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Prismatic 2.0 - Simulation software for scanning and high resolution transmission electron microscopy (STEM and
Luis Rangel DaCosta1, Hamish G Brown2, Philipp M Pelz1
1National Center for Electron Microscopy, Molecular Foundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, USA; Department of Materials Science and Engineering, University of California Berkeley, Berkeley, CA 94720, USA.
Prismatic 2.0 is a new open-source software for fast scanning transmission electron microscopy (STEM) simulations. It significantly reduces calculation times for atomic-resolution materials science, making STEM experiments easier to interpret.
Area of Science:
- Materials Science
- Computational Physics
- Electron Microscopy
Background:
- Scanning transmission electron microscopy (STEM) is crucial for atomic-resolution materials characterization.
- Accurate simulations are essential for interpreting STEM experimental data.
- Traditional STEM simulations are computationally intensive due to the need for modeling electron scattering at each probe position.
Purpose of the Study:
- To introduce Prismatic version 2.0, a significantly improved software for fast STEM simulations.
- To enhance the efficiency and accessibility of STEM simulations for materials science research.
- To provide a versatile tool for interpreting complex STEM experimental results.
Main Methods:
- Developed Prismatic 2.0, featuring algorithmic improvements for faster simulations.
- Incorporated support for multi-CPU and multi-GPU systems.
- Included conventional multislice and the PRISM simulation methods.
Main Results:
- Prismatic 2.0 enables rapid simulation of STEM experiments, drastically reducing calculation times.
- The software supports advanced features like plane-wave transmission electron microscopy (TEM) and includes a graphical user interface (GUI).
- New algorithmic improvements and post-processing capabilities enhance simulation accuracy and utility.
Conclusions:
- Prismatic 2.0 offers a powerful and efficient solution for STEM simulations, accelerating materials characterization.
- The open-source availability and multi-platform support (C++, Python, Docker) increase accessibility for researchers.
- This advancement facilitates more accurate interpretation of atomic-resolution STEM data.
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