Michael R. P. Ragazzon
Software Engineer PhD Engineering Cybernetics


While pursuing my academic interests, the main area of research focused on the topic of atomic force microscopy (AFM). By utilizing tools from control engineering, our efforts at improving AFM can be divided into two main areas of interest:

(I) Improving the performance of the microscope. In dynamic mode AFM, the imaging bandwidth is governed by the slowest component in the open-loop chain consisting of the vertical actuator, cantilever and demodulator. Of which, the latter has been our main concern. Our efforts included (1) development and utilization of new high-bandwidth demodulators, (2) studying possibilities for entirely circumventing the demodulator, as well as (3) investigating and comparing state-of-the-art demodulators in AFM.

(II) Model-based approach to revealing nanomechanical properties using AFM. Revealing nanomechanical properties of soft samples is possible using AFM due to its ability to measure forces acting between the cantilever tip on the microscope and the sample. Traditionally, static load-unload force curves have been used to measure elasticity of the sample by fitting the measurements to the Hertz contact model. More recently, dynamic approaches allow one to additionally reveal properties such as viscosity and multifrequency amplitude and phase. We have been developing a new model-based approach to revealing dynamic properties such as viscoelasticity. Utilizing this online identification approach allows one to monitor time-varying mechanical properties, including elastic modulus, in real-time. Such a model enables one to iteratively improve the sample model as more data is gathered, by taking into accounting the measured signals. This can assist to better understand the dynamics and mechanisms of the sample, as well as helping to develop improved models for simulation.

Experiments were conducted at the Nanopositioning lab at the Department of Engineering Cybernetics, NTNU. In addition to custom-built nanopositioning devices, a commercial AFM is available for implementation of novel control and identification strategies.

Figure: Lyapunov estimator for high-bandwidth amplitude demodulation.
Figure: AFM experiment employing parameter identification on a two-component polymer sample.