Renu Sharma

In-Situ Transmission Electron Microscopy Experiments (eBook, ePUB)

Design and Practice

• Format: ePub

Produktbeschreibung

In-Situ Transmission Electron Microscopy Experiments

Design and execute cutting-edge experiments with transmission electron microscopy using this essential guide

In-situ microscopy is a recently-discovered and rapidly-developing approach to transmission electron microscopy (TEM) that allows for the study of atomic and/or molecular changes and processes while they are in progress. Experimental specimens are subjected to stimuli that replicate near real-world conditions and

their effects are observed at a previously unprecedented scale. Though in-situ microscopy is becoming an increasingly important approach to TEM, there are no current texts combining an up-to-date overview of this cutting-edge set of techniques with the experience of in-situ TEM professionals.

In-Situ Transmission Electron Microscopy Experiments meets this need with a work that synthesizes the collective experience of myriad collaborators. It constitutes a comprehensive guide for planning and performing in-situ TEM measurements,

incorporating both fundamental principles and novel techniques. Its combination of technical detail and practical how-to advice makes it an indispensable introduction to this area of research.

In-Situ Transmission Electron Microscopy Experiments readers will also find:

• Coverage of the entire experimental process, from method selection to experiment design to measurement and data analysis
• Detailed treatment of multimodal and correlative microscopy, data processing and machine learning, and more
• Discussion of future challenges and opportunities facing this field of research

In-Situ Transmission Electron Microscopy Experiments is essential for graduate students, post-doctoral fellows, and early career researchers entering the field of in-situ TEM.

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Produktdetails

• Verlag: Wiley-VCH
• Erscheinungstermin: 10. Mai 2023
• Englisch
• ISBN-13: 9783527834846
• Artikelnr.: 68030184

Autorenporträt

Renu Sharma, PhD, is an NIST Emeritus Fellow and worked as project leader there from 2009 to 2019. Before working at NIST, she was Senior Research Scientist in the LeRoy Eyring Center for Solid State Science at Arizona State University, as well as an affiliated faculty member in multiple departments. She is a pioneer in the field of transmission electron microscopy who has published extensively on the subject.

Inhaltsangabe

IN-SITU TEM
General Scope of the Book and Review of the Chapters
Why in-situ TEM?
TEM Overview
TEM/STEM-Based Characterization Techniques
Other Techniques
Introduction to Different Stimuli Used for In situ TEM

EXPERIMENT DESIGN PHILOSOPHY
General Aspects
Choice of Technique and the Microscope
TEM Holder Design and Selection
Specimen Design and Preparation
Guidelines for Experimental Setup
Practical Example of Designing In-situ TEM Experiments
Applications to Quantitative Data

IN-SITU HEATING
History
Currently Available Heating Holders
Experimental Considerations
Select Applications
Limiations and Possibilities

IN SITU CRYO-TEM
Historical Perspective
Specimen Holder Design and Function
Specimen Design and Preparation
Practical Aspects of Performing Cryogenic Cooling
Some Noteworthy Applications

DESIGNING LIQUID AND GAS CELL HOLDERS
Historical Perspective
Design Philosophy
Windows
Microfabricated Window-Cell (Microchips)
Examples of Modified Window Holders

IN SITU SOLID-LIQUID INTERACTIONS
Historical Perspective
Holder Design and Selection
Specimen Design and Preparation
Data Acquisition
Practical Challenges
Select Examples of Applications

IN-SITU GAS-SOLID INTERACTIONS
Historical Perspective
Current Strategies
Gas Manifold Design and Construction
Practical Aspects of Performi Experiment in Gas Environments
Select Examples of Applications
Review of Benefits and Limitations

MULTIMODAL AND CORRELATIVE MICROSCOPY
Multimodal TEM
Correlative Approaches

DATA PROCESSING AND MACHINE LEARNING
History of Image Simulation and Processing
Current Status
Data Management
Data Processing and Machine Learning (ML)
Select Applications
Future Needs
Limitations

FUTURE VISION
Historical Aspects
Current Status
Technical Challenges
Developing Relevant Strategies