Optimization of Q-factor of AFM cantilevers using genetic algorithms

Micro cantilever beams have been intensively used in sensing applications including to scanning profiles and surfaces where there resolution and imaging speed are critical. Force resolution is related to the Q-factor. When the micro-cantilever operates in air with small separation gaps, the Q-factor is even more reduced due to the squeeze-film damping effect. Thus, the optimization of the configuration of an AFM micro-cantilever is presented in this work with the objective of improving its Q-factor. To accomplish this task, we propose the inclusion of holes as breathing chimneys in the initial design to reduce the squeeze-film damping effect. The evaluation of the Q-factor was carried out using finite element model, which is implemented to work together with the squeeze-film damping model. The methodology applied in the optimization process was genetic algorithms, which considers as constraints the maximum allowable stress, fundamental frequency and spring constant with respect to the initial design. The results show that the optimum design, which includes holes with an optimal location, increases the Q-factor almost five times compared to the initial design.

► It was optimized the Q-factor of a cantilever, which operates near to the surface in air.
► It was proposed the inclusion of holes as breathing chimneys in the cantilever's surface.
► Genetic algorithms and finite element analysis were applied to find the optimum configuration for the Q-factor.
► Optimum design keeps first frequency and the spring constant very close to the original and has a better force resolution.
► Final design can be easily manufactured through a mask.