Related papers: Exploring Nanofibrous Networks with X-ray Photon C…
Learning models of complex spatial density functions, representing the steady-state density of mobile nodes moving on a two-dimensional terrain, can assist in network design and optimization problems, e.g., by accelerating the computation…
Hollow-core fibers offer superior loss and latency characteristics compared to solid-core alternatives, yet the geometric complexity of nested antiresonance nodeless fibers (NANFs) makes traditional optimization computationally prohibitive.…
Networks of nanowires and nanosheets are important for many applications in printed electronics. However, the network conductivity and mobility are usually limited by the inter-particle junction resistance, a property that is challenging to…
A practical, biologically motivated case of protein complexes (immunoglobulin G and FcRII receptors) moving on the surface of mastcells, that are common parts of an immunological system, is investigated. Proteins are considered as…
Optoelectronic micro- and nanostructures have a vast parameter space to explore for modification and optimisation of their functional performance. This paper reports on a data-led approach using high-throughput single nanostructure…
Microgels are elastic and deformable particles with a hybrid nature between that of polymers and colloids and unconventional behaviours with respect to hard colloids. We investigated the dynamics of a soft microgel made of interpenetrated…
Harnessing the optical properties of noble metals down to the nanometer-scale is a key step towards fast and low-dissipative information processing. At the 10-nm length scale, metal crystallinity and patterning as well as probing of surface…
Graph Nerual Networks (GNNs) are effective models in graph embedding. It extracts shallow features and neighborhood information by aggregating neighbor information to learn the embedding representation of different nodes. However, the local…
The implementation of natural and artificial proteins with designer properties and functionalities offers unparalleled opportunity for functional nanoarchitectures formed through self-assembly. However, to exploit the opportunities offered…
Active materials take advantage of their internal sources of energy to self-organize in an automated manner. This feature provides a novel opportunity to design micron-scale machines with minimal required control. However, self-organization…
Control and transport of nanoscale objects in fluids is challenging because of the unfavorable scaling of most interaction mechanisms to small length scales. We design energy landscapes for nanoparticles by accurately shaping the geometry…
The simulation of fluid flow in real, multiscale porous media remains challenging due to the complexity of nanoscale phenomena and the difficulty of developing upscaling methodologies. In this study, we introduce a multiscale filtration…
X-ray photon correlation spectroscopy was used to probe the diffusive dynamics of colloidal particles in a shear flow. Combining X-ray techniques with microfluidics is an experimental strategy that reduces the risk of x-ray induced beam…
Modern microelectronic devices are composed of interfaces between a large number of materials, many of which are in amorphous or polycrystalline phases. Modeling such non-crystalline materials using first-principles methods such as density…
Diffusion MRI tractography is an important tool for identifying and analyzing the intracranial course of cranial nerves (CNs). However, the complex environment of the skull base leads to ambiguous spatial correspondence between diffusion…
The miniaturization of diagnostic devices that exploit optical detection schemes requires the design of light-sources combining small size, high performance for effective excitation of chromophores, and mechanical flexibility for easy…
Nanopores are both a tool to study single-molecule biophysics and nanoscale ion transport, but also a promising material for desalination or osmotic power generation. Understanding the physics underlying ion transport through nano-sized…
Functional connectivity estimates are highly sensitive to analysis choices and can be dominated by noise when the number of sampled time points is small relative to network dimensionality. This issue is particularly acute in fMRI, where…
The diffusive transport of biased Brownian particles in a two-dimensional symmetric channel is investigated numerically considering both the no-flow and the reflection boundary conditions at the channel boundaries. Here, the geometrical…
Fibrous networks are ideal functional materials since they provide mechanical rigidity at low weight. Such structures are omnipresent in natural biomaterials from cells to tissues, as well as in man-made materials from polymeric composites…