By Dr Yan Kei Chiang

Preprints

Le DH; Kronowetter F; Chiang YK; Maeder M; Marburg S; Powell DA, 2024, Reconfigurable Manipulation of Sound with a Multi-material 3D-Printed Origami Metasurface, http://arxiv.org/abs/2409.17522v1

Kronowetter F; Maeder M; Chiang Y; Huang L; Schmid J; Oberst S; Powell D; Marburg S, 2023, Direct visualization of a Friedrich-Wintgen quasi-bound state in the continuum, http://dx.doi.org/10.21203/rs.3.rs-2311624/v1

Huang L; Jia B; Pilipchuk AS; Chiang Y; Huang S; Li J; Shen C; Bulgakov EN; Deng F; Powell DA; Cummer SA; Li Y; Sadreev AF; Miroshnichenko AE, 2022, A General Framework of Bound States in the Continuum in an Open Acoustic Resonator, http://dx.doi.org/10.48550/arxiv.2208.01396

Melnikov A; Köble S; Schweiger S; Chiang YK; Marburg S; Powell DA, 2022, Microacoustic metagratings at ultra-high frequencies fabricated by two-photon lithography, http://dx.doi.org/10.48550/arxiv.2202.03490

Huang L; Jia B; Chiang YK; Huang S; Shen C; Deng F; Yang T; Powell DA; Li Y; Miroshnichenko AE, 2022, Topological Supercavity Resonances In the Finite System, http://dx.doi.org/10.48550/arxiv.2201.05324

Sepehrirahnama S; Oberst S; Chiang YK; Powell DA, 2021, Willis coupling-induced acoustic radiation force and torque reversal, http://arxiv.org/abs/2110.01354v2

Sepehrirahnama S; Oberst S; Chiang YK; Powell D, 2021, Acoustic radiation force and radiation torque beyond particles: Effects of non-spherical shape and Willis coupling, http://dx.doi.org/10.48550/arxiv.2107.01775

Chiang YK; Quan L; Peng Y; Sepehrirahnama S; Oberst S; Alù A; Powell D, 2021, Scalable Metagrating for Efficient Ultrasonic Focusing, http://dx.doi.org/10.48550/arxiv.2104.12937

Huang L; Chiang YK; Huang S; Shen C; Deng F; Cheng Y; Jia B; Li Y; Powell DA; Miroshnichenko AE, 2021, Sound Trapping in an Open Resonator, http://dx.doi.org/10.48550/arxiv.2103.11581

Xu L; Rahmani M; Ma Y; Smirnova DA; Kamali KZ; Deng F; Chiang YK; Huang L; Zhang H; Gould S; Neshev DN; Miroshnichenko AE, 2019, Enhanced Light-Matter Interactions in Dielectric Nanostructures via Machine Learning Approach, http://dx.doi.org/10.48550/arxiv.1912.10212

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