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Updated: Sep 26, 2025

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Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction
Published on: April 1, 2017
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Effects of Structural and Microstructural Features on the Total Scattering Pattern of Nanocrystalline Materials
Nicola Dengo1, Norberto Masciocchi1, Antonio Cervellino2
1Dipartimento di Scienza e Alta Tecnologia & To.Sca.Lab, Università dell'Insubria, via Valleggio 11, 22100 Como, Italy.
Nanomaterials (Basel, Switzerland)
|April 23, 2022
Summary
Characterizing nanomaterials requires understanding atomic-scale features. This study reveals how size, morphology, and defects influence atomic pair distribution functions, aiding in material analysis.
Area of Science:
- Materials Science
- Nanotechnology
- Solid-State Physics
Background:
- Atomic and nanometer-scale features significantly impact nanomaterial properties.
- Total scattering methods are key for nanomaterial characterization.
- Disentangling microstructural effects from size/morphology in nanomaterials is challenging.
Purpose of the Study:
- To simulate and identify fingerprints of structural and microstructural features on nanomaterial scattering patterns.
- To analyze the influence of size, morphology, and defects on the atomic pair distribution function.
- To provide a generalizable method for nanomaterial characterization.
Main Methods:
- Utilized atomistic models of cadmium selenide as a prototypical system.
- Simulated effects on the atomic pair distribution function using Debye scattering equation.
- Computed reciprocal space patterns to analyze real and reciprocal space scattering.
Main Results:
- Identified distinct fingerprints of size, size dispersion, structure, and morphology on scattering patterns.
- Demonstrated the interplay between planar defects and other microstructural features.
- Highlighted measurable features in total scattering patterns for effective characterization.
Conclusions:
- The study provides a framework for interpreting scattering data from nanomaterials.
- The identified fingerprints offer insights into defect analysis and property prediction.
- Results are broadly applicable to various classes of nanomaterials.
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