Related papers: Ridge approximation for thin nematic polymer netwo…
A crucial property for achieving secure, trustworthy and interpretable deep learning systems is their robustness: small changes to a system's inputs should not result in large changes to its outputs. Mathematically, this means one strives…
We start from a variational model for nematic elastomers that involves two energies: mechanical and nematic. The first one consists of a nonlinear elastic energy which is influenced by the orientation of the molecules of the nematic…
We apply Physics-Informed Neural Networks (PINNs) for solving identification problems of nonhomogeneous materials. We focus on the problem with a background in elasticity imaging, where one seeks to identify the nonhomogeneous mechanical…
The influence of the energy dependence of the free NN t-matrix on the optical potential of nucleon-nucleus elastic scattering is investigated within the context of a full-folding model based on the impulse approximation. The treatment of…
We consider a thin elastic sheet in the shape of a disk whose reference metric is that of a singular cone. I.e., the reference metric is flat away from the center and has a defect there. We define a geometrically fully nonlinear free…
Rod-shaped colloids with attractive tips can form linear aggregates that may subsequently undergo hierarchical self-assembly into nematic fluids. Inspired by recent modelling efforts on chromonic liquid crystals, composed of discotic…
We theoretically study the nematic ordering transition of rods that are able to elastically adjust their mutually excluded volumes. The model rods, which consist of a hard core surrounded by a deformable shell, mimic the structure of…
We develop a methodology for the calculation of surface free energies based on the probability distribution of a wandering interface. Using a simple extension of the NpT sampling, we allow the interface area to randomly probe the available…
Reconstituted filamentous actin networks with myosin motor proteins form active gels, in which motor proteins generate forces that drive the network far from equilibrium. This motor activity can also strongly affect the network elasticity;…
Active semiflexible filament collectives, ranging from motor-driven cytoskeletal filaments to slender organisms such as cyanobacteria and worm aggregates, abound in nature. Yet how activity and flexibility jointly govern their organization,…
Designing reconfigurable materials based on deformable nanoparticles (NPs) hinges on an understanding of the energetically-favored shapes these NPs can adopt. Using simulations, we show that hollow, deformable patchy NPs tailored with…
We employ computer simulations and thermodynamic integration to analyse the effects of bending rigidity and slit confinement on the free energy cost of tying knots, $\Delta F_{\rm knotting}$, on polymer chains under tension. A…
A self-consistent model is developed to investigate attachment / detachment kinetics of two soft, deformable microspheres with irregular surface and coated with flexible binding ligands. The model highlights how the microscale binding…
Neural plasticity is an important functionality of human brain, in which number of neurons and synapses can shrink or expand in response to stimuli throughout the span of life. We model this dynamic learning process as an $L_0$-norm…
We have simulated the motion of a bead subjected to a constant force while embedded in a network of semiflexible polymers which can represent actin filaments. We find that the bead displacement obeys the power law x ~ t^alfa. After the…
Diamond, the hardest natural crystal, has attracted significant attention for its plasticity, which is reported to be determined by its stacking faults. Studies mainly focused on one-dimensional linear pathways in stacking transitions,…
In this paper, we investigate the geometric structure of activation spaces of fully connected layers in neural networks and then show applications of this study. We propose an efficient approximation algorithm to characterize the convex…
The recent discovery of electro-active polymers has shown great promises in the field of soft robotics, and was logically followed by experimental, numerical and theoretical developments. Most of these studies were concerned with systems…
We study the structural and dynamical mechanisms of reinforcement of a polymer nanocomposite (PNC) via coarse-grained molecular dynamics simulations. In a regime of strong polymer-filler interactions, the stress at failure of the PNC is…
Spin excitation in a nano-graphite ribbon with zigzag edges is investigated theoretically. Due to the strongly localized nature of the states near Fermi energy, the effective Hamiltonian for the low energy physics is given by Heisenberg…