propose the use of deep learning generative models to tackle this bottleneck by training the predictive models using generated synthetic data.

Surfactant-laden droplet size prediction in a flow-focusing microchannel: a data-driven approach.

The control of droplet formation and size using microfluidic devices is a critical operation for both laboratory and industrial applications, in micro-dosage. Surfactants can be added to improve the stability and control the size of the droplets by modifying their interfacial properties. In this study, a large-scale data set of droplet size was obtained from high-speed imaging experiments conducted on a flow-focusing microchannel where aqueous surfactant-laden droplets were generated in silicone oil.

Ensemble latent assimilation with deep learning surrogate model: application to drop interaction in a microfluidics device.

A major challenge in the field of microfluidics is to predict and control drop interactions. This work develops an image-based data-driven model to forecast drop dynamics based on experiments performed on a microfluidics device. Reduced-order modelling techniques are applied to compress the recorded images into low-dimensional spaces and alleviate the computational cost.

Drying-induced stresses in poroelastic drops on rigid substrates.

We develop a theory for drying-induced stresses in sessile, poroelastic drops undergoing evaporation on rigid surfaces. Using a lubrication-like approximation, the governing equations of three-dimensional nonlinear poroelasticity are reduced to a single thin-film equation for the drop thickness. We find that thin drops experience compressive elastic stresses but the total in-plane stresses are tensile.

Adsorption of Hydrolysed Polyacrylamide onto Calcium Carbonate.

Carbonate rock strengthening using chemical techniques is a strategy to prevent excessive fines migration during oil and gas production. We provide herein a study of the adsorption of three types of hydrolysed polyacrylamide (HPAM) of different molecular weight (F3330S, 11-13 MDa; F3530 S, 15-17 MDa; F3630S, 18-20 MDa) onto calcium carbonate (CaCO) particles via spectrophotometry using a Shimadzu UV-2600 spectrometer. The results are compared to different adsorption isotherms and kinetic models.

Continuum-scale modelling of polymer blends using the Cahn-Hilliard equation: transport and thermodynamics.

The Cahn-Hilliard equation is commonly used to study multi-component soft systems such as polymer blends at continuum scales. We first systematically explore various features of the equation system, which give rise to a deep connection between transport and thermodynamics-specifically that the Gibbs free energy of mixing function is central to formulating a well-posed model. Accordingly, we explore how thermodynamic models from three broad classes of approach (lattice-based, activity-based and perturbation methods) can be incorporated within the Cahn-Hilliard equation and examine how they impact the numerical solution for two model polymer blends, noting that although the analysis presented here is focused on binary mixtures, it is readily extensible to multi-component mixtures.

Surface Topography Effects on Pool Boiling via Non-equilibrium Molecular Dynamics Simulations.

In this work, we investigate nucleate pool boiling via non-equilibrium molecular dynamics simulations. The effect of nano-structured surface topography on nucleation and transition to a film-like boiling regime is studied at the molecular scale, by varying the cavity aspect ratio, wall superheat, and wettability through a systematic parametric analysis conducted on a Lennard-Jones (LJ) system. The interplay of the aforementioned factors is rationalized by means of a classical nucleation theory-based model.

Film Control to Study Contributions of Waves to Droplet Impact Dynamics on Thin Flowing Liquid Films.

Droplet impact is a very common phenomenon in nature and attracts attention due to its aesthetic fascination and wide-ranging applications. Previous studies on flowing liquid films have neglected the contributions of spatial structures of waves to the impact outcome, while this has recently been shown to have a significant influence on the drop impact dynamics. In this report, we outline a step-by-step procedure to investigate the effect of periodic inlet forcing of a flowing liquid film leading to the production of spatiotemporally regular wave structures on drop impact dynamics.

Bulk viscosity of molecular fluids.

The bulk viscosity of molecular models of gases and liquids is determined by molecular simulations as a combination of a dilute gas contribution, arising due to the relaxation of internal degrees of freedom, and a configurational contribution, due to the presence of intermolecular interactions. The dilute gas contribution is evaluated using experimental data for the relaxation times of vibrational and rotational degrees of freedom. The configurational part is calculated using Green-Kubo relations for the fluctuations of the pressure tensor obtained from equilibrium microcanonical molecular dynamics simulations.

