Nano-structural Analysis
Nano-structural Analysis - Related Videos
13:43
Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions
0 Views •
Cited by 15 •
2013
We describe a correlative microscopy method that combines high-speed 3D live-cell fluorescent light microscopy and high-resolution cryo-electron tomography. We demonstrate the capability of the correlative method by imaging dynamic, small HIV-1 particles interacting with host HeLa cells.
11:56
Fluorescence Imaging with One-nanometer Accuracy (FIONA)
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Cited by 11 •
2014
Single fluorophores can be localized with nanometer precision using FIONA. Here a summary of the FIONA technique is reported, and how to carry out FIONA experiments is described.
08:51
A Modular Workflow for Quantitative, Structural and Functional Analysis of Leptospira Biofilms
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2025
This protocol delivers a modular, BSL-2 workflow combining crystal-violet biomass assays, time-lapse phase-contrast kinetics, confocal 3-D/matrix mapping, SEM ultrastructure, and an in vivo hamster infection module to cultivate, quantify, characterize and investigate Leptospira biofilm functional role, enabling standardized evaluation of mutants and anti-biofilm interventions across laboratories.
10:25
Sub-nanometer Resolution Imaging with Amplitude-modulation Atomic Force Microscopy in Liquid
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Cited by 39 •
2016
We present a method for achieving sub-nanometer resolution images with amplitude-modulation (tapping mode) atomic force microscopy in liquid. The method is demonstrated on commercial atomic force microscopes. We explain the rationale behind our choices of parameters and suggest strategies for resolution optimization.
17:06
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Cited by 17 •
2012
We describe a novel approach for simultaneous analysis of brain function and structure using magnetic resonance imaging (MRI). We assess brain structure with high-resolution diffusion-weighted imaging and white-matter fiber tractography. Unlike standard structural MRI, these techniques allow us to directly relate anatomical connectivity to functional properties of brain networks.
FAQs
The key step is relating nanoscale observations to larger-scale material performance. Grain boundaries, interfaces, pores, defects, and molecular or crystal arrangements can alter how a material responds, even when those features occupy only small regions. By comparing local structure with measured behavior, engineers can identify which structural variations influence strength, conductivity, catalytic activity, barrier performance, or failure.
These measurement types provide complementary evidence rather than interchangeable results. Imaging reveals nanoscale morphology, diffraction examines structural or crystal arrangements, spectroscopy supplies compositional information, and scanning probe measurements characterize surface-related features. Combining them helps distinguish whether an observed engineering effect arises from shape, arrangement, composition, or a localized structural irregularity.
These features can become controlling locations for material behavior because they interrupt, separate, or modify the surrounding structure. Their presence and arrangement may help explain changes in strength, conductivity, catalytic activity, barrier performance, or failure. Examining them individually allows engineers to move beyond average bulk measurements and determine how localized structure contributes to overall performance.
Engineers compare the nanoscale structures produced under different processing conditions and then relate those observations to functional or mechanical results. Changes in grain boundaries, interfaces, pores, defects, or molecular and crystal arrangements can indicate how processing altered the material. This structure-to-function comparison supports materials design by identifying structural features associated with desired performance or reduced failure.
A workflow begins by selecting the nanoscale feature relevant to the engineering question, such as morphology, composition, defects, or crystal arrangement. Researchers then choose one or more compatible approaches from imaging, diffraction, spectroscopy, and scanning probe measurements. Results are interpreted alongside bulk properties to connect local observations with material performance, quality control, or failure mechanisms.
The approach is useful when bulk measurements alone cannot explain why a material performs differently or fails unexpectedly. Engineers can apply it while developing metals, ceramics, polymers, or nanocomposites, and when evaluating processing outcomes or device and infrastructure reliability. The resulting structural evidence helps compare materials, identify problematic features, and guide adjustments intended to improve performance.
Nano-structural analysis supports decisions about materials design, quality control, and reliability. It can help explain variations in strength, conductivity, catalytic activity, barrier performance, and failure behavior by identifying relevant nanoscale structure. In research and development, these observations provide a basis for linking processing conditions to function and for selecting structures suited to particular engineering requirements.