相关论文: Semiconductor sub-micro-/nanochannel networks by d…

Mathematical modeling has broad applications in neuroscience whether modeling the dynamics of a single synapse or an entire network of neurons. In Part I, we model vesicle replenishment and release at the photoreceptor synapse to better…

Following our recent interest in metamaterial-based devices supporting resonant tunneling, energy squeezing and supercoupling through narrow waveguide channels and bends, here we analyze the fundamental physical mechanisms behind this…

Deep learning has made significant applications in the field of data science and natural science. Some studies have linked deep neural networks to dynamic systems, but the network structure is restricted to the residual network. It is known…

With the recently massive development in convolution neural networks, numerous lightweight CNN-based image super-resolution methods have been proposed for practical deployments on edge devices. However, most existing methods focus on one…

Physical properties of composite materials can be pre-engineered by controlling their structure and composition at the mesoscale. Yet, approaches for achieving this are limited and rarely scalable. We introduce a new breed of self-assembled…

The loss surface of deep neural networks has recently attracted interest in the optimization and machine learning communities as a prime example of high-dimensional non-convex problem. Some insights were recently gained using spin glass…

Multipolar electromagnetic phenomena in sub-wavelength resonators are at the heart of metamaterial science and technology. In this letter, we demonstrate selective and enhanced coupling to specific multipole resonances via beam engineering.…

Nanofibrous networks are the foundation and natural building strategy for all life forms on our planet. Apart from providing structural integrity to cells and tissues, they also provide a porous scaffold allowing transport of substances,…

Wrinkles and nanobubbles are an integral and often unavoidable part of integrating 2D van der Waals semiconductors into actual device architectures. Despite their ubiquitous nature, quantitative correlation between such spatially…

Elastic sheets with macroscopic dimensions are easy to deform by bending and stretching. Yet shaping nanometric sheets by mechanical manipulation is hard. Here we show that nanoparticle self-assembly could be used to this end. We…

We considered diffusion-driven processes on small-world networks with distance-dependent random links. The study of diffusion on such networks is motivated by transport on randomly folded polymer chains, synchronization problems in…

Under supercoiling constraints, naked DNA, such as a large part of bacterial DNA, folds into braided structures called plectonemes. The double-helix can also undergo local structural transitions, leading to the formation of denaturation…

Light interference in strongly disordered photonic media can generate lasers where random modes are amplified in unpredictable way. The ease of fabrication, along with their low coherence caused by multiple small-linewidth peaks, made…

Coupling, synchronization, and non-linear dynamics of resonator modes are omnipresent in nature and highly relevant for a multitude of applications ranging from lasers to Josephson arrays and spin torque oscillators. Nanomechanical…

Deep residual networks were shown to be able to scale up to thousands of layers and still have improving performance. However, each fraction of a percent of improved accuracy costs nearly doubling the number of layers, and so training very…

We develop a model for gels and entangled solutions of semiflexible biopolymers such as F-actin. Such networks play a crucial structural role in the cytoskeleton of cells. We show that the rheologic properties of these networks can result…

Reinforcement learning is applied to the development of control strategies in order to reduce skin friction drag in a fully developed turbulent channel flow at a low Reynolds number. Motivated by the so-called opposition control (Choi et…

The off-normal ion irradiation of semiconductor materials is seen to induce nanopatterning effects. Different theories are proposed to explain the mechanisms that drive self-reorganization of amorphisable surfaces. One of the prominent…

Inspired by the diversity of biological neurons, quadratic artificial neurons can play an important role in deep learning models. The type of quadratic neurons of our interest replaces the inner-product operation in the conventional neuron…

Illumination of colloid sphere monolayers by circularly polarized beams enables the fabrication of concave patterns consisting of circular nanohole miniarrays that can be transferred into convex metal nanoparticle patterns via a lift-off…