Understanding hydrodynamic wear in self-similar superhydrophobic coatings subjected to rapid droplet impacts.

Superhydrophobic materials rely on both chemical apolarity and surface roughness to achieve the high contact angles and the low roll-off angles that lead to self-cleaning and antibacterial properties. Current superhydrophobic coatings tend to be delicate and lose their properties easily when subjected to droplet impact. Such impact deteriorates these coatings through hydrodynamic wear; changing structure, eroding hydrophobic chemistry, and quickly leading to full wet out of the substrate. In fact, hydrodynamic wear is more detrimental to coatings than seemingly more aggressive mechanical wear including scratching with sandpaper - a common approach used to claim both self-similarity of a material and extreme robustness against wear. What makes certain coatings more robust against hydrodynamic wear? To understand this answer, we systematically study ten disparate self-similar superhydrophobic coating approaches from academia to industry by subjecting them to hydrodynamic wear with rapid droplet impacts. We offer an iteration of a spinning disk methodology that enables parallel testing of multiple coatings simultaneously. We have developed an analytical model that accurately estimates the average size and velocity of droplets created from the spinning disk. We find rapid droplet impacts that simulate a medium rain can deteriorate most coatings within seconds or minutes, with certain exceptions lasting up to 22 days. The more resilient coatings share common attributes including robust apolar chemistry, hierarchal topography, and a slow loss of sacrificial material. The best performing coatings can be characterized using power-law relationships that parallel mechanical fatigue functions and provide a predictive quantitative metric for the performance of hydrophobic coatings. Overall, this paper offers a quantitative approach to hydrodynamic wear of self-similar superhydrophobic coatings.

Thermoformable Boron Nitride Based All-Ceramics.

Thermoforming processing, traditionally reserved for thermoplastic polymers and sheet metals, is extended here to boron-based all-ceramics. Specifically, sintered boron nitride composite sheets manufactured via a combined vibration and tape-casting photopolymerization process exhibit a highly oriented microstructure that allows these preform sheets to flow as viscous Bingham pseudoplastics during compression molding. These sintered all-ceramic preforms are thermoformed into thin, complex parts with features down to 200 µm. Further, a new workflow is leveraged to generate bespoke all-ceramic heat spreaders that can be press-fit onto printed circuit boards and outperform metal heat sinks as a low-profile thermal management solution. This work offers a route for other all-ceramics that may be thermoformed through first fabricating pre-forms with highly-ordered anisotropic microstructures.

Increasing efficiency and accuracy of magnetic interaction calculations in colloidal simulation through machine learning.

Calculating the magnetic interaction between magnetic particles that are positioned in close proximity to one another is a surprisingly challenging task. Exact solutions for this interaction exist either through numerical expansion of multipolar interactions or through solving Maxwell's equations with a finite element solver. These approaches can take hours for simple configurations of three particles. Meanwhile, across a range of scientific and engineering problems, machine learning approaches have been developed as fast computational platforms for solving complex systems of interest when large data sets are available. In this paper, we bring the touted benefits of recent advances in science-based machine learning algorithms to bear on the problem of modeling the magnetic interaction between three particles. We investigate this approach using diverse machine learning systems including physics informed neural networks. We find that once the training data has been collected and the model has been initiated, simulation times are reduced from hours to mere seconds while maintaining remarkable accuracy. Despite this promise, we also try to lay bare the current challenges of applying machine learning to these and more complex colloidal systems.

Enhanced diffusion and magnetophoresis of paramagnetic colloidal particles in rotating magnetic fields.

Dispersions of paramagnetic colloids can be manipulated with external magnetic fields to assemble structures via dipolar assembly and control transport via magnetophoresis. For fields held steady in time, the dispersion structure and dynamic properties are coupled. This coupling can be problematic when designing processes involving field-induced forces, as particle aggregation competes against and hinders particle transport. Time-varying fields drive dispersions out-of-equilibrium, allowing the structure and dynamics to be tuned independently. Rotating the magnetic field direction using two biaxial fields is a particularly effective mode of time-variation and has been used experimentally to enhance particle transport. Fundamental transport properties, like the diffusivity and magnetophoretic mobility, dictate dispersions' out-of-equilibrium responses to such time-varying fields, and are therefore crucial to understand to effectively design processes utilizing rotating fields. However, a systematic study of these dynamic quantities in rotating fields has not been performed. Here, we investigate the transport properties of dispersions of paramagnetic colloids in rotating magnetic fields using dynamic simulations. We find that self-diffusion of particles is enhanced in rotating fields compared to steady fields, and that the self-diffusivity in the plane of rotation reaches a maximum value at intermediate rotation frequencies that is larger than the Stokes-Einstein diffusivity of an isolated particle. We also show that, while the magnetophoretic velocity of particles through the bulk in a field gradient decreases with increasing rotation frequency, the enhanced in-plane diffusion allows for faster magnetophoretic transport through porous materials in rotating fields. We examine the effect of porous confinement on the transport properties in rotating fields and find enhanced diffusion at all pore sizes. The confined and bulk values of the transport properties are leveraged in simple models of magnetophoresis through tortuous porous media.

Polypropylene crystallization at an alumina interface using single walled carbon nanotubes.

