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Results for “transmissive”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A human monoclonal antibody blocks malaria transmission and defines a highly conserved neutralizing
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Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States
Non-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (R eff ) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median R eff below 1 when combined with either stay at home orders (median R eff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median R eff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.
Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images
Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.
Towards data-driven next-generation transmission electron microscopy
Electron microscopy touches on nearly every aspect of modern life, underpinning materials development for quantum computing, energy and medicine. We discuss the open, highly integrated and data-driven microscopy architecture needed to realize transformative discoveries in the coming decade.
Atom vacancies and electronic transmission Stark effects in boron nanoflake junctions
Finite-sized boron nanomaterials have received little attention in comparison to their graphene-like 2D boron analogues. It is with systems of precise atomic structures where the electrical conductance can be most fruitfully analyzed at the fundamental level. To understand how conductance varies with respect to the electronic structure, and particularly with vacancies, we study finite-sized boron nanoflakes (BNFs) and closely examine their remarkable changes in physical properties. Unlike carbon-based materials, we find from non-equilibrium Green's functions density functional theory (NEGF-DFT) calculations that the charge transport of BNFs with 35–37 atoms is modulated by site-specific atomic vacancies. Here, the BNF with no vacancy (B 37 ) shows significantly lower conductivity (9.23 μS), than B 36 with one vacancy (46.1 μS), and lower still than with two vacancies (B 35 , 54.2 μS). From the thermopower function, these nanomaterials change from strong hole conductors to electron and back to hole conductors with the addition of each vacancy, from a doublet (B 37 ) to singlet (B 36 ) to doublet (B 35 ) ground state, respectively.
Quantum theory of electronic excitation and sputtering by transmission electron microscopy
Combining quantum electrodynamics with density functional theory, we model electronic excitation and sputtering by beam electrons in two-dimensional materials. Electronic excitations can drastically increase the sputtering rates in these materials.
In situ transmission electron microscopy as a toolbox for the emerging science of nanometallurgy
The paper describes a novel lab-on-a-chip approach that allows the observation of live nanoalloying and heat treatment at the nanoscale.
Chiral induction at the nanoscale and spin selectivity in electron transmission in chiral methylated BEDT-TTF derivatives
Great efforts have been made in the last few decades to realize electronic devices based on organic molecules. A possible approach in this field is to exploit the chirality of organic molecules for the development of spintronic devices, an applicative way to implement the chiral-induced spin selectivity (CISS) effect. In this work we exploit enantiopure tetrathiafulvalene (TTF) derivatives as chiral inducers at the nanoscale. The aim is to make use of TTF's well-known and unique semiconducting properties, to be expressed in the fields of enantio-selectivity and the chiral-induced spin selectivity (CISS) effect. Further, the experimental results shown in this paper further demonstrate how chirality and spin are deeply interrelated, as foreseen within the CISS effect theory, paving the way for the application of TTF derivatives in the field of spintronics. In this work, we demonstrate that tetramethyl-bis(ethylenedithio)-tetrathiafulvalene (TM-BEDT-TTF) (1) behaves as an efficient spin filter, as evidenced by magneto-atomic force microscopy (mc-AFM) measurements. Additionally, it is shown to be effective in transferring chirality to CdS/CdSe core–shell nanoparticles, as inferred from the analysis of circularly resolved photoluminescence spectra. This makes 1 a promising candidate for a variety of applications, ranging from plasmonics to quantum computing.
Influence of Sand Morphology on Interparticle Force and Stress Transmission Using Three-Dimensional
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