Moving Contact Lines: Linking Molecular Dynamics and Continuum-Scale Modeling.

Despite decades of research, the modeling of moving contact lines has remained a formidable challenge in fluid dynamics whose resolution will impact numerous industrial, biological, and daily life applications. On the one hand, molecular dynamics (MD) simulation has the ability to provide unique insight into the microscopic details that determine the dynamic behavior of the contact line, which is not possible with either continuum-scale simulations or experiments. On the other hand, continuum-based models provide a link to the macroscopic description of the system.

Impact of droplets on immiscible liquid films.

The impact of droplets on liquid films is a ubiquitous phenomenon not only in nature but also in many industrial applications. Compared to the widely-studied impact of droplets on films of identical fluids, the impact of droplets on immiscible films has received far less attention. In the present work, we show using high-speed imaging that immiscibility has a profound effect on the impact dynamics.

Doubly excited pulse waves on thin liquid films flowing down an inclined plane: An experimental and numerical study.

The interaction patterns between doubly excited pulse waves on thin liquid films flowing down an inclined plane are studied both experimentally and numerically. The effect of varying the film flow rate, interpulse interval, and substrate inclination angle on the pulse interaction patterns is examined. Our results show that different interaction patterns exist for these binary pulses, which include solitary wave behavior, partial or complete pulse coalescence, and pulse noncoalescence.

Simulation of immiscible liquid-liquid flows in complex microchannel geometries using a front-tracking scheme.

The three-dimensional two-phase flow dynamics inside a microfluidic device of complex geometry is simulated using a parallel, hybrid front-tracking/level-set solver. The numerical framework employed circumvents numerous meshing issues normally associated with constructing complex geometries within typical computational fluid dynamics packages. The device considered in the present work is constructed via a module that defines solid objects by means of a static distance function.

Monomer diffusion into static and evolving polymer networks during frontal photopolymerisation.

Frontal photopolymerisation (FPP) is a directional solidification process that converts monomer-rich liquid into crosslinked polymer solid by light exposure and finds applications ranging from lithography to 3D printing. Inherent to this process is the creation of an evolving polymer network that is exposed to a monomer bath. A combined theoretical and experimental investigation is performed to determine the conditions under which monomer from this bath can diffuse into the propagating polymer network and cause it to swell.

Droplet impact on flowing liquid films with inlet forcing: the splashing regime.

The impact process of droplets falling obliquely on thin flowing films is studied using a high-speed imaging system with a focus on splashing. Frequency-forcing of the flow rate at the inlet is applied in order to form solitary waves prior to droplet impact. The outcomes associated with impact on targeted regions of the waves are examined; these include the capillary wave region preceding the large wave peak, the flat film region, and the wave hump region.

Impact of Droplets on Liquid Films in the Presence of Surfactant.

The impact of droplets on liquid films is ubiquitous in natural and industrial processes, and surfactants can significantly alter the impact process by changing the local surface tension. Here we study the impact of droplets on liquid films in the presence of surfactant using high-speed photography, and reveal the flow pattern by dye-tracing. The effects of the droplet size and speed, and the initial film thickness on the impact process are elucidated.

Bulk advection and interfacial flows in the binary coalescence of surfactant-laden and surfactant-free drops.

This work focuses on the study of bulk flows accompanying the coalescence of two aqueous drops, one containing surfactant and the other surfactant-free, in silicone oils of various viscosities. It is observed that the surfactant-free drop intrudes into the surfactant-laden drop in the form of a penetrating jet whose speed increases and average radius decreases with increasing outer phase viscosity. Mixing patterns within the coalescing drops are due to the force imbalance caused by capillary pressure difference and surfactant-induced Marangoni stresses.

Physical insights into the blood-brain barrier translocation mechanisms.

The number of individuals suffering from diseases of the central nervous system (CNS) is growing with an aging population. While candidate drugs for many of these diseases are available, most of these pharmaceutical agents cannot reach the brain rendering most of the drug therapies that target the CNS inefficient. The reason is the blood-brain barrier (BBB), a complex and dynamic interface that controls the influx and efflux of substances through a number of different translocation mechanisms.