Interfaces play an important and often limiting role in the mechanical, thermal, and electrical performance of composite materials. Here we suggest a novel method to improve the interfacial interaction in polypropylene-alumina composites using single-walled carbon nanotubes (SWNTs) to nucleate lamellar crystals at the interface. Macroscopic alumina substrates are used to determine the ideal crystallization parameters and investigate the kinetics of crystal growth. SWNTs are uniformly adsorbed to the interface via Van der Waals interactions and lamellar crystals are grown on the surface using isothermal solution processing techniques. Avrami analysis of crystal surface coverage was used to confirm one-dimensional transcrystalline growth commonly seen with SWNT nucleated crystals. Scanning electron microscopy was used to confirm shish-kebab structures present at the SWNT-polypropylene interface. The determined crystallization parameters were used on colloidal solutions of alumina platelets to successfully create uniformly coated particles with an improved interface. This method shows promise for improving the interphase of semicrystalline polymer-ceramic composites to achieve excellent material properties.

Paramagnetic colloids: Chaotic routes to clusters and molecules.

We present computer simulations and experiments on dilute suspensions of superparamagnetic particles subject to rotating magnetic fields. We focus on chains of four particles and their decay routes to stable structures. At low rates, the chains track the external field. At intermediate rates, the chains break up but perform a periodic (albeit complex) motion. At sufficiently high rates, the chains generally undergo chaotic motion at short times and decay to either closely packed clusters or more dispersed, colloidal molecules at long times. We show that the transition out of the chaotic states can be described as a Poisson process in both simulation and experiment.

Assembling particle clusters with incoherent 3D magnetic fields.

Directed assembly of particle suspensions in massively parallel formats, such as with magnetic fields, has application in rheological control, smart drug delivery, and active colloidal devices from optical materials to microfluidics. At the heart of these applications lies a control optimization problem for driving the assembly and dissolution of highly monodisperse particle clusters. For magnetic field control, most attention to-date has been centered around in-phase coherent magnetic fields. Instead, we investigate a family of incoherent 3D magnetic fields that are capable of creating controlled and tunable particle assemblies such as dimers, trimers, and quadramers. These field functions can be tuned to assemble monodisperse clusters with long term stability and can quickly switch the clusters between different states. This subset of three-dimensional field functions that we have studied demonstrates the rich phase space available to tune colloidal suspensions with magnetic fields.

Designing bioinspired composite reinforcement architectures via 3D magnetic printing.

Discontinuous fibre composites represent a class of materials that are strong, lightweight and have remarkable fracture toughness. These advantages partially explain the abundance and variety of discontinuous fibre composites that have evolved in the natural world. Many natural structures out-perform the conventional synthetic counterparts due, in part, to the more elaborate reinforcement architectures that occur in natural composites. Here we present an additive manufacturing approach that combines real-time colloidal assembly with existing additive manufacturing technologies to create highly programmable discontinuous fibre composites. This technology, termed as '3D magnetic printing', has enabled us to recreate complex bioinspired reinforcement architectures that deliver enhanced material performance compared with monolithic structures. Further, we demonstrate that we can now design and evolve elaborate reinforcement architectures that are not found in nature, demonstrating a high level of possible customization in discontinuous fibre composites with arbitrary geometries.

Toward Accumulation of Magnetic Nanoparticles into Tissues of Small Porosity.

Magnetic concentration of drug-laden magnetic nanoparticles has been proven to increase the delivery efficiency of treatment by 2-fold. In these techniques, particles are concentrated by the presence of a magnetic source that delivers a very high magnetic field and a strong magnetic field gradient. We have found that such magnetic conditions cause even 150 nm particles to aggregate significantly into assemblies that exceed several micrometers in length within minutes. Such assembly sizes exceed the effective intercellular pore size of tumor tissues preventing these drug-laden magnetic nanoparticles from reaching their target sites. We demonstrate that by using dynamic magnetic fields instead, we can break up these magnetic nanoparticles while simultaneously concentrating them at target sites. The dynamic fields we investigate involve precessing the field direction while maintaining a field gradient. Manipulating the field direction drives the particles into attractive and repulsive configurations that can be tuned to assemble or disassemble these particle clusters. Here, we develop a simple analytic model to describe the kinetic thresholds of disassembly and we compare both experimental and numerical results of magnetic particle suspensions subjected to dynamic fields. Finally we apply these methods to demonstrate penetration in a porous scaffold with a similar pore size to that expected of a tumor tissue.

Understanding and overcoming shear alignment of fibers during extrusion.

Fiber alignment is the defining architectural characteristic of discontinuous fiber composites and is dictated by shear-dominated processing techniques including flow-injection molding, tape-casting, and mold-casting. However, recent colloidal assembly techniques have started to employ additional forces in fiber suspensions that have the potential to change the energy landscape of the shear-dominated alignment in conditions of flow. In this paper, we develop an energetics model to characterize the shear-alignment of rigid fibers under different flow conditions in the presence of magnetic colloidal alignment forces. We find that these colloidal forces can be sufficient to manipulate the energetic landscape and obtain tunable fiber alignment during flow within even small geometries, such as capillary flow. In most conditions, these colloidal forces work to freeze the fiber orientation during flow and prevent the structure disrupting phenomenon of Jeffrey's orbits that has been accepted to rule fiber suspensions under simple shear flow.