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Abstract:

Polymeric, soft, and biological materials exhibit viscoelasticity, which is a time dependent mechanical response to deformation. Material viscoelasticity emerges from the movement of a material's constituent molecules at the nano- and microscale in response to applied deformation. Therefore, viscoelastic properties depend on the speed at which a material is deformed. Recent technological advances, especially in atomic force microscopy (AFM), have provided tools to measure and map material viscoelasticity with nanoscale resolution. However, to obtain additional information about the viscoelastic behavior of a material from such measurements, theoretical grounding during data analysis is required. For example, commercially available bimodal AFM imaging maps two different viscoelastic properties of a sample, the storage modulus, E′, and loss tangent, tan δ, with each property being measured by a different resonance frequency of the AFM cantilever. While such techniques provide high resolution maps of E′ and tan δ, the different measurement frequencies make it difficult to calculate key viscoelastic properties of the sample such as: the model of viscoelasticity that describes the sample, the loss modulus, E′′, at either frequency, elasticity E, viscosity η, and characteristic response times τ. To overcome this difficulty, we present a new data analysis procedure derived from linear viscoelasticity theory. This procedure is applied and validated by performing amplitude modulation–frequency modulation (AM–FM) AFM, a commercially available bimodal imaging technique, on a styrene–butadiene rubber (SBR) with known mechanical behavior. The new analysis procedure correctly identified the type of viscoelasticity exhibited by the SBR and accurately calculated SBR E, η, and τ, providing a useful means of enhancing the amount of information gained about a sample's nanoscale viscoelastic properties from bimodal AFM measurements. Additionally, being derived from fundamental models of linear viscoelasticity, the procedure can be employed for any technique where different viscoelastic properties are measured at different and discrete frequencies with applied deformations in the linear viscoelastic regime of a sample.

Abstract:

Controlling the self‐assembly of nanoparticle building blocks into macroscale soft matter structures is an open question and of fundamental importance to fields as diverse as nanomedicine and next‐generation energy storage. Within the vast library of nanoparticles, the fullerenes—a family of quasi‐spherical carbon allotropes—are not explored beyond the most common, C60. Herein, a facile one‐pot method is demonstrated for functionalizing fullerenes of different sizes (C60, C70, C84, and C90–92), yielding derivatives that self‐assemble in aqueous solution into supramolecular hydrogels with distinct hierarchical structures. It is shown that the mechanical properties of these resultant structures vary drastically depending on the starting material. This work opens new avenues in the search for control of macroscale soft matter structures through tuning of nanoscale building blocks.

Abstract:

Neural electrodes have recently been developed with surface modifications of conductive polymers, in particular poly­(3,4-ethylenedioxythiophene) (PEDOT), and extensively studied for their roles in recording and stimulation, aiming to improve their biocompatibility. In this work, the implications for the design of practical neural sensors are clarified, and systematic procedures for their preparation are reported. In particular, this study introduces the use of in vitro double electrode experiments to mimic the responses of neural electrodes with a focus on signal-recording electrodes modified with PEDOT. Specifically, potential steps on one unmodified electrode in an array are used to identify the responses for PEDOT doped with different anions and compared with that of a bare platinum (Pt) electrode. The response is shown to be related to the rearrangement of ions in solution near the detector electrode resulting from the potential step, with a current transient seen at the detector electrode. A rapid response for PEDOT doped with chloride (ca. 0.04 s) ions was observed and attributed to the fast movement of chloride ions in and out of the polymer film. In contrast, PEDOT doped with poly­(styrenesulfonate) (PSS) responds much slower (ca. 2.2 s), and the essential immobility of polyanion constrains the direction of current flow.

Abstract:

Polymeric materials are widely used in industries ranging from automotive to biomedical. Their mechanical properties play a crucial role in their application and function and arise from the nanoscale structures and interactions of their constitutive polymer molecules. Polymeric materials behave viscoelastically, i.e., their mechanical responses depend on the time scale of the measurements; quantifying these time-dependent rheological properties at the nanoscale is relevant to develop, for example, accurate models and simulations of those materials, which are needed for advanced industrial applications. In this paper, an atomic force microscopy (AFM) method based on the photothermal actuation of an AFM cantilever is developed to quantify the nanoscale loss tangent, storage modulus, and loss modulus of polymeric materials. The method is then validated on styrene–butadiene rubber (SBR), demonstrating the method’s ability to quantify nanoscale viscoelasticity over a continuous frequency range up to 5 orders of magnitude (0.2–20,200 Hz). Furthermore, this method is combined with AFM viscoelastic mapping obtained with amplitude modulation–frequency modulation (AM–FM) AFM, enabling the extension of viscoelastic quantification over an even broader frequency range and demonstrating that the novel technique synergizes with preexisting AFM techniques for quantitative measurement of viscoelastic properties. The method presented here introduces a way to characterize the viscoelasticity of polymeric materials and soft and biological matter in general at the nanoscale for any application.