Adhesion of perfume-filled microcapsules to model fabric surfaces

The retention and adhesion of melamine formaldehyde (MF) microcapsules on a model fabric surface in aqueous solution were investigated using a customised flow chamber technique and atomic force microscopy (AFM). A cellulose film was employed as a model fabric surface. Modification of the cellulose with chitosan was found to increase the retention and adhesion of microcapsules on the model fabric surface. The AFM force–displacement data reveal that bridging forces resulting from the extension of cellulose chains dominate the adhesion between the microcapsule and the unmodified cellulose film, whereas electrostatic attraction helps the microcapsules adhere to the chitosan-modified cellulose film. The correlation between results obtained using these two complementary techniques suggests that the flow chamber device can be potentially used for rapid screening of the effect of chemical modification on the adhesion of microparticles to surfaces, reducing the time required to achieve an optimal formulation

Coupling the Leidenfrost effect and elastic deformations to power sustained bouncing

The Leidenfrost effect occurs when an object near a hot surface vaporizes rapidly enough to lift itself up and hover. Although well-understood for liquids and stiff sublimable solids, nothing is known about the effect with materials whose stiffness lies between these extremes. Here we introduce a new phenomenon that occurs with vaporizable soft solids: the elastic Leidenfrost effect. By dropping hydrogel spheres onto hot surfaces we find that, rather than hovering, they energetically bounce several times their diameter for minutes at a time. With high-speed video during a single impact, we uncover high-frequency microscopic gap dynamics at the sphere-substrate interface. We show how these otherwise-hidden agitations constitute work cycles that harvest mechanical energy from the vapour and sustain the bouncing. Our findings unleash a powerful and widely applicable strategy for injecting mechanical energy into soft materials, with relevance to fields ranging from soft robotics and metamaterials to microfluidics and active matter

Atomic force microscopy analysis of nanoparticles in non-ideal conditions

Nanoparticles are often measured using atomic force microscopy or other scanning probe microscopy methods. For isolated nanoparticles on flat substrates, this is a relatively easy task. However, in real situations, we often need to analyze nanoparticles on rough substrates or nanoparticles that are not isolated. In this article, we present a simple model for realistic simulations of nanoparticle deposition and we employ this model for modeling nanoparticles on rough substrates. Different modeling conditions (coverage, relaxation after deposition) and convolution with different tip shapes are used to obtain a wide spectrum of virtual AFM nanoparticle images similar to those known from practice. Statistical parameters of nanoparticles are then analyzed using different data processing algorithms in order to show their systematic errors and to estimate uncertainties for atomic force microscopy analysis of nanoparticles under non-ideal conditions. It is shown that the elimination of user influence on the data processing algorithm is a key step for obtaining accurate results while analyzing nanoparticles measured in non-ideal conditions