Air bubbles in water are excellent acoustic resonators. Their ability to strongly interact with acoustic waves has led to the development of acoustic metamaterials made of bubbles, for instance in order to turn acoustic reflectors into perfect absorbers [1].
In this project, the main objective will be to conceive a new kind of acoustic metamaterial using a structured clouds of bubbles. On the conceptual side, in order to understand the collective emission properties of bubbles, the project will be based on the analogy that can be made between acoustic experiments involving resonating bubbles and quantum optics experiments involving cold atoms [2]. On the experimental side, the project will benefit from the unique expertise at LIPhy to trap air bubbles in cages that are fabricated using 3D printing technology [3]. Finally, in order to conceive acoustic metamaterials with optimal properties, the project will involve employing powerful tools developed by the deep-learning community, such as efficient optimizers based on automatic differentiation.
At an initial stage, the project will involve understanding the dynamics of two bubbles, using numerical simulations and experimental measurements. At a later stage, collective emission in more complex systems made of clouds of bubbles will be investigated in simulations and experiments.
[2] Bouchet and Carminati, JOSA A 36, 186-195 (2019)
[3] Combriat et al., Soft Matter 16, 2829-2835 (2020)
In this project, the main objective will be to conceive a new kind of acoustic metamaterial using a structured clouds of bubbles. On the conceptual side, in order to understand the collective emission properties of bubbles, the project will be based on the analogy that can be made between acoustic experiments involving resonating bubbles and quantum optics experiments involving cold atoms [2]. On the experimental side, the project will benefit from the unique expertise at LIPhy to trap air bubbles in cages that are fabricated using 3D printing technology [3]. Finally, in order to conceive acoustic metamaterials with optimal properties, the project will involve employing powerful tools developed by the deep-learning community, such as efficient optimizers based on automatic differentiation.
At an initial stage, the project will involve understanding the dynamics of two bubbles, using numerical simulations and experimental measurements. At a later stage, collective emission in more complex systems made of clouds of bubbles will be investigated in simulations and experiments.
Bibliography
[1] Leroy et al., Physical Review B 91, 020301 (2015)[2] Bouchet and Carminati, JOSA A 36, 186-195 (2019)
[3] Combriat et al., Soft Matter 16, 2829-2835 (2020)