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An aqueous hyaluronic acid (HA(aq)) pericellular coat, when mediating the tactile aspect of cellular contact inhibition, has three tasks: interface formation, mechanical signal transmission and interface separation. To quantify the interfacial adhesive behavior of HA(aq), we induce simultaneous interface formation and separation between HA(aq) and a model hydrophobic, hysteretic Si-SAM surface. While surface tension γ remains essentially constant, interface formation and separation depend greatly on concentration (5 ≤ C ≤ 30 mg mL(-1)), molecular weight (6 ≤ MW ≤ 2000 kDa) and interfacial velocity (0 ≤ V ≤ 3 mm s(-1)), each of which affect shear elastic and loss moduli G′ and G′′, respectively. Viscoelasticity dictates the mode of interfacial motion: wetting-dewetting, capillary necking, or rolling. Wetting-dewetting is quantified using advancing and receding contact angles θ(A) and θ(R), and the hysteresis between them, yielding data landscapes for each C above the [MW, V] plane. The landscape sizes, shapes, and curvatures disclose the interplay, between surface tension and viscoelasticity, which governs interfacial dynamics. Gel point coordinates modulus G and angular frequency ω appear to predict wetting-dewetting (G75 ω0.2), capillary necking (75 ω0.2G200 ω0.075) or rolling (G200ω0.075). Dominantly dissipative HA(aq) sticks to itself and distorts irreversibly before separating, while dominantly elastic HA(aq) makes contact and separates with only minor, reversible distortion. We propose the dimensionless number (G′V)/(ω(r)γ), varying from 10(-5) to 10(3) in this work, as a tool to predict the mode of interface formation-separation by relating interfacial kinetics with bulk viscoelasticity. Cellular contact inhibition may be thus aided or compromised by physiological or interventional shifts in [C, MW, V], and thus in (G′V)/(ω(r)γ), which affect both mechanotransduction and interfacial dynamics. These observations, understood in terms of physical properties, may be broadened to probe interfacial dynamics of other viscoelastic aqueous biopolymers.

Diffusion of small to medium sized molecules in polymeric medical device materials underlies a broad range of public health concerns related to unintended leaching from or uptake into implantable medical devices. However, obtaining accurate diffusion coefficients for such systems at physiological temperature represents a formidable challenge, both experimentally and computationally. While molecular dynamics simulation has been used to accurately predict the diffusion coefficients, D, of a handful of gases in various polymers, this success has not been extended to molecules larger than gases, e.g., condensable vapours, liquids, and drugs. We present atomistic molecular dynamics simulation predictions of diffusion in a model drug eluting system that represent a dramatic improvement in accuracy compared to previous simulation predictions for comparable systems. We find that, for simulations of insufficient duration, sub-diffusive dynamics can lead to dramatic over-prediction of D. We present useful metrics for monitoring the extent of sub-diffusive dynamics and explore how these metrics correlate to error in D. We also identify a relationship between diffusion and fast dynamics in our system, which may serve as a means to more rapidly predict diffusion in slowly diffusing systems. Our work provides important precedent and essential insights for utilizing atomistic molecular dynamics simulations to predict diffusion coefficients of small to medium sized molecules in condensed soft matter systems.