activity
20202023
most citedLearning hidden elasticity with deep neural networks

86 citations · 96 across the 5 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn2023

Nature-inspired three-dimensional surface serration topologies enable silent flight by suppressing airfoil-turbulence interaction noise

Zixiao Wei, Stanley Wang, Sean Farris +6

As natural predators, owls fly with astonishing stealth due to the sophisticated serrated surface morphology of their feathers that produces advantageous flow characteristics and f…

cond-mat.mtrl-sci2023

Generalized effective dynamic constitutive relation for heterogeneous media: Beyond the quasi-infinite and periodic limits

Jeong-Ho Lee, Zhizhou Zhang, Grace X. Gu

Dynamic homogenization theories are powerful tools for describing and understanding the behavior of heterogeneous media such as composites and metamaterials. However, a major chall…

cond-mat.mtrl-sci2022★ 10 cited

Maximum Electro-Momentum Coupling in Piezoelectric Metamaterial Scatterers

Jeong-Ho Lee, Zhizhou Zhang, Grace X. Gu

Analogous to electromagnetic bianisotropy, engineered piezoelectric metamaterials can possess electro-momentum coupling between the macroscopic momentum and electric stimuli. This…

cond-mat.mtrl-sci2022

Rational design of piezoelectric metamaterials with tailored electro-momentum coupling

Zhizhou Zhang, Jeong-Ho Lee, Grace X. Gu

Piezoelectric materials have wide sensing and energy transduction applications due to their inherent coupling of mechanical deformation and electric field. Recent discoveries have…

cond-mat.soft2020★ 86 cited

Learning hidden elasticity with deep neural networks

Chun-Teh Chen, Grace X. Gu

We introduce a de novo elastography method to learn the elasticity of solids from measured strains. The deep neural network in our new method is supervised by the theory of elastic…