Recent progresses on metamaterials for optical absorption and sensing: A review

Y Yao, Z Liao, Z Liu, X Liu, J Zhou, G Liu… - Journal of Physics D …, 2021 - iopscience.iop.org
Metamaterials (MMs) offer great potential for achieving optical absorption due to their novel
electromagnetic properties. MM absorbers can overcome the thickness limitation and …

Machine learning–assisted design of material properties

S Kadulkar, ZM Sherman, V Ganesan… - Annual Review of …, 2022 - annualreviews.org
Designing functional materials requires a deep search through multidimensional spaces for
system parameters that yield desirable material properties. For cases where conventional …

Efficient design of a dielectric metasurface with transfer learning and genetic algorithm

D Xu, Y Luo, J Luo, M Pu, Y Zhang, Y Ha… - Optical Materials …, 2021 - opg.optica.org
Machine learning has been widely adopted in various disciplines as they offer low-
computational cost solutions to complex problems. Recently, deep learning-enabled …

Design of an ultra-broadband terahertz absorber based on a patterned graphene metasurface with machine learning

Z Ding, W Su, Y Luo, L Ye, H Wu, H Yao - Journal of Materials …, 2023 - pubs.rsc.org
The development of patterned graphene metasurface absorbers (PGMAs) offers potential
solutions for achieving light weight, thinness, wide absorption bandwidth, and tunable …

Machine learning aided design and optimization of thermal metamaterials

C Zhu, EA Bamidele, X Shen, G Zhu, B Li - Chemical Reviews, 2024 - ACS Publications
Artificial Intelligence (AI) has advanced material research that were previously intractable,
for example, the machine learning (ML) has been able to predict some unprecedented …

Absorption and diffusion enabled ultrathin broadband metamaterial absorber designed by deep neural network and PSO

J Chen, W Ding, XM Li, X **, KP Ye… - IEEE Antennas and …, 2021 - ieeexplore.ieee.org
With absorption and interference cancellation, lossy metamaterials can achieve broadband
electromagnetic wave absorption. However, the design of such metamaterial absorbers …

Manifold learning for knowledge discovery and intelligent inverse design of photonic nanostructures: breaking the geometric complexity

M Zandehshahvar, Y Kiarashinejad, M Zhu… - Acs …, 2022 - ACS Publications
Here, we present a new approach based on manifold learning for knowledge discovery and
inverse design with minimal complexity in photonic nanostructures. Our approach builds on …

Deep learning-driven forward and inverse design of nanophotonic nanohole arrays: streamlining design for tailored optical functionalities and enhancing accessibility

T Jahan, T Dash, SE Arman, R Inum, S Islam, L Jamal… - Nanoscale, 2024 - pubs.rsc.org
In nanophotonics, nanohole arrays (NHAs) are periodic arrangements of nanoscale
apertures in thin films that provide diverse optical functionalities essential for various …

Deep-learning-empowered holographic metasurface with simultaneously customized phase and amplitude

R Zhu, J Wang, X Fu, X Liu, T Liu, Z Chu… - … Applied Materials & …, 2022 - ACS Publications
Metasurfaces with simultaneously and independently controllable amplitude and phase
have provided a higher degree of freedom in manipulating electromagnetic (EM) waves …

Inverse design of a Helmholtz resonator based low-frequency acoustic absorber using deep neural network

K Mahesh, S Kumar Ranjith, RS Mini - Journal of Applied Physics, 2021 - pubs.aip.org
The design of low-frequency sound absorbers with broadband absorption characteristics
and optimized dimensions is a pressing research problem in engineering acoustics. In this …