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1.
Soft Matter ; 19(34): 6556-6568, 2023 Aug 30.
Artigo em Inglês | MEDLINE | ID: mdl-37599649

RESUMO

We numerically study the dynamics of a passive fluid droplet confined within a microchannel whose walls are covered with a thin layer of active gel. The latter represents a fluid of extensile material modelling, for example, a suspension of cytoskeletal filaments and molecular motors. Our results show that the layer is capable of producing a spontaneous flow triggering a rectilinear motion of the passive droplet. For a hybrid design (a single wall covered by the active layer), at the steady state the droplet attains an elliptical shape, resulting from an asymmetric saw-toothed structure of the velocity field. In contrast, if the active gel covers both walls, the velocity field exhibits a fully symmetric pattern considerably mitigating morphological deformations. We further show that the structure of the spontaneous flow in the microchannel can be controlled by the anchoring conditions of the active gel at the wall. These findings are also confirmed by selected 3D simulations. Our results may stimulate further research addressed to design novel microfludic devices whose functioning relies on the collective properties of active gels.

2.
Eur Phys J E Soft Matter ; 46(5): 32, 2023 May 08.
Artigo em Inglês | MEDLINE | ID: mdl-37154834

RESUMO

Tracking droplets in microfluidics is a challenging task. The difficulty arises in choosing a tool to analyze general microfluidic videos to infer physical quantities. The state-of-the-art object detector algorithm You Only Look Once (YOLO) and the object tracking algorithm Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT) are customizable for droplet identification and tracking. The customization includes training YOLO and DeepSORT networks to identify and track the objects of interest. We trained several YOLOv5 and YOLOv7 models and the DeepSORT network for droplet identification and tracking from microfluidic experimental videos. We compare the performance of the droplet tracking applications with YOLOv5 and YOLOv7 in terms of training time and time to analyze a given video across various hardware configurations. Despite the latest YOLOv7 being 10% faster, the real-time tracking is only achieved by lighter YOLO models on RTX 3070 Ti GPU machine due to additional significant droplet tracking costs arising from the DeepSORT algorithm. This work is a benchmark study for the YOLOv5 and YOLOv7 networks with DeepSORT in terms of the training time and inference time for a custom dataset of microfluidic droplets.

3.
J Chem Phys ; 158(10): 104101, 2023 Mar 14.
Artigo em Inglês | MEDLINE | ID: mdl-36922125

RESUMO

A regularized version of the lattice Boltzmann method for efficient simulation of soft materials is introduced. Unlike standard approaches, this method reconstructs the distribution functions from available hydrodynamic variables (density, momentum, and pressure tensor) without storing the full set of discrete populations. This scheme shows significantly lower memory requirements and data access costs. A series of benchmark tests of relevance to soft matter, such as collisions of fluid droplets, is discussed to validate the method. The results can be of particular interest for high-performance simulations of soft matter systems on future exascale computers.

4.
Phys Rev Lett ; 128(12): 128001, 2022 Mar 25.
Artigo em Inglês | MEDLINE | ID: mdl-35394304

RESUMO

We report new dynamical modes in confined soft granular flows, such as stochastic jetting and dripping, with no counterpart in continuum viscous fluids. The new modes emerge as a result of the propagation of the chaotic behavior of individual grains-here, monodisperse emulsion droplets-to the level of the entire system as the emulsion is focused into a narrow orifice by an external viscous flow. We observe avalanching dynamics and the formation of remarkably stable jets-single-file granular chains-which occasionally break, resulting in a non-Gaussian distribution of cluster sizes. We find that the sequences of droplet rearrangements that lead to the formation of such chains resemble unfolding of cancer cell clusters in narrow capillaries, overall demonstrating that microfluidic emulsion systems could serve to model various aspects of soft granular flows, including also tissue dynamics at the mesoscale.


Assuntos
Microfluídica , Emulsões , Viscosidade
5.
Langmuir ; 37(30): 9026-9033, 2021 08 03.
Artigo em Inglês | MEDLINE | ID: mdl-34291636

RESUMO

We numerically study the translocation dynamics of double emulsion drops with multiple close-packed inner droplets within constrictions. Such liquid architectures, which we refer to as HIPdEs (high-internal phase double emulsions), consist of a ternary fluid, in which monodisperse droplets are encapsulated within a larger drop in turn immersed in a bulk fluid. Extensive two-dimensional lattice Boltzmann simulations show that if the area fraction of the internal drops is close to the packing fraction limit of hard spheres and the height of the channel is much smaller than the typical size of the emulsion, the crossing yields permanent shape deformations persistent over long periods of time. Morphological changes and rheological response are quantitatively assessed in terms of the structure of the velocity field, circularity of the emulsion, and rate of energy dissipated by viscous forces. Our results may be used to improve the design of soft mesoscale porous materials, which employ HIPdEs as templates for tissue engineering applications.


Assuntos
Engenharia Tecidual , Emulsões , Porosidade , Reologia , Viscosidade
6.
Soft Matter ; 17(9): 2374-2383, 2021 Mar 11.
Artigo em Inglês | MEDLINE | ID: mdl-33592086

RESUMO

A recently proposed mesoscale approach for the simulation of multicomponent flows with near-contact interactions is employed to investigate the early stage formation and clustering statistics of soft flowing crystals in microfluidic channels. Specifically, we first demonstrate the ability of the aforementioned mesoscale model to accurately reproduce main mechanisms leading to the formation of two basic droplet patterns (triangular and hexagonal), in close agreement with experimental evidence. Next, we quantitatively evaluate the device-scale clustering efficiency of the crystal formation process by introducing a new orientational order parameter, based on the Delaunay triangulation and Voronoi diagrams analysis of the droplet patterns. The mesoscale computational approach employed in this work proves to be an efficient tool to shed new light on the complex dynamics of dense emulsions, from short-scale thin-film hydrodynamics, all the way up to global structure formation and statistics of the resulting droplets ensembles.

