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Open Access Publications from the University of California

Visualizing soft material and ionic liquid dynamics using interferometric and Fourier microscopy techniques

  • Author(s): Bayles, Alexandra Victoria
  • Advisor(s): Squires, Todd M
  • Helgeson, Matthew E
  • et al.

This work extends and exploits two new video microscopy platforms to perform high-throughput characterization of soft material dynamics. The first portion uses microfluidic Fabry-Perot interferometry to provide mechanistic insight into gradient-driven diffusion of molecular solutes in ionic liquids. The second portion uses differential dynamic microscopy to measure rheological properties of viscoelastic materials.

Ionic liquids (ILs) are promising solvents that are poised to replace conventional industrial fluids in a number of separation and reaction processes. In these applications, ILs offer improved solute selectivity, energy efficient recyclability, higher loading capacity, and reduced environmental toxicity in comparison to traditional organic solvents. However, multiple IL-solute pairs are known to suffer from slow solute dynamics, which impede mass transfer in emerging IL technologies. Since slow solute diffusivity is commonly associated with high IL bulk viscosities, ILs are often selected from a vast ion design space on the basis of their viscosity–despite the fact that continuum viscosity based models provide inaccurate diffusivity predictions.

In part one of this work, we develop mechanistic understanding of anomalous diffusion in ILs, and use it to provide direct insight into solute transport limitations in ILs and develop quantitatively accurate analytic predictions of solute diffusivity. In our approach, we develop and employ a novel method, microfluidic Fabry-Perot interferometry, that enables label-free visualization of solute concentration fields as they evolve spatially and temporally. This technique is used to measure the gradient-driven sorption of solutes in three canonical IL-solute systems: (1) CO2 reactive absorption by amine-based ILs; (2) H2O sorption by methylimidazolium halide ILs; and (3) H2O sorption by poly(ethylene glycol) methylimidazolium ionogels. In system (1), the measured concentration profiles directly map the propagation of CO2 reaction fronts, and quantify the effect of viscosity increases upon sorption. In systems (2) and (3), the concentration profiles enable high-throughput extraction of composition dependent diffusivities over a broad phase space, and the development of mechanistically distinct transport models. Specifically, diffusion is modeled by an activated process of water molecules hopping between ion pairs where the magnitude of the electrostatic activation barrier follows the strength of hydrogen bonding with the methylimidazolium head group. We find that hydrogen bonding strength can be measured independently via 1H NMR, and subsequently used to calculate accurate solute diffusivities. We anticipate that the new conceptual frameworks developed using this visualization platform will improve a priori diffusivity predictions, help identify ion moieties that control diffusion, and ultimately enable rational design of task-specific ILs.

Engineered soft materials are often designed around their dynamic properties – e.g. diffusivities, viscous and elastic moduli. Navigating broad formulation-design space requires rapid, accurate, material-robust and volume-efficient tools to measure these critical properties. In the second portion of this work, we report how to measure critical rheological properties using differential dynamic microscopy (DDM). DDM measures the ensemble dynamics of colloidal and complex fluid motion by analyzing statistical intensity fluctuations due to scatterer motion in optical video micrographs. Here, we recast conventional DDM analysis in terms of a particle-displacement theoretical framework. The new framework directly illustrates how DDM can be used to (1) extract the mean squared displacement of Brownian particles embedded in soft materials, (2) measure microrheology of viscoelastic materials, and (3) analyze images obtained in previously elusive imaging modes. These predictions are experimentally verified by conducting DDM on dilute probes in Newtonian fluids, viscoelastic wormlike micelles, and crosslinking polymer gels. All analyses were performed using a software package, DDMCalc, that we developed and distributed. DDMCalc was the first DDM software package made publicly available. The examples and analyses expose the relative strengths and weaknesses of DDM compared to existing analysis techniques. Significantly, DDM retains all ensemble information encoded in the images, requires few user inputs, and can be applied to optically dense systems that would otherwise be difficult to measure using traditional multiple particle tracking or photocorrelation spectroscopy. These results show that DDM can extend the range of probe microrheology experiments, and highlight its potential as a high-throughput characterization platform.

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