A deep learning approach for designed diffraction-based acoustic patterning in microchannels

Abstract

Acoustic waves can be used to accurately position cells and particles and are appropriate for this activity owing to their biocompatibility and ability to generate microscale force gradients. Such fields, however, typically take the form of only periodic one or two-dimensional grids, limiting the scope of patterning activities that can be performed. Recent work has demonstrated that the interaction between microfluidic channel walls and travelling surface acoustic waves can generate spatially variable acoustic fields, opening the possibility that the channel geometry can be used to control the pressure field that develops. In this work we utilize this approach to create novel acoustic fields. Designing the channel that results in a desired acoustic field, however, is a non-trivial task. To rapidly generate designed acoustic fields from microchannel elements we utilize a deep learning approach based on a deep neural network (DNN) that is trained on images of pre-solved acoustic fields. We use then this trained DNN to create novel microchannel architectures for designed microparticle patterning. Microfluidic platforms are an important tool for precise micromanipulation, using force gradients on the length scale of cells and microparticles themselves. A major application space in microfluidics is the patterning and long-term retention of living cells; patterning is a powerful tool for the formation of cellular spheroids 1 , tissue engineering 2 , drug screening 1 and single-cell analysis 3 , cellular interactions 4 , and mechanobiology 5. The design of microfluidic systems for these activities, however, typically occurs on a first-principles basis and generally omits parametric optimization of the microchannel features. This has a large impact when hydrodynamic forces are involved, since the channel geometry can affect how, for example, lift and drag forces are distributed. In the case of hydrodynamic effects there has been some work using numerical simulations 6,7 to configure channels to optimize their mixing and dilution characteristics, showing the promise of modifying channel shapes for creating optimized microfluidic devices. Actively applied forces, rather than just hydrodynamic ones, however, are increasingly integrated into microfluidic devices for more refined and dynamic actuation. Acoustic fields are a particularly useful method for micromanipulation due to their biocompatibility, high force magnitudes arising from MPa order pressures and wavelengths that can match the length scale of individual cells. To date, acoustic fields have shown their capacity for versatile microscale actuation activities including patterning 8 , acoustic streaming 9-11 , droplet manipulation 12 , cell cultures 13,14 , mixing 15,16 and sorting 8 , with actuation down to the single cell level 12,17. In the case of patterning, these fields have typically been limited to creating simple lines 18 or grids 19 of cells and microparticles due to the limitations imposed by the transducers and channel geometries. For the most part these ...

The role of channel height and actuation method on particle manipulation in surface acoustic wave (SAW)-driven microfluidic devices

“…As such, we term this diffractive acoustic SAW (DASAW). DASAW principles have been demonstrated and explored in some of our recent work, principally from the perspective of predicting the spatial periodicity of the diffractive fringes that develop as a function of fluid/substrate properties, acoustic wavelength and the orientation of channel walls to the TSAW propagation direction (Devendran et al 2017;Collins et al 2018Collins et al , 2019O'Rorke et al 2018;Devendran et al 2020;Raymond et al 2020). This present work, however, seeks to explore DASAW from the perspective of the sizedependent effects on particles, especially in comparison to those from more conventional SSAW-driven systems.…”

Multiphysics microfluidics for cell manipulation and separation: a review

“…Acoustic manipulation is label-free and has shown excellent biocompatibility, making it feasible and versatile for use in the separation, [181][182][183] focusing, 184-186 trapping, 187,188 enrichment 189,190 and patterning 191,192 of various biological particles, such as blood cells, 193,194 CTCs, 156,195 bacteria, 196,197 extracellular vesicles, 198,199 lipoproteins, 200 and DNA. 201,202 This journal is © The Royal Society of Chemistry 2022…”

Acoustically Manipulating Internal Structure of Disk-in-Sphere Endoskeletal Droplets

“…Disk-in-sphere endoskeletal droplets consisting of solid perfluorododecane (PFDD, C12F26, s=1.73 g/cm 3 , cs=641 m/s 22 ) and liquid perfluorohexane (PFH, C6F14, density =1.69 g/cm 3 and sound velocity 4 = 479 m/s 24 ) were fabricated using a flow focusing microfluidic channel (Fig. 1A, B, C).…”

“…Among the host of attractive and repulsive interactions available to colloidal particles [12][13][14][15] , acoustic radiation forces, induced by acoustic fields, have proved to be an efficient way to manipulate particles. Even though the particle responses to acoustic radiation forces have been used for applications such as particle separation [16][17][18][19] , particle manipulation 20,21 and assembly of complex structures 22,23 , the manipulation of internal structures within endoskeletal colloids has not yet been reported. In this work, two unprecedented phenomena were discovered.…”