We measure the current vs voltage (I-V) characteristics of a diodelike tunnel junction consisting of a sharp metallic tip placed at a variable distance d from a planar collector and emitting electrons via electric-field assisted emission. All curves collapse onto one single graph when I is plotted as a function of the single scaling variable Vd^{-\lambda}, d being varied from a few mm to a few nm, i.e., by about six orders of magnitude. We provide an argument that finds the exponent {\lambda} within the singular behavior inherent to the electrostatics of a sharp tip. A simulation of the tunneling barrier for a realistic tip reproduces both the scaling behavior and the small but significant deviations from scaling observed experimentally.Comment: 6 pages, 6 figures. Accepted for publication in Physical Review
There have been great efforts on the nanoscale 3D probing of brain tissues to image subcellular morphologies. However, limitations in terms of tissue coverage, anisotropic resolution, stain dependence, and complex sample preparation all hinder achieving a better understanding of the human brain functioning in the subcellular context. Herein, X‐ray nanoholotomography is introduced as an emerging synchrotron radiation‐based technology for large‐scale, label‐free, direct imaging with isotropic voxel sizes down to 25 nm, exhibiting a spatial resolution down to 88 nm. The procedure is nondestructive as it does not require physical slicing. Hence, it allows subsequent imaging by complementary techniques, including histology. The feasibility of this 3D imaging approach is demonstrated on human cerebellum and neocortex specimens derived from paraffin‐embedded tissue blocks. The obtained results are compared to hematoxylin and eosin stained histological sections and showcase the ability for rapid hierarchical neuroimaging and automatic rebuilding of the neuronal architecture at the level of a single cell nucleolus. The findings indicate that nanoholotomography can complement microscopy not only by large isotropic volumetric data but also by morphological details on the sub‐100 nm level, addressing many of the present challenges in brain tissue characterization and probably becoming an important tool in nanoanatomy.
Micro computed tomography has been combined with dedicated data analysis for the in vitro quantification of sub-surface enamel lesion mineralization. Two artificial white spot lesions, generated on a human molar crown in vitro, were examined. One lesion was treated with a self-assembling peptide intended to trigger nucleation of hydroxyapatite crystals. We non-destructively determined the local X-ray attenuation within the specimens before and after treatment. The three-dimensional data was rigidly registered. Three interpolation methods, i.e., nearest neighbor, tri-linear, and tri-cubic interpolation were evaluated. The mineralization of the affected regions was quantified via joint histogram analysis, i.e., a voxel-by-voxel comparison of the tomography data before and after mineralization. After ten days incubation, the mean mineralization coefficient reached 35.5% for the peptide-treated specimen compared to 11.5% for the control. This pilot study does not give any evidence for the efficacy of peptide treatment nor allows estimating the necessary number of specimens to achieve significance, but shows a sound methodological approach on the basis of the joint histogram analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.