Mathematical innovation: Advanced mathematical tools for full description of nanostructures and nanotechnology product surfaces.
The topography and morphology of nanostructures are often highly complex. Complexity is often increased due to the coexistence of random and quasi-organized surface features. The complete and quantified description of this complexity cannot be done with existing mathematical methods. Mathematical innovation is required that will lead to new solutions. Nanometrisis pioneers the development of new mathematical solutions for fuller description of morphological complexity of nanostructures.
Synchronization with industry needs: Prompt adjustment with the roadmaps of the various disciplines of nanotechnology.
The semiconductor and microelectronics industry was the first to establish with great success, roadmaps (every two years) for product and technology development including their metrology (International Technology Roadmap for Semiconductors). This defined directions for the industry, but also quantified the progress to be achieved in the coming years. Nanometrisis closely monitors any changes in these roadmaps and adjusts its software accordingly.
Synchronization with research needs: Continuous feedback with recent research developments and their selective application into further development of software.
The evolution of modern industry is heavily dependent on research focusing on the micro and nanoscale modification and quantitative characterization of its products. Nanometrisis adapts its software incorporating selective and useful new research results thanks to the advanced research experience of its members.
Hybrid (Holistic) Metrology: Algorithmic support of combining measurements from scanning electron (SEM), atomic force (AFM), and other microscopes.
No metrological technique is perfect. Certain inaccuracies or systematic errors may be present in one method, but absent from another one. This weakness is critical if only one technique is used to describe the desired properties of nano products. Hybrid metrology suggests the intelligent combination of two or more measurement methods aiming at minimizing the impact of metrological inaccuracy. Nanometrisis develops an algorithm combining measurements from atomic and electron microscopy for the most precise characterization of roughness and morphology of a free surface.
«Smart» Metrology: Targeted selection of critical parameters for nanostructure characterization depending on their application.
Nanostructured products are usually targeted towards a specific application – e.g. nanoelectronics, optics, wetting control -. However, until now their metrology provides a generic set of parameters and functions regardless of whether such parameters are critical for the specific application. Nanometrisis pioneers a process of targeted (“smart”) metrology, which will guide the user towards those parameters and functions that are most critical in the context of specific applications. This is done on the basis of laws and relationships from theory, simulation and experimental measurement results published in the literature and connecting topographical features with performance in a specific application.
Integration of machine learning techniques in our software.
Nanometrisis develops state of the art deep learning techniques for microscope image enhancement and denoising.