Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Induced Electric Fields: Applications01:27

Induced Electric Fields: Applications

An important distinction exists between the electric field induced by a changing magnetic field and the electrostatic field produced by a fixed charge distribution. Specifically, the induced electric field is nonconservative because it does not work in moving a charge over a closed path. In contrast, the electrostatic field is conservative and does no net work over a closed path. Hence, electric potential can be associated with the electrostatic field but not the induced field. The following...
Generating Electromagnetic Radiations01:10

Generating Electromagnetic Radiations

The German physicist Heinrich Hertz (1857–1894) was the first to generate and detect certain types of electromagnetic waves in the laboratory. Starting in 1887, he performed a series of experiments that confirmed the existence of electromagnetic waves and verified that they travel at the speed of light. Hertz used an alternating-current RLC (resistor-inductor-capacitor) circuit that resonated at a known frequency and connected it to a loop of wire. High voltages induced across the gap in the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

All-LCP Terahertz Metasensor with Dual Quasi-BIC Resonances for Dual-Range Refractive Index Sensing.

Biosensors·2026
Same author

Biodegradable Silicon-Based Electromagnetic Energy Harvester toward Wireless Power Supply.

ACS applied materials & interfaces·2025
Same author

Multi-Mode Coupling Enabled Broadband Coverage for Terahertz Biosensing Applications.

Biosensors·2025
Same author

Multi-Degree-of-Freedom Stretchable Metasurface Terahertz Sensor for Trace Cinnamoylglycine Detection.

Biosensors·2024
Same author

Surface plasmon-cavity hybrid state and its graphene modulation at THz frequencies.

Nanophotonics (Berlin, Germany)·2024
Same author

Chalcogenide phase-change material advances programmable terahertz metamaterials: a non-volatile perspective for reconfigurable intelligent surfaces.

Nanophotonics (Berlin, Germany)·2024

Related Experiment Video

Updated: Jun 14, 2026

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor
07:28

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor

Published on: August 30, 2012

11.2K

Evolutionary Diffusion Framework Empowering High-Performance Freeform Terahertz Metasurface Sensing.

Chenxi Zhang1, Mengya Pan1,2, Qiankai Hong1

  • 1School of Integrated Circuits, Shandong University, Jinan 250100, China.

Sensors (Basel, Switzerland)
|March 28, 2026
PubMed
Summary

This study introduces a new generative-evolutionary strategy for designing Terahertz (THz) metasurface sensors. This method efficiently creates bespoke sensors with high sensitivity, overcoming data limitations in traditional designs.

Keywords:
conditional diffusion modeldeep learningfreeform designinverse designterahertz metasurface sensors

More Related Videos

Simulation, Fabrication and Characterization of THz Metamaterial Absorbers
13:44

Simulation, Fabrication and Characterization of THz Metamaterial Absorbers

Published on: December 27, 2012

16.0K
Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces
09:33

Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces

Published on: June 7, 2019

6.8K

Related Experiment Videos

Last Updated: Jun 14, 2026

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor
07:28

Terahertz Microfluidic Sensing Using a Parallel-plate Waveguide Sensor

Published on: August 30, 2012

11.2K
Simulation, Fabrication and Characterization of THz Metamaterial Absorbers
13:44

Simulation, Fabrication and Characterization of THz Metamaterial Absorbers

Published on: December 27, 2012

16.0K
Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces
09:33

Demonstration of Equal-Intensity Beam Generation by Dielectric Metasurfaces

Published on: June 7, 2019

6.8K

Area of Science:

  • Optics and Photonics
  • Materials Science
  • Metamaterials

Background:

  • Metasurfaces enable advanced light-matter interactions but face design challenges.
  • Traditional methods are computationally expensive; deep learning requires vast data and has limited design space exploration.

Purpose of the Study:

  • To develop an efficient inverse design strategy for Terahertz (THz) metasurface sensors.
  • To overcome data bottlenecks and design space limitations in current deep learning approaches.

Main Methods:

  • A multi-model-driven generative-evolutionary strategy (GES) was proposed.
  • The GES utilizes a Conditional Diffusion Generator (CDG) and an Attention-Enhanced Residual Network (ARN).
  • This framework explores 2100 potential configurations, selectively generating high-potential data in stages.

Main Results:

  • Inversely designed metasurfaces demonstrated high-contrast resonance peaks.
  • Exceptional sensitivity was achieved across low, mid, and high THz bands.
  • The GES effectively addressed data requirements and design space limitations.

Conclusions:

  • The proposed GES offers an efficient paradigm for designing high-performance functional metamaterials.
  • This approach significantly accelerates the development of application-specific THz sensing technologies.
  • The framework enables on-demand inverse design of bespoke THz metasurface sensors.