Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques

Cryo-electron microscopy (cryo-EM) is a powerful tool for imaging biological samples but is typically limited by sample thickness, which is restricted to a few hundred nanometers depending on the electron energy. However, there is a growing need for imaging techniques capable of studying biological...

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Main Authors: Bradyn Quintard, Xi Yang, Liguo Wang
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/2/565
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author Bradyn Quintard
Xi Yang
Liguo Wang
author_facet Bradyn Quintard
Xi Yang
Liguo Wang
author_sort Bradyn Quintard
collection DOAJ
description Cryo-electron microscopy (cryo-EM) is a powerful tool for imaging biological samples but is typically limited by sample thickness, which is restricted to a few hundred nanometers depending on the electron energy. However, there is a growing need for imaging techniques capable of studying biological samples up to 10 µm in thickness while maintaining nanoscale resolution. This need motivates the use of mega-electron-volt scanning transmission electron microscopy (MeV-STEM), which leverages the high penetration power of MeV electrons to generate high-resolution images of thicker samples. In this study, we employ Monte Carlo simulations to model electron–sample interactions and explore the signal decay of imaging electrons through thick specimens. By incorporating material properties, interaction cross-sections for energy loss, and experimental parameters, we investigate the relationship between the incident and transmitted beam intensities. Key factors such as detector collection angle, convergence semi-angle, and the material properties of samples were analyzed. Our results demonstrate that the relationship between incident and transmitted beam intensities follows the Beer–Lambert law over thicknesses ranging from a few microns to several tens of microns, depending on material composition, electron energy, and collection angles. The linear depth of silicon dioxide reaches 3.9 µm at 3 MeV, about 6 times higher than that at 300 keV. Meanwhile, the linear depth of amorphous ice reaches 17.9 µm at 3 MeV, approximately 11.5 times higher than that at 300 keV. These findings are crucial for advancing the study of thick biological and semiconductor samples using MeV-STEM.
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spelling doaj-art-d953073d21374471b4e14a352c30e7d22025-01-24T13:19:52ZengMDPI AGApplied Sciences2076-34172025-01-0115256510.3390/app15020565Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo TechniquesBradyn Quintard0Xi Yang1Liguo Wang2Department of Physics & Astronomy, Dartmouth College, Hanover, NH 03755, USANational Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USALaboratory of BioMolecular Structure, Brookhaven National Laboratory, Upton, NY 11973, USACryo-electron microscopy (cryo-EM) is a powerful tool for imaging biological samples but is typically limited by sample thickness, which is restricted to a few hundred nanometers depending on the electron energy. However, there is a growing need for imaging techniques capable of studying biological samples up to 10 µm in thickness while maintaining nanoscale resolution. This need motivates the use of mega-electron-volt scanning transmission electron microscopy (MeV-STEM), which leverages the high penetration power of MeV electrons to generate high-resolution images of thicker samples. In this study, we employ Monte Carlo simulations to model electron–sample interactions and explore the signal decay of imaging electrons through thick specimens. By incorporating material properties, interaction cross-sections for energy loss, and experimental parameters, we investigate the relationship between the incident and transmitted beam intensities. Key factors such as detector collection angle, convergence semi-angle, and the material properties of samples were analyzed. Our results demonstrate that the relationship between incident and transmitted beam intensities follows the Beer–Lambert law over thicknesses ranging from a few microns to several tens of microns, depending on material composition, electron energy, and collection angles. The linear depth of silicon dioxide reaches 3.9 µm at 3 MeV, about 6 times higher than that at 300 keV. Meanwhile, the linear depth of amorphous ice reaches 17.9 µm at 3 MeV, approximately 11.5 times higher than that at 300 keV. These findings are crucial for advancing the study of thick biological and semiconductor samples using MeV-STEM.https://www.mdpi.com/2076-3417/15/2/565Monte Carlo simulationMeV-STEMBeer Lambert lawelectron-specimen interactionnanometer resolutionthick biological samples
spellingShingle Bradyn Quintard
Xi Yang
Liguo Wang
Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques
Applied Sciences
Monte Carlo simulation
MeV-STEM
Beer Lambert law
electron-specimen interaction
nanometer resolution
thick biological samples
title Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques
title_full Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques
title_fullStr Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques
title_full_unstemmed Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques
title_short Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques
title_sort quantitative modeling of high energy electron scattering in thick samples using monte carlo techniques
topic Monte Carlo simulation
MeV-STEM
Beer Lambert law
electron-specimen interaction
nanometer resolution
thick biological samples
url https://www.mdpi.com/2076-3417/15/2/565
work_keys_str_mv AT bradynquintard quantitativemodelingofhighenergyelectronscatteringinthicksamplesusingmontecarlotechniques
AT xiyang quantitativemodelingofhighenergyelectronscatteringinthicksamplesusingmontecarlotechniques
AT liguowang quantitativemodelingofhighenergyelectronscatteringinthicksamplesusingmontecarlotechniques