High Tech with a Human Touch
Design of Impedance Matched Infrared Antennas Using Optical Vector Near-field Mapping
In any frequency range, an antenna allows a subwavelength-sized sensor to present an appreciable capture cross section to incident electromagnetic radiation. Despite a large technological interest in enhanced infrared sensing, extension of traditional antenna-design concepts into the infrared has remained difficult. Due to substantial spectral variations in the infrared, the frequency-dependent complex permittivities of the optical antenna, substrate and sensor materials must be explicitly accounted for in the design process. Despite progress over the past several years in controlling the spectral, polarization, and angular responses of infrared antennas, and the demonstration of various antenna-coupled IR sensors, including bolometers, tunnel-diode rectifiers and Schottky-diode rectifiers, low collection efficiencies are still considered the technology-limiting challenge. This can be largely attributed to the impedance mismatch caused by reactive surface impedance of metals. However, the only experimentally accessible variable has been the dc voltage appearing across the sensor itself under far-field illumination of the antenna. To quantify the nature of the impedance mismatch as a prerequisite for the targeted design of an impedance-matched optical antenna, a new approach is needed in the form of probing local electric fields on the antenna and sensor.
Researchers seek to increase sensitivity of optical-antenna-coupled detectors by an order of magnitude. We will gain understanding of relevant design parameters and subsequently design impedance-matched optical antenna-sensor combinations. We utilize our newly developed high-spatial-resolution, three-dimensional probe techniques to measure electric fields in the vicinity of the optical antennas. This enables us, for the first time, to determine the infrared-frequency impedance as a function of position. Combined with an iterative design-fabrication-test approach, this will enable development of infrared impedance-matching components.
We scale up the concept of a radiofrequency network analyzer by nine orders of magnitude in frequency. This proven advance yields experimental tools needed to extend the performance of optical antenna-coupled sensors by a similar scale in frequency, making the entire field of passive low frequency electronics operational in the infrared range. Optical antennas have been proposed for a wide range of applications, including nanoscale chemical and photon sensors, nearfield microscopy, and optical rectennas for energy-harvesting. Such devices would transform the field of optics, enabling sensing devices of nano-scale dimensions with order-of-magnitude enhancement in sensitivity, responsivity, and reliability compared to conventional optical techniques.
Specifically, our approach will involve developing and characterizing baseline designs for antennas, transmission lines and bolometric sensors, refining the experimental apparatus for quantifying collection efficiency, exploring the trade space for these baseline designs, extending the method to include tunnel-diode and Schottky-diode rectifiers, exploration of alternate planar-antenna geometries, development of nanoscale impedance-matching network components, and demonstration of impedance-matched IR antennas with at least an order of magnitude better collection efficiency. The proposed research will not only make antenna technology viable at IR frequencies, but lumped-circuit electronics as well, which stands to revolutionize high-frequency sensing and signal processing. In addition, on the fundamental level, this work will extend the traditional realm of antennas into the IR range, exploring the distinct spectral region at the transition between the overdamped visible (plasmon-polariton resonance) and underdamped low-frequency (geometric antenna resonance) ranges.
This research project is a collaboration between the University of North Carolina at Charlotte (Dr. Glenn Boreman), the University of Colorado at Boulder (Dr. Markus Raschke), and Florida Institute of Technology (Dr. Brian Lail).