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Related Concept Videos

Passive Filters01:27

Passive Filters

600
Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
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Active Filters01:25

Active Filters

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Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
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Biasing of Metal-Semiconductor Junctions01:27

Biasing of Metal-Semiconductor Junctions

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Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
In Schottky junctions, where the semiconductor is n-type, applying a positive voltage to the metal relative to the semiconductor reduces its Fermi...
330
Bandpass Sampling01:17

Bandpass Sampling

253
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
253

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Related Experiment Video

Updated: Sep 5, 2025

Scalable Solution-processed Fabrication Strategy for High-performance, Flexible, Transparent Electrodes with Embedded Metal Mesh
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Bandpass Filter Integrated Metalens Based on Electromagnetically Induced Transparency.

Dongzhi Shan1,2, Jinsong Gao1,2,3, Nianxi Xu1

  • 1Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Nanomaterials (Basel, Switzerland)
|July 9, 2022
PubMed
Summary

This study presents a novel bandpass filter integrated metalens for long-wavelength infrared (LWIR) imaging. The design combines focusing and filtering capabilities into a single metasurface device, improving imaging performance by reducing stray light.

Keywords:
bandpass filterelectromagnetically induced transparency metasurfaceintegrated deviceslong-wavelength infraredmetalens

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Area of Science:

  • Optics and Photonics
  • Metamaterials and Nanophotonics

Background:

  • Metalenses, while effective diffractive optical elements, suffer from reduced bandwidth with increasing aperture size, degrading imaging performance.
  • Integrating filtering capabilities into metalenses is crucial for enhancing optical system efficiency, especially in the long-wavelength infrared (LWIR) spectrum.

Purpose of the Study:

  • To design and validate a bandpass filter integrated metalens utilizing electromagnetically induced transparency (EIT) for LWIR imaging.
  • To demonstrate the feasibility of combining focusing and filtering functions within a single metasurface device for compact optical systems.

Main Methods:

  • Design of a metalens incorporating an EIT metasurface for bandpass filtering.
  • Simulation of a 300-μm-diameter metalens with an f-number of 0.8 to validate the design approach.
  • Utilizing identical material composition and fabrication processes for both the metalens and EIT metasurface.

Main Results:

  • The integrated metalens achieved focusing near the diffraction limit at the target LWIR wavelength.
  • The EIT metasurface effectively minimized stray light from non-target wavelengths without compromising focusing capabilities.
  • Successful integration of bandpass filtering and focusing functionalities into a single metasurface device.

Conclusions:

  • The proposed bandpass filter integrated metalens design method is feasible for LWIR imaging applications.
  • This approach offers a promising solution for developing compact and high-performance optical systems in the LWIR range.
  • The integration of EIT metasurfaces provides a pathway for advanced optical functionalities in miniaturized systems.