7.
Philos Trans A Math Phys Eng Sci ; 379(2208): 20200400, 2021 Oct 18.
Artigo em Inglês | MEDLINE | ID: mdl-34455844

RESUMO

We present a deep learning-based object detection and object tracking algorithm to study droplet motion in dense microfluidic emulsions. The deep learning procedure is shown to correctly predict the droplets' shape and track their motion at competitive rates as compared to standard clustering algorithms, even in the presence of significant deformations. The deep learning technique and tool developed in this work could be used for the general study of the dynamics of biological agents in fluid systems, such as moving cells and self-propelled microorganisms in complex biological flows. This article is part of the theme issue 'Progress in mesoscale methods for fluid dynamics simulation'.

8.
J Chem Phys ; 152(14): 144101, 2020 Apr 14.
Artigo em Inglês | MEDLINE | ID: mdl-32295357

RESUMO

We present an extension of the multiparticle collision dynamics method for flows with complex interfaces, including supramolecular near-contact interactions mimicking the effect of surfactants. The new method is demonstrated for the case of (i) short range repulsion of droplets in close contact, (ii) arrested phase separation, and (iii) different pattern formation during spinodal decomposition of binary mixtures.

9.
Environ Sci Technol ; 51(8): 4280-4288, 2017 04 18.
Artigo em Inglês | MEDLINE | ID: mdl-28333448

RESUMO

Active research in nanotechnology contemplates the use of nanomaterials for environmental engineering applications. However, a primary challenge is understanding the effects of nanomaterial properties on industrial device performance and translating unique nanoscale properties to the macroscale. One emerging example consists of graphene oxide (GO) membranes for separation processes. Thus, here we investigate how individual GO properties can impact GO membrane characteristics and water permeability. GO chemistry and morphology were controlled with easy-to-implement photoreduction and sonication techniques and were quantitatively correlated, offering a valuable tool for accelerating characterization. Chemical GO modification allows for fine control of GO oxidation state, allowing control of GO architectural laminate (GOAL) spacing and permeability. Water permeability was measured for eight GOALs characterized by different GOAL chemistry and morphology and indicates that GOAL nanochannel height dictates water transport. The experimental outputs were corroborated with mesoscale water transport simulations of relatively large domains (thousands of square nanometers) and indicate a no-slip Darcy-like behavior inside the GOAL nanochannels. The experimental and simulation evidence presented in this study helps create a clearer picture of water transport in GOAL and can be used to rationally design more effective and efficient GO membranes.


Assuntos
Grafite/química , Oxigênio , Nanoestruturas/química , Nanotecnologia , Óxidos/química
10.
J Chem Phys ; 146(21): 214703, 2017 Jun 07.
Artigo em Inglês | MEDLINE | ID: mdl-28576088

RESUMO

The surface structure and composition of a multi-component catalyst are critical factors in determining its catalytic performance. The surface composition can depend on the local pressure of the reacting species, leading to the possibility that the flow through a nanoporous catalyst can affect its structure and reactivity. Here, we explore this possibility for oxidation reactions on nanoporous gold, an AgAu bimetallic catalyst. We use microscopy and digital reconstruction to obtain the morphology of a two-dimensional slice of a nanoporous gold sample. Using lattice Boltzmann fluid dynamics simulations along with thermodynamic models based on first-principles total-energy calculations, we show that some sections of this sample have low local O2 partial pressures when exposed to reaction conditions, which leads to a pure Au surface in these regions, instead of the active bimetallic AgAu phase. We also explore the effect of temperature on the surface structure and find that moderate temperatures (≈300-450 K) should result in the highest intrinsic catalytic performance, in apparent agreement with experimental results.

11.
Eur Phys J Plus ; 136(8): 864, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34458055

RESUMO

The state-of-the-art deep learning-based object recognition YOLO algorithm and object tracking DeepSORT algorithm are combined to analyze digital images from fluid dynamic simulations of multi-core emulsions and soft flowing crystals and to track moving droplets within these complex flows. The YOLO network was trained to recognize the droplets with synthetically prepared data, thereby bypassing the labor-intensive data acquisition process. In both applications, the trained YOLO + DeepSORT procedure performs with high accuracy on the real data from the fluid simulations, with low error levels in the inferred trajectories of the droplets and independently computed ground truth. Moreover, using commonly used desktop GPUs, the developed application is capable of analyzing data at speeds that exceed the typical image acquisition rates of digital cameras (30 fps), opening the interesting prospect of realizing a low-cost and practical tool to study systems with many moving objects, mostly but not exclusively, biological ones. Besides its practical applications, the procedure presented here marks the first step towards the automatic extraction of effective equations of motion of many-body soft flowing systems.

12.
Phys Rev E ; 97(3-1): 033308, 2018 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-29776036

RESUMO

We present a lattice Boltzmann model for charged leaky dielectric multiphase fluids in the context of electrified jet simulations, which are of interest for a number of production technologies including electrospinning. The role of nonlinear rheology on the dynamics of electrified jets is considered by exploiting the Carreau model for pseudoplastic fluids. We report exploratory simulations of charged droplets at rest and under a constant electric field, and we provide results for charged jet formation under electrospinning conditions.

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