Scanning Transmission Electron Microscopy

Advanced Characterization Methods for Materials Science Applications
Herausgeber: Bruma, Alina

• Broschiertes Buch

Produktbeschreibung

This book focuses on explaining and applying the principles of machine learning-based techniques and advanced image processing methods currently used in the electron microscopy community suitable for handling large electron microscopy data sets and extracting structure-property information for various materials.

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Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 150
• Erscheinungstermin: 7. Oktober 2024
• Englisch
• Abmessung: 234mm x 156mm x 9mm
• Gewicht: 240g
• ISBN-13: 9780367655389
• ISBN-10: 0367655381
• Artikelnr.: 71715582

Autorenporträt

Dr. Alina Bruma received her PhD degree in Nanoscale Physics from The University of Birmingham, UK in 2013. Dr. Bruma completed several postdoctoral stages at the Laboratory of Crystallography and Materials Science (CRISMAT-CNRS) France, University of Texas at San Antonio, USA and The National Institute of Standards and Technology, USA before moving to the American Institute of Physics Publishing in 2019. Her research has been focused on the study of crystalline structure of materials and the determination of their structure-property relationship using transmission electron microscopy and electron diffraction. Dr Bruma is also the Chairman of The Electron Diffraction sub-committee at the International Center for Diffraction Data (ICDD).

Inhaltsangabe

Chapter 1 Practical Aspects of Quantitative and High-Fidelity STEM Data
Recording Chapter 2 Machine Learning for Electron Microscopy Chapter 3
Application of Advanced Aberration-Corrected Transmission Electron
Microscopy to Material Science: Methods to Predict New Structures and Their
Properties Chapter 4 Large Dataset Electron Diffraction Patterns for the
Structural Analysis of Metallic Nanostructures