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Carbon Nanotube based Variable Frequency Patch-Antenna

Researchers at UCI have developed a patch antenna constructed from carbon nanotubes, whose transmission frequency can be tuned entirely electronically. Additionally, the antenna can be made operable in the microwave to visible frequency regime by simply varying the device dimensions and composition.

Ultrasensitive Photodetectors And Method For Making The Same

Photodetectors for infrared light suffer from low performance and high cost which hampers commercial applications. The researchers have engineered a method to boost the performance of any current photodetectors, especially within the infrared region, using quantum dots.   The researchers have demonstrated world record performance for sensing and detection.

Mapping Ciliary Activity Using Phase Resolved Spectrally Encoded Interferometric Microscopy

Researchers at UCI have developed an imaging technique that can monitor and measure small mobile structures called cilia in our airways and in the oviduct. This invention will serve as a stepping stone for study of respiratory diseases, oviduct ciliary colonoscopy and future clinical translations.

Polarization-Sensitive Optical Coherence Tomography Using a Polarization-Insensitive Detector

A polarization-sensitive optical coherence tomography (PS-OCT) is a common approach to non-invasively imaging in biomedical applications. The inventors have come up with a new way of creating a PS-OCT that is cheaper and simpler.

Integration And Mass Transfer Of Microleds

Brief description not available

Novel Reflective Microscope Objective Lens For All Colors

The researchers at the University of California, Irvine (UCI) have developed a microscopic lens, made entirely of reflective curved surface, where all the light wavelengths are focused at the same time for better resolution and larger field view of the image.

A Phase-Changing Polymer Film for Broadband Smart Windows Applications

UCLA researchers in the Department of Materials Science and Engineering have developed an energy efficient smart window coating with wide light bandwidth and long cycle lifetimes.

High Resolution Laser Speckle Imaging of Blood Flow

Prof. Guillermo Aguilar and his colleagues from the University of California, Riverside have developed a new approach to laser speckle imaging, called Laser Speckle Optical Flow Imaging (LSOFI) to be used for autonomous blood vessel detection and as a qualitative tool for blood flow visualization. LSOFI works by capturing the speckle displacement caused by different physical behavior and use the data to create a mapped image. It has been shown that LSOFI has many advantages over LSCI methods both in temporal and spatial resolution. Namely, LSOFI can be used to produce higher resolution images compared with the LSCI method using less frames. Combining this technology with Graphics Processing Unit (GPU) computation increases the speed of LSOFI, so GPU enabled LSOFI shows potential to create a fast and fully functional quasi-real time blood flow imaging system.  Fig 1: Comparison of blood flow imaging techniques applied to the raw image. The shown results are for Laser Speckle Optical Flow Imaging (LSOFI) using the Farneback Optical Flow algorithm, traditional Laser Speckle Imaging (LSI), and Temporal Frame Averaging (sLASCA).  

Enhanced Block Copolymer Self-Assembly

Brief description not available

Development of a CMOS-Compatible, Nano-photonic, Laser

Researchers at the University of California, Davis have developed a new class of lasers and amplifiers that uses a CMOS-compatible electronics platform - and can also be applied to nano-amplifiers and nano-lasers applications.

Real-time, Passive Non-Line-of-Sight Imaging with Thermal Camera by Exploiting Bidirectional Reflectance Distribution Function

UCLA researchers in the Department of Electrical and Computer Engineering have developed a Non-line-of-sight (NLOS) Imaging System using low cost thermal cameras that enable 3D recovery of NLOS heat source for imaging around corners.

Compact Ion Gun for Ion Trap Surface Treatment in Quantum Information Processing Architectures

Electromagnetic noise from surfaces is one of the limiting factors for the performance of solid state and trapped ion quantum information processing architectures. This noise introduces gate errors and reduces the coherence time of the systems. Accordingly, there is great commercial interest in reducing the electromagnetic noise generated at the surface of these systems.Surface treatment using ion bombardment has shown to reduce electromagnetic surface noise by two orders of magnitude. In this procedure ions usually from noble gasses are accelerated towards the surface with energies of 300eV to 2keV. Until recently, commercial ion guns have been repurposed for surface cleaning. While these guns can supply the ion flux and energy required to prepare the surface with the desired quality, they are bulky and limit the laser access, making them incompatible with the requirements for ion trap quantum computing.To address this limitation, UC Berkeley researchers have developed an ion gun that enables in-situ surface treatment without sacrificing high optical access, enabling in situ use with a quantum information processor.

Athermal Nanophotonic Lasers

Researchers at the University of California, Davis have developed a nanolaser platform built from materials that do not exhibit optical gain.

Photonic-Electronic, Real-Time, Signal Processing

Researchers at the University of California, Davis have developed a method for ultra-wideband and highly precise, photonic-electronic, signal processing. This technology is capable of high-speed, real-time signal correlation/processing by exploiting RF-photonics, ultra-stable optical frequency combs and high precision electronics.

Higher-Speed and More Energy-Efficient Signal Processing Platform for Neural Networks

Researchers at the University of California, Davis have developed a nanophotonic-based platform for signal processing and optical computing in algorithm-based neural networks that is faster and more energy-efficient than current technologies.

Multi-Wavelength, Nanophotonic, Neural Computing System

Researchers at the University of California, Davis have developed a multi-wavelength, Spiking, Nanophotonic, Neural Reservoir Computing (SNNRC) system with high-dimensional (HD) computing capability.

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