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Carbon nanotubes are a good realization of one-dimensional crystals where basic science and potential nanodevice applications merge. Defects are known to modify the electrical resistance of carbon nanotubes. They can be present in as-grown…
Optical reflectivity contrast provides a simple, fast and noninvasive method for characterization of few monolayer samples of two-dimensional materials. Here we apply this technique to measure the thickness of thin flakes of hexagonal Boron…
Achieving both efficiency and strong discriminative ability in lightweight visual tracking is a challenge, especially on mobile and edge devices with limited computational resources. Conventional lightweight trackers often struggle with…
Coatings comprised of carbon nanotubes are very black; that is, characterized by low reflectance over a broad wavelength range from the visible to far infrared. Arguably there is no other material that is comparable. This is attributable to…
Dynamic full-field optical coherence microscopy (d-FF-OCM) is a label-free imaging technique that captures intrinsic subcellular motions to generate functional contrast. This dynamic approach yields images with fluorescence-like contrast,…
As the aerospace industry becomes increasingly demanding for stronger lightweight materials, the ultra-strong carbon nanotube (CNT) composites with highly aligned CNT network structures could be the answer. In this work, a novel methodology…
Understanding structure-property relationships in complex materials requires integrating complementary measurements across multiple length scales. Here we propose an interpretable "multimodal" machine learning framework that unifies…
Chiral carbon nanotubes (CNTs) are direct-gap semiconductors with optical properties governed by one-dimensional excitons with enormous oscillator strengths. Each species of chiral CNTs has an enantiomeric pair of left- and right-handed…
Due to its powerful capability of self-supervised representation learning and clustering, contrastive attributed graph clustering (CAGC) has achieved great success, which mainly depends on effective data augmentation and contrastive…
Determination of optical absorption cross-section is always among the central importance of understanding a material. However its realization on individual nanostructures, such as carbon nanotubes, is experimentally challenging due to the…
The need to explain the output of a deep neural network classifier is now widely recognized. While previous methods typically explain a single class in the output, we advocate explaining the whole output, which is a probability distribution…
An algorithm is developed for structure identification of amorphous carbonaceous nanomaterials with a joint x-ray and neutron diffraction data analysis, using the data on the chemical composition of the sample from other diagnostics. The…
The one-dimensional confinement of quasiparticles in individual carbon nanotubes (CNTs) leads to extremely anisotropic electronic and optical properties. In a macroscopic ensemble of randomly oriented CNTs, this anisotropy disappears…
In this paper, we introduce a novel approach to novel object captioning which employs relative contrastive learning to learn visual and semantic alignment. Our approach maximizes compatibility between regions and object tags in a…
Accurate determination of crystal structures is central to materials science, underpinning the understanding of composition-structure-property relationships and the discovery of new materials. Powder X-ray diffraction is a key technique in…
We report a novel approach to the design and implementation of a tunable cavity on an optical nanofiber (ONF). The key point is to create a composite photonic crystal cavity (CPCC), by combining an ONF and a chirped period defect mode…
Optical Coherence Tomography (OCT) is a non-invasive depth resolved optical imaging modality, that enables high resolution, cross-sectional imaging in biological tissues and materials at clinically relevant depths. Though OCT offers high…
Feature coding has become increasingly important in scenarios where semantic representations rather than raw pixels are transmitted and stored. However, most existing methods are architecture-specific, targeting either CNNs or Transformers.…
A metasurface hologram combines fine spatial resolution and large viewing angles with a planar form factor and compact size. However, it suffers coherent artifacts originating from electromagnetic cross-talk between closely packed…
Calculations of the conductance of a carbon nanotube (CNT)-molecule-CNT structure are in agreement with experimental measurements [1]. The features in the transmission correspond directly to the features of the isolated molecular orbitals.…