Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Scanning Electron Microscopy

Scanning Electron Microscopy

A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
Fundamental Principles
Accelerated...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Rainfall immediately before and after fire promotes long-term occurrence of a rare, fire-sensitive passerine.

Ecological applications : a publication of the Ecological Society of America·2026

Same author

Biodiversity accounting on farms: Relating diversity of bird assemblages to ecosystem condition.

The Science of the total environment·2024

Same author

Portable thermal scanners to detect and monitor small endotherms: A comparative assessment of available equipment to guide practitioners.

Ecology and evolution·2023

Same author

Unmasking the Resolution-Throughput Tradespace of Focused-Ion-Beam Machining.

Advanced functional materials·2023

Same author

Routine Laboratory Tests are not Necessary After Primary Total Joint Arthroplasty: A Prospective Study Utilizing a Selective Algorithmic Approach.

The Journal of arthroplasty·2022

Same author

Probing Electrified Liquid-Solid Interfaces with Scanning Electron Microscopy.

ACS applied materials & interfaces·2020

Search research articles

Related Experiment Video

Updated: Dec 26, 2025

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

Published on: January 20, 2023

An a posteriori Error Estimate for Scanning Electron Microscope Simulation with Adaptive Mesh Refinement.

William F Mitchell¹, John S Villarrubia²

¹Applied and Computational Mathematics Division, Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899.

Journal of Scientific Computing

|March 14, 2020

Summary

This summary is machine-generated.

This study introduces a new adaptive mesh refinement algorithm for scanning electron microscope simulations. It significantly reduces computation time and mesh size while maintaining accuracy in electron trajectory simulations.

Keywords:

A posteriori error estimation Adaptive mesh refinement Finite element analysis Scanning electron microscope simulation

More Related Videos

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

Related Experiment Videos

Last Updated: Dec 26, 2025

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

Published on: January 20, 2023

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

Area of Science:

Materials Science
Computational Physics
Microscopy

Background:

Scanning electron microscopy (SEM) signal intensity depends complexly on sample topography and composition.
Accurate SEM measurements require explicit accounting for the signal-measurand relationship.
Simulators are crucial for theoretical understanding due to numerous signal determinants.

Purpose of the Study:

To develop a novel adaptive mesh refinement algorithm for SEM simulations.
To improve the efficiency of finite element analysis in SEM simulations, particularly for charging nonconducting samples.
To minimize errors in electron trajectories during SEM simulations.

Main Methods:

Implementation of a new a posteriori local error estimator for adaptive mesh refinement.
Finite element analysis to compute electric fields in SEM simulations.
Algorithm validation using a test problem with a known exact solution.

Main Results:

The new adaptive mesh refinement algorithm reduces computation time and mesh size.
Achieved comparable electron trajectory accuracy to hand-graded meshes with fewer vertices.
Demonstrated a 3.5x reduction in vertices and 2.25x less computation time.

Conclusions:

The developed algorithm enhances the efficiency of SEM simulations.
Minimizing electron trajectory error is a more effective strategy for SEM simulations than traditional energy norm minimization.
This method offers significant computational savings for SEM simulations involving nonconducting samples.