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1. Electro-optic transduction in silicon via gigahertz-frequency nanomechanics

   https://doi.org/10.1364/OPTICA.479162  

   Zhao, Han; Bozkurt, Alkim; Mirhosseini, Mohammad (June 2023, Optica)

   Interfacing electronics with optical fiber networks is key to the long-distance transfer of classical and quantum information. Piezo-optomechanical transducers enable such interfaces by using gigahertz-frequency acoustic vibrations as mediators for converting microwave photons to optical photons via the combination of optomechanical and piezoelectric interactions. However, despite successful demonstrations, efficient quantum transduction remains out of reach due to the challenges associated with hybrid material integration and increased loss from piezoelectric materials when operating in the quantum regime. Here, we demonstrate an alternative approach in which we actuate 5-GHz phonons in a conventional silicon-on-insulator platform. In our experiment, microwave photons resonantly drive a phononic crystal oscillator via the electrostatic force realized in a charge-biased narrow-gap capacitor. The mechanical vibrations are subsequently transferred via a phonon waveguide to an optomechanical cavity, where they transform into optical photons in the sideband of a pump laser field. Operating at room temperature and atmospheric pressure, we measure a microwave-to-optical photon conversion efficiency of 1.72±0.14×10⁻⁷in a 3.3 MHz bandwidth. Our results mark a stepping stone towards quantum transduction with integrated devices made from crystalline silicon, which promise efficient high-bandwidth operation and integration with superconducting qubits. Additionally, the lack of need for piezoelectricity or other intrinsic nonlinearities makes our approach applicable to a wide range of materials for potential applications beyond quantum technologies. 

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2. Independently Tunable Thermal Conductance and Phononic Band Gaps of 3D Lattice Materials

   https://doi.org/10.1002/adem.201901004  

   Babatola, Oluseyi; Patil, Ganesh U.; Hsieh, Daniel; Matlack, Kathryn H.; Sinha, Sanjiv (December 2019, Advanced Engineering Materials)

   Lattice materials provide unusual thermal and vibrational properties but not within the same structure. Thermal and vibrational multifunctionality is, however, crucial for thermomechanical applications such as automotive, aerospace, building, transportation, and energy infrastructure. In applications involving mobility, both high heat transfer and low mass are desired. Although there have been various efforts to design multifunctional lattice materials, the focus has largely remained on quasi‐static mechanical and thermal properties or mechanical and vibrational properties. Herein, designs of realizable lattice materials are reported, which are inherently thermally resistive, with vastly improved thermal conductance and omnidirectional phononic band gaps. By redesigning the truss structures to serve as interconnected heat pipes, a three‐order‐of‐magnitude improvement in the specific thermal conductance is found. Nodal masses at truss junctions are further used to obtain full vibrational band gaps. It is shown that it is possible to independently tune vibrational and thermal properties within the same structure. This work provides background for the design and fabrication of multifunctional lattice materials that simultaneously prevent structural vibrations and enhance heat conduction. 

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3. Merging mechanical bound states in the continuum in high-aspect-ratio phononic crystal gratings

   https://doi.org/10.1038/s42005-024-01692-9  

   Tong, Hao; Liu, Shengyan; Fang, Kejie (December 2024, Communications Physics)

   Abstract Mechanical bound states in the continuum (BICs) present an alternative avenue for developing high-frequency, high-Qmechanical resonators, distinct from the conventional band structure engineering method. While symmetry-protected mechanical BICs have been realized in phononic crystals, the observation of accidental mechanical BICs—whose existence is independent of mode symmetry and tunable by structural parameters—has remained elusive. This challenge is primarily attributed to the additional radiation channel introduced by the longitudinal component of elastic waves. Here, we employ a coupled wave theory to predict and experimentally demonstrate mechanical accidental BICs within a high-aspect-ratio gallium arsenide phononic crystal grating. We observe the merging process of accidental BICs with symmetry-protected BICs, resulting in reduced acoustic radiation losses compared to isolated BICs. This finding opens up new possibilities for phonon trapping using BIC-based systems, with potential applications in sensing, transduction, and quantum measurements. 

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4. Experimental realization of an additively manufactured monatomic lattice for studying wave propagation

   https://doi.org/10.1119/5.0085124  

   Mork, Nehemiah; Kuchibhatla, Sai A. R.; Leamy, Michael J.; Fronk, Matthew D. (January 2023, American Journal of Physics)

   Increasing interest in wave propagation in phononic systems and metamaterials motivates the development of experimental designs, measurement techniques, and fabrication methods for use in basic research and classroom demonstrations. The simplest phononic system, the monatomic chain, exhibits rich physics such as dispersion and frequency-domain filtering. However, a limited number of experimental studies showcase monatomic chains for macroscale observation of phonons. Herein, we discuss the design, fabrication, and testing of monatomic lattices as enabled by three-dimensional (3D) printing. Using this widely available technology, we provide design guidelines for realization of a monatomic chain composed of 3D printed serpentine springs and press-fitted cylindrical masses. We also present measurement techniques that record propagating waves and algorithms for the experimental determination of dispersion behavior. 

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5. Inverse Design Framework With Invertible Neural Networks for Passive Vibration Suppression in Phononic Structures

   https://doi.org/10.1115/1.4052300  

   Oddiraju, Manaswin; Behjat, Amir; Nouh, Mostafa; Chowdhury, Souma (February 2022, Journal of Mechanical Design)

   null (Ed.)

   Abstract Automated inverse design methods are critical to the development of metamaterial systems that exhibit special user-demanded properties. While machine learning approaches represent an emerging paradigm in the design of metamaterial structures, the ability to retrieve inverse designs on-demand remains lacking. Such an ability can be useful in accelerating optimization-based inverse design processes. This paper develops an inverse design framework that provides this capability through the novel usage of invertible neural networks (INNs). We exploit an INN architecture that can be trained to perform forward prediction over a set of high-fidelity samples and automatically learns the reverse mapping with guaranteed invertibility. We apply this INN for modeling the frequency response of periodic and aperiodic phononic structures, with the performance demonstrated on vibration suppression of drill pipes. Training and testing samples are generated by employing a transfer matrix method. The INN models provide competitive forward and inverse prediction performance compared to typical deep neural networks (DNNs). These INN models are used to retrieve approximate inverse designs for a queried non-resonant frequency range; the inverse designs are then used to initialize a constrained gradient-based optimization process to find a more accurate inverse design that also minimizes mass. The INN-initialized optimizations are found to be generally superior in terms of the queried property and mass compared to randomly initialized and inverse DNN-initialized optimizations. Particle swarm optimization with INN-derived initial points is then found to provide even better solutions, especially for the higher-dimensional aperiodic structures. 

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