The Bayles Lab enjoys developing new tools to probe transport phenomena in complex fluids and gels. While we are primarily an experimental group, we write custom codes to extract quantitative information from video microscopy and to accelerate process design. We leverage these capabilities to perform fundamental research, to explore emergent technologies, and to provide insight into challenges faced by industrial partners. Active research areas include:
Sculpting hierarchical architectures using advective assembly
Natural materials such as tissue, bone, and wood exploit structural hierarchy to strengthen, functionalize, and organize composites. To build similar hierarchical architectures in synthetic products, engineers have devised assembly methods (e.g. self-, directed-, interfacial-) that manipulate attractive and repulsive interactions to template species. As a chemistry-agnostic alternative, we engineer fluidic networks to assemble advecting materials into designer patterns. The structures produced by this method are determined by the geometry of the network which contours laminar streamlines. We achieve voxelated control by constructing networks in a modular fashion from three primitive flow elements: cutting, adding, and rotating flows. Clever sequencing of these elements allows us to efficiently multiply the number of features while shrinking their characteristic dimension over several orders of magnitude. Advective assembly exchanges thermodynamic with rheological constraints, and thus provides access to an unexplored realm of material design. Our group is excited by the advantages advective assembly offers in multiple applications. By integrating advective assemblers into 3D printing nozzles, we extrude structured, multi-material filaments while mitigating challenges associated with throughput, interlayer adhesion, high pressure drops, topological constraints, and bio-compatibility. In product formulation, we strive to capitalize on the continuous operation and scalability of these deconstructed static mixers, and improve the efficiency of existing processes. In parallel with our experimental efforts, we are actively exploring how computational fluid dynamics, Boolean combinatorial logic, and machine learning can be used in inverse assembler design.
Programming soft actuator deformation using flow-templated architecture
Responsive soft materials experience changes in physical properties when their local environment is perturbed. Hydrogels are an emblematic example: the swollen polymer networks will release or absorb solvent depending on how sensitive their particular chemistry is to solvent quality, pH, temperature, light, and even magnetic and electrical fields. Swelling tends to be isotropic for gels with uniform structure. However, gels with spatially varying networks swell differentially, producing anisotropic macroscopic deformations. Bending, coiling, folding, and unidirectional expansion are useful motions for soft robotic, sensing, and haptic applications. Programing these deformations requires precise control over the gel architecture. Such control is typically achieved by fabricating actuators in multiple manufacturing steps, which require significant time, material, and process modification when switching between chemistries. As an alternative, we are developing single-step processing routes using our expertise in advective assembly. Engineered flows allow us to organize hydrogel precursors selectively and then secure their distribution via crosslinking. Since the fluidic structuring is geometrically dictated, we can harness the potential of easily accessible chemistries. We characterize our soft actuators by measuring the magnitude, direction, and dynamics of their motion in response to different stimuli. Macroscopic and microscopic video microscopy provide the means to examine swelling dynamics across multiple length scales, and develop a comprehensive model for actuator design.
Probing mass transport across interfaces using microfluidic interferometry
In addition to using microfluidics to build structured soft materials, our group also exploits microfluidics to characterize mass transport inside structured soft materials. Diffusion is an integral and inescapable process throughout the synthesis, use, and disposal of materials. Diffusion dictates the efficiency of separations, the dispersion of therapeutics, and can limit rates of reaction. As engineers, we are typically introduced to mass transport by solving Fick’s Laws for a concentration profile that evolves in space and time. While this is analytically tractable, simple solutions do not necessarily describe transport in complex environments. To characterize rich, non-trivial behavior in structured materials, experimentalists often use fluorescent, trackable species as proxies for the actual species of interest. In our group, we’re developing new tools to measure diffusion of native species without chemical modification. Microfluidic Fabry-Perot interferometry provides a window into the spatiotemporal evolution of concentration gradients. The geometry and flows within the device set boundary and initial conditions, while the semi-reflective surface coatings provide the means to measure small changes in refractive index (10-5) and subsequently concentration. Our goal is to refine and use these measurements to provide unique insight into transport limitations in a variety of industries.
