Research
Photonics & Electromagnetics
Evolutionary optimization of electromagnetic devices
Daniel Weile
- Evolutionary optimization of electromagnetic devices
- Fabrication of Light Emitters Based on Tin-Germanium Alloys
- Devices and Imaging in the High-Terahertz Band
- Antenna Coupled Nano-Photonic Waveguides for MMW FPAs
- Optical biopsy & single-cell spectroscopy
- 50% Efficient Solar Cells
- Electro-optical properties of carbon nanostructures
- High-reliability Vertical Cavity Surface Emitting Lasers (VCSEL's) and VCSEL arrays
- Integration of Optoelectronics and Optical Networks in Advanced Fiberglass/Resin Composites
- Micromechanical Large-Area Modulators for Free-space Optical Communication
- Silicon-based light emitters
- Time-domain integral equation methods for the solution of Maxwell's Equations
- Design of 2D Read-out Integrated Circuit for 3-D Laser-radar Imaging Systems
- Spintronic Sensors and Microwave Phase Detection
- Broadband Silicon-Based Quantum Dot Absorption Materials
- Terahertz Spectroscopy of Doped Nanostructures
- Dilute Nitride Technology for Infrared Detectors
- Germanium-Based Solar Cells for Long Wavelength Sensitivity
Current funding
ARL and Applied EM, Inc.
Group Staff
Graduate Student
Anuraag Mohan
Raymond A. Wildman
The design of electromagnetic devices is a time-consuming and arduous task. Though computational electromagnetics techniques have eliminated some of the burden of laboratory work, in many cases they have merely moved the exertion from the anechoic chamber to the computer room. The research done under this project seeks to rectify this situation by letting computers do the design directly using optimization paradigms inspired by nature.
Foremost among these is Darwinian evolution, nature's method for maximizing survivability. Optimizers based on evolution are known as evolutionary optimizers. While they vary greatly in their details, evolutionary optimizers all work by considering potential designs of some object as an individual in nature, and basing the survival of the individual on its performance in solving the problem at hand. New designs are created through both mutation and hybridization, just as in nature.
Other nature-based optimization paradigms include simulated annealing (which is based on the cooling of metals), particle swarm optimization (which is based on social interactions), and ant colony optimization (which is based on the method ants use to find food). The application of these methods to electromagnetic optimization problems has resulted in marvelous new electromagnetic devices ranging from antennas and absorbers to radomes and photonic crystals.
Recent publications
S. Cui, D. S. Weile, and J. L. Volakis "Novel planar electromagnetic absorber design using genetic algorithms," IEEE Trans. Antennas Propagat., vol. 54, no. 6, pp. 1811-1817, 2006.
S. Cui and D. S. Weile, "Application of a particle swarm optimization scheme to the design of electromagnetic absorbers," IEEE Trans. Antennas Propagat., vol. 53, no. 11, pp. 3616-3624, 2005.
S. Cui, A. Mohan, and D. S. Weile, "Pareto optimal design of absorbers using a parallel elitist nondominated sorting genetic algorithm and the finite element boundary integral method" IEEE Trans. Antennas Propagat., vol. 53, no. 6, pp. 2099-2107, 2005.
