Thermo Scientific Auto Slice and View and Maps, two automation software packages for electron/ion microscopy, are excellent for simplifying gathering common imaging techniques. However, it is rarely standard practice to work toward cutting-edge research objectives or to satisfy particular industrial needs.
Both basic and industrial automation frequently call for sophisticated imaging and analysis methods outside the purview of general-purpose software.
Automated Electron Microscopy and FIB-SEM Imaging
The electron and ion microscopy customization toolkit is Thermo Scientific AutoScript 4 software. With Autoscript Software based on Python, users can automate imaging and related processing pipelines designed to address particular research questions.
AutoScript Software
- Focuses on the microscope for higher throughput
- Provides a direct link between research needs and microscope automation
- Enables improved reproducibility and accuracy
Automated Electron Microscopy and FIB-SEM Imaging
Integrated IDE
Automated Script Development is facilitated by an integrated development environment (IDE). Including object browsing and auto-completion syntax tools guarantee a smooth, fast, and unified scripting framework for the user.
Python
Utilize the most widely used scientific programming language to fully utilize the power of the microscope. Based on Python 3.5, Autoscript Software has several pre-installed libraries for image processing, machine learning, data analysis, and scientific computing.
Scripting Toolbox
The AutoScript 4 software includes several prebuilt routines that are frequently needed. Developing scripts that specify the research workflow can take less time when users do not have to start from scratch.
Specifications
Source: Thermo Fisher Scientific – Electron Microscopy Solutions
| . |
. |
| Supported microscope control methods |
- Electron beam control
- Ion beam control
- SEM and FIB imaging (all detectors)
- Stage control
- Patterning
- Gas injection system (GIS)
|
| Common packages |
- NumPy, SciPy, Pandas, OpenCV, SciKit-image, Matplotlib, Jupyter
|
| Application examples |
- Automated region-of-interest finding and imaging
- Parameter sweeps (acquire images at different kV, current, etc.)
- Feature tracking or drift compensation
- FIB nanopatterning
- On-the-fly feature measurements
- On-the-fly image processing (segmentation, deconvolution, thresholding, colormap changes, image inversion, 3D plots, FFTs, histogram operations)
|
| Compatibility |
- Runs on Windows® 7 or Windows 10 support computer
- Compatible with Windows 7 or Windows 10 based SEM and DualBeam systems
|