The open source software Gwyddion is developed in close collaboration with the CEITEC RG Development of Methods for Analysis and Measuring and a large number of participants from other institutions throughout the world. It has become a standard software in the field and is used by thousands of scientists.
Gwyddion implements all data processing and analysis functions commonly used in Scanning Probe Microscopy – and many unusual and experimental ones on top of it, including:
- Correction of scan line, global and local image defects.
- Evaluation of statistical parameters.
- Measurement of terraces, lattices, curvature and other geometrical shapes.
- Marking and evaluation of grains/particles.
- A wide variety of filters and morphological operations, such as smoothing or edge detection.
- Specialised functions for instance for mechanical and magnetic modes or tip modelling.
Design and implementation of Gwyddion
Overall Gwyddion screenshot.
Gwyddion was designed as a cross-platform and extensible. It consits of three main parts: libraries providing core data processing routines, GUI elements and utility functions; modules that provide specific data processing and file functions; and a small and simple application itself that primarily serves as a glue connecting everything else together.
Notable features of Gwyddion include:
- Support for more than 140 SPM file formats.
- Processing of data under arbitrarily shaped masks.
- Calibration and metrology support.
- Single point spectra, volume, XYZ and curve map data support.
- Generation of artificial surfaces and measurement simulation.
- Python 2 scripting.
References:
- David Nečas, Petr Klapetek, Gwyddion: an open-source software for SPM data analysis, Central European Journal of Physics 10 (2012) 181-188, 10.2478/s11534-011-0096-2
Data analysis methods in SPM
The development of Gwyddion is naturaly connected to development of data processing methods in SPM. Examples includes methods for the analysis of nanoparticles under non-ideal conditions or statistical characterisation of roughness in irregular rough regions. Quantitative analysis of SPM data should also include uncertainties of the obtained parameters. This requires the characterisation of measurement errors in SPM, both systematic and random, and their propagation through data processing calculations.
Algorithm for evaluation of atomic steps on Si.
For quantitative analysis of data acquired using novel SPM scanning modes, such as fast point spectroscopy and imaging, it is crucial to have available independent data processing methods that can be applied off-line (after acquisition) and consistently to data measured using different instruments. Thanks to the open-source nature of Gwyddion, all algorithms implemented there can be examined and verified at the source code level, which is key for comparablity of results and further progress to standardisation in nanometrology.
References:
- David Nečas, Andrew Yacoot, Miroslav Valtr, Petr Klapetek, Demystifying data evaluation in the measurement of periodic structures, Measurement Science and Technology 34 (2023) 055015, 10.1088/1361-6501/acbab3
- David Nečas, Petr Klapetek, Synthetic Data in Quantitative Scanning Probe Microscopy, Nanomaterials 11 (2021) 1746, 10.3390/nano11071746
- Jørgen Garnæs, David Nečas, Lars Nielsen, Morten Hannibal Madsen, Antoni Torras-Rosell, Guanghong Zeng, Petr Klapetek, Andrew Yacoot, Algorithms for using silicon steps for scanning probe microscope evaluation, Metrologia 57 (2020) 064002, 10.1088/1681-7575/ab9ad3
- David Nečas, Miroslav Valtr, Petr Klapetek, How levelling and scan line corrections ruin roughness measurement and how to prevent it, Scientific Reports 10 (2020) 15294, 10.1038/s41598-020-72171-8
- David Nečas, Petr Klapetek, Miroslav Valtr, Estimation of roughness measurement bias originating from background subtraction, Measurement Science and Technology 31 (2020) 094010, 10.1088/1361-6501/ab8993
- David Nečas, Petr Klapetek, Volker Neu, Marek Havlíček, Robert Puttock, Olga Kazakova, Xiukun Hu, Lenka Zajíčková, Determination of tip transfer function for quantitative MFM using frequency domain filtering and least squares method, Scientific Reports 9 (2019) 3880, 10.1038/s41598-019-40477-x
- David Nečas, Petr Klapetek, Study of user influence in routine SPM data processing, Measurement Science and Technology 28 (2017) 034014, 10.1088/1361-6501/28/3/034014
SPM instrumentation
Although Gwyddion focuses on the software part, the broader Gwyddion ecosystem includes also novel scanning and hardware projects, led by Petr Klapetek in research group Development of Methods for Analysis and Measuring at CEITEC BUT.
References:
- Miroslav Valtr, Petr Klapetek, Jan Martinek, Ondřej Novotný, Zdeněk Jelínek, Václav Hortvík, David Nečas, Scanning Probe Microscopy controller with advanced sampling support, HardwareX 15 (2023) e00451, 10.1016/j.ohx.2023.e00451
- Petr Klapetek, Andrew Yacoot, Petr Grolich, Miroslav Valtr, David Nečas, Gwyscan: a library to support non-equidistant Scanning Probe Microscope measurements, Measurement Science and Technology 28 (2017) 034015, 10.1088/1361-6501/28/3/034015