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A simple model was constructed to describe the polar ordering of non-centrosymmetric supramolecular aggregates formed by self assembling triblock rodcoil polymers. The aggregates are modeled as dipoles in a lattice with an Ising-like penalty associated with reversing the orientation of nearest neighbor dipoles. The choice of the potentials is based on experimental results and structural features of the supramolecular objects. For films of finite thickness, we find a periodic structure along an arbitrary direction perpendicular to the substrate normal, where the repeat unit is composed of two equal width domains with dipole up and dipole down configuration. When a short range interaction between the surface and the dipoles is included the balance between the up and down dipole domains is broken. Our results suggest that due to surface effects, films of finite thickness have a none zero macroscopic polarization, and that the polarization per unit volume appears to be a function of film thickness.
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We present a method for modelling textile structures, such as weft knits, on families of bicontinuous surfaces. By developing a tangible interpretation of mathematical theory, we combine perspectives of art, design, engineering, and science to understand how the architecture of the knit relates to its physical and mathematical properties. While modelling and design tools have become ubiquitous in many industries, there is still a significant lack of predictive advanced manufacturing techniques available for the design and manufacture of textiles. We describe a mathematical structure as a system for dynamic modelling of textiles in the form of a physical prototype which may be used to inform and predict relevant textile parameters prior to fabrication. This includes dimensional changes due to yarn relaxation, which would streamline production of knit textiles for industry, makers and textile artists.
We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular we compute the density of states of adsorbed polymers as a function of the number of ligand-receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking.
We investigate the transition between the Cassie-Baxter and Wenzel states of a slowly evaporating, micron-scale drop on a superhydrophobic surface. In two dimensions analytical results show that there are two collapse mechanisms. For long posts the drop collapses when it is able to overcome the free energy barrier presented by the hydrophobic posts. For short posts, as the drop loses volume, its curvature increases allowing it to touch the surface below the posts. We emphasise the importance of the contact line retreating across the surface as the drop becomes smaller: this often preempts the collapse. In a quasi-three dimensional simulation we find similar behaviour, with the additional feature that the drop can de-pin from all but the peripheral posts, so that its base resembles an inverted bowl.
When a drop of water is placed on a rough surface, there are two possible extreme regimes of wetting: the one called Cassie-Baxter (CB) with air pockets trapped underneath the droplet and the one characterized by the homogeneous wetting of the surface, called the Wenzel (W) state. A way to investigate the transition between these two states is by means of evaporation experiments, in which the droplet starts in a CB state and, as its volume decreases, penetrates the surfaces grooves, reaching a W state. Here we present a theoretical model based on the global interfacial energies for CB and W states that allows us to predict the thermodynamic wetting state of the droplet for a given volume and surface texture. We first analyze the influence of the surface geometric parameters on the droplets final wetting state with constant volume, and show that it depends strongly on the surface texture. We then vary the volume of the droplet keeping fixed the geometric surface parameters to mimic evaporation and show that the drop experiences a transition from the CB to the W state when its volume reduces, as observed in experiments. To investigate the dependency of the wetting state on the initial state of the droplet, we implement a cellular Potts model in three dimensions. Simulations show a very good agreement with theory when the initial state is W, but it disagrees when the droplet is initialized in a CB state, in accordance with previous observations which show that the CB state is metastable in many cases. Both simulations and theoretical model can be modified to study other types of surface.
Rough or textured hydrophobic surfaces are dubbed superhydrophobic due to their numerous desirable properties, such as water repellency and interfacial slip. Superhydrophobicity stems from an aversion for water to wet the surface texture, so that a water droplet in the superhydrophobic Cassie state, contacts only the tips of the rough hydrophobic surface. However, superhydrophobicity is remarkably fragile, and can break down due to the wetting of the surface texture to yield the Wenzel state under various conditions, such as elevated pressures or droplet impact. Moreover, due to large energetic barriers that impede the reverse (dewetting) transition, this breakdown in superhydrophobicity is widely believed to be irreversible. Using molecular simulations in conjunction with enhanced sampling techniques, here we show that on surfaces with nanoscale texture, water density fluctuations can lead to a reduction in the free energetic barriers to dewetting by circumventing the classical dewetting pathways. In particular, the fluctuation-mediated dewetting pathway involves a number of transitions between distinct dewetted morphologies, with each transition lowering the resistance to dewetting. Importantly, an understanding of the mechanistic pathways to dewetting and their dependence on pressure, allows us to augment the surface texture design, so that the barriers to dewetting are eliminated altogether and the Wenzel state becomes unstable at ambient conditions. Such robust surfaces, which defy classical expectations and can spontaneously recover their superhydrophobicity, could have widespread importance, from underwater operation to phase change heat transfer applications.
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