相关论文: Calibrated absolute optical contrast for high-thro…

Anisotropic materials with different signs of components of the permittivity tensor are called indefinite materials. Known realizations of indefinite media suffer of high absorption losses. We show that periodic arrays of parallel carbon…

To help address the occlusion problem in panoptic segmentation and image understanding, this paper proposes a new large-scale dataset named COCO-OLAC (COCO Occlusion Labels for All Computer Vision Tasks), which is derived from the COCO…

Catalyst design is crucial for materials synthesis, especially for complex reaction networks. Strategies like collaborative catalytic systems and multifunctional catalysts are effective but face challenges at the nanoscale. Carbon nanotube…

Photodetectors play key roles in many applications such as remote sensing, night vision, reconnaissance, medical imaging, thermal imaging, and chemical detection. Several properties such as performance, reliability, ease of integration,…

Coherent anti-Stokes Raman scattering is a widely used imaging technique that provides chemical contrast without the need for labels, making it an extremely valuable tool in physics, chemistry, and biology. In this work, we explore its…

We study the behavior of charged spherical Au nanoparticles in a nanofluidic slit as a function of the separation of the symmetrically charged confining surfaces. A dedicated setup called the nano-fluidic confinement apparatus (NCA) allows…

The covalent functionalization of single-walled carbon nanotubes (SWCNTs) with luminescent quantum defects enables their application as near-infrared single-photon sources, as optical sensors, and for in-vivo tissue imaging. Tuning the…

Camouflaged Object Detection (COD) aims to segment targets that share extreme textural and structural similarities with their complex environments. Leveraging their capacity for long-range dependency modeling, Transformer-based detectors…

Deep convolutional neural networks have become a key element in the recent breakthrough of salient object detection. However, existing CNN-based methods are based on either patch-wise (region-wise) training and inference or fully…

Graph Neural Networks (GNNs) are widely used as the engine for various graph-related tasks, with their effectiveness in analyzing graph-structured data. However, training robust GNNs often demands abundant labeled data, which is a critical…

Coiled Carbon Nanotubes (CCNTs) are increasingly set to become a vital factor in the new generation of nanodevices and energy-absorbing materials due to their outstanding properties. In the following work, the multi-objective optimization…

While optical coherence tomography (OCT) provides a resolution down to 1 micrometer it has difficulties to visualize cellular structures due to a lack of scattering contrast. By evaluating signal fluctuations, a significant contrast…

Heterogeneous graph neural networks (HGNNs) as an emerging technique have shown superior capacity of dealing with heterogeneous information network (HIN). However, most HGNNs follow a semi-supervised learning manner, which notably limits…

Using carbon nanotubes (CNTs) produced by chemical vapor deposition, we have explored different strategies for the preparation of carbon nanotube devices suited for electrical and mechanical measurements. Though the target device is a…

We report the observation of strong third harmonic generation from a macroscopic array of aligned ultralong single-wall carbon nanotubes (SWCNTs) with intense midinfrared radiation. Through power-dependent experiments, we determined the…

Photonic signal processing requires efficient on-chip light sources with higher modulation bandwidths. Todays conventional fastest semiconductor diode lasers exhibit modulation speeds only on the order of a few tens of GHz due to gain…

Macroscopic arrays of highly crystalline nanocarbons offer the possibility of modifying the electronic structure of their low dimensional constituents, for example through doping, and studying the resulting collective bulk behaviour.…

Texture classification is a pivotal task in computer vision, presenting unique challenges due to high inter-class similarity and the sensitivity of structural patterns to scale and illumination changes. While Convolutional Neural Networks…

In recent years, many new materials have been developed and prepared to improve the performance of light-harvesting technologies and to develop new and attractive applications. The problem of stability of long-term operation of various…

Recent measurements in single-walled carbon nanotubes show that, on resonance, all nanotubes display the same peak optical conductivity of approximately 8 $e^2/h$, independent of radius or chirality [Joh \emph{et al.}, \emph{Nature…