Absolute Integrator is a piece of quantitative STEM image analysis code, written in MatLab™, for the calculation and visualisation of absolute scattering cross-sections from atomic-resolution HAADF data. The software processes matched sets of detector efficiency maps along with their experimental images. It can also be used to analyse simulated images to produce cross-section library data. Such quantitative STEM analysis, when combined with reference simulation, can be a powerful tool in thickness / composition studies.
Academic/non-commercial users can now Download Absolute Integrator for FREE. The current v1.6.4 release includes several new features including:
- Automated HAADF detector sensitivity analysis and calibration,
- Image magnification (pixel-size) calibration from its diffractogram,
- Automated image peak-finding based on the Ranger code,
- The ability to determine and subtract either a global or locally varying background,
- Automatic determination of integration regions for all atomic-columns within the image,
- Calculation and visualisation of all column cross-sections in the image, and
- NEW: Calculation of column ellipticities (beta feature).
The current software is optimised for the analysis of atomic-resolution images of metallic nano-particles. To the left and example of such an image is shown from a  oriented pure platinum sample supported on carbon-black.
Analysis of these images present several challenges and the software has been designed to be as robust as possible. Each stage of the analysis including the peak-finding algorithm, background subtraction and atomic-column intensity-integration have been designed carefully to minimise errors in the final results.
An academic manuscript describing the method and software in detail is under preparation and will be available soon.
Absolute Integrator for academic / non-commercial use can be downloaded below. A full user manual is in preparation but brief instructions can be found here.
Research Papers Using Absolute Integrator
- “Probing the Bonding in Nitrogen-Doped Graphene Using Electron Energy Loss Spectroscopy”
Rebecca J. Nicholls, Adrian T. Murdock, Joshua Tsang, Jude Britton, Timothy J. Pennycook, Antal Koós, Peter D. Nellist, Nicole Grobert, and Jonathan R. Yates
ACS Nano 7 (2013). DOI: 10.1021/nn402489v (see supplimentary inforamtion)