Search

Theintriguing ability of certain surfactant molecules to drivethe superspreading of liquids to complete wetting on hydrophobic substratesis central to numerous applications that range from coating flow technologyto enhanced oil recovery. Despite significant experimental efforts,the precise mechanisms underlying superspreading remain unknown todate. Here, we isolate these mechanisms by analyzing coarse-grainedmolecular dynamics simulations of surfactant molecules of varyingmolecular architecture and substrate affinity. We observe that forsuperspreading to occur, two key conditions must be simultaneouslysatisfied: the adsorption of surfactants from the liquid–vaporsurface onto the three-phase contact line augmented by local bilayerformation. Crucially, this must be coordinated with the rapid replenishmentof liquid–vapor and solid–liquid interfaces with surfactantsfrom the interior of the droplet. This article also highlights andexplores the differences between superspreading and conventional surfactants,paving the way for the design of molecular architectures tailoredspecifically for applications that rely on the control of wetting. [ABSTRACT FROM AUTHOR]

The self-sustained motion of fluids on gradient substrates is a spectacular phenomenon, which can be employed and controlled in applications by carefully engineering the substrate properties. Here, we report on a design of a gel substrate with stiffness gradient, which can cause the spontaneous motion of a droplet along (durotaxis) or to the opposite (antidurotaxis) direction of the gradient, depending on the droplet affinity to the substrate. By using extensive molecular dynamics simulations of a coarse-grained model, we find that the mechanisms of the durotaxis and antidurotaxis droplet motion are distinct, require the minimization of the interfacial energy between the droplet and the substrate, and share similarities with those mechanisms previously observed for brush substrates with stiffness gradient. Moreover, durotaxis motion takes place over a wider range of affinities and is generally more efficient (faster motion) than antidurotaxis. Thus, our study points to further possibilities and guidelines for realizing both antidurotaxis and durotaxis motion on the same gradient substrate for applications in microfluidics, energy conservation, and biology.

The blood-brain barrier (BBB) is a physical barrier that regulates the homeostasis of the neural microenvironment. A relative estimate of the BBB permeability, which is important for drug design, may be experimentally provided by the logBB (the blood-brain concentration ratio) and the logPS (permeability-surface-area product), while many computational methods aim to identify key properties that correlate well with these quantities. Although currently existing computational methods (e.g., quantitative structure activity relation) have made a significant contribution in screening various compounds that could potentially translocate through the BBB, they are unable to provide a physical explanation of the underlying processes and they can often be computationally demanding. Here, we use steered molecular dynamics simulation to estimate the BBB permeability of various compounds on the basis of simple lipid-membrane models by computing the nonequilibrium work, W neq , produced by pulling the compounds through the membrane. We found that the values of W neq correlate remarkably well with logBB and logPS for a range of compounds and different membrane types and pulling speeds, independently of the choice of force field. Moreover, our results provide insight into the role of hydrogen bonds, the energetic barriers, and the forces exerted on the ligands during their pulling. Our method is computationally easy to implement and fast. Therefore, we anticipate that it could provide a reliable prescreening tool for estimating the relative permeability of the BBB to various substances.

Despite decades of research, the modeling of moving contact lines has remained a formidable challenge in fluid dynamics whose resolution will impact numerous industrial, biological, and daily life applications. On the one hand, molecular dynamics (MD) simulation has the ability to provide unique insight into the microscopic details that determine the dynamic behavior of the contact line, which is not possible with either continuum-scale simulations or experiments. On the other hand, continuum-based models provide a link to the macroscopic description of the system. In this Feature Article, we explore the complex range of physical factors, including the presence of surfactants, which governs the contact line motion through MD simulations. We also discuss links between continuum- and molecular-scale modeling and highlight the opportunities for future developments in this area.

The application of coarse-grained (CG) models in biology is essential to access large length and time scales required for the description of many biological processes. The ELNEDIN protein model is based on the well-known MARTINI CG force-field and incorporates additionally harmonic bonds of a certain spring constant within a defined cutoff distance between pairs of residues, in order to preserve the native structure of the protein. In this case, the use of unbreakable harmonic bonds hinders the study of unfolding and folding processes. To overcome this barrier we have replaced the harmonic bonds with Lennard-Jones interactions based on the contact map of the native protein structure as is done in Go̅-like models. This model exhibits very good agreement with all-atom simulations and the ELNEDIN. Moreover, it can capture the structural motion linked to particular catalytic activity in the Man5B protein, in agreement with all-atom simulations. In addition, our model is based on the van der Waals radii, instead of a cutoff distance, which results in a smaller contact map. In conclusion, we anticipate that our model will provide further possibilities for studying biological systems based on the MARTINI CG force-field by using advanced-sampling methods, such as parallel tempering and metadynamics.

We investigate the self-assembly of bottle-brush block copolymers into well-defined periodic morphologies by using molecular dynamics simulations of a bead-spring model. The microphase separation is driven by the chemical incompatibility between the different blocks of side chains leading to the formation of two- and three-domain lamellae and hexagonally packed cylinders. The molecular asymmetry required for the formation of cylindrical domains is not introduced by the difference in volume fractions, but by the asymmetry of the side chain lengths. Such behavior deviates significantly from what is typically known for linear block copolymers. The obtained morphology maps provide a genuine way of understanding the role of molecular architecture in achieving experimentally desired structures for nanoporous and photonic materials based on the self-assembly of bottle-brush block copolymers.