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High-Speed, High-Memory NMR Spectrometer and Hyperpolarizer

         Recent advancements in nuclear magnetic resonance (NMR) spectroscopy have underscored the need for novel instrumentation, but current commercial instrumentation performs well primarily for pre-existing, mainstream applications. Modalities involving, in particular, integrated electron-nuclear spin control, dynamic nuclear polarization (DNP), and non-traditional NMR pulse sequences would benefit greatly from more flexible and capable hardware and software. Advances in these areas would allow many innovative NMR methodologies to reach the market in the coming years.          To address this opportunity, UC Berkeley researchers have developed a novel high-speed, high-memory NMR spectrometer and hyperpolarizer. The device is compact, rack-mountable and cost-effective compared to existing spectrometers. Furthermore, the spectrometer features robust, high-speed NMR transmit and receive functions, synthesizing and receiving signals at the Larmor frequency and up to 2.7GHz. The spectrometer features on-board, phase-sensitive detection and windowed acquisition that can be carried out over extended periods and across millions of pulses. These and additional features are tailored for integrated electron-nuclear spin control and DNP. The invented spectrometer/hyperpolarizer opens up new avenues for NMR pulse control and DNP, including closed-loop feedback control, electron decoupling, 3D spin tracking, and potential applications in quantum sensing.

Computation Method For 3D Point-Cloud Holography

 The dynamic patterning of 3D optical point clouds has emerged as a key enabling technology in volumetric processing across a number of applications. In the context of biological microscopy, 3D point cloud patterning is employed for non-invasive all-optical interfacing with cell ensembles. In augmented and virtual reality (AR/VR), near-eye display systems can incorporate virtual 3D point cloud-based objects into real-world scenes, and in the realm of material processing, point cloud patterning can be mobilized for 3D nanofabrication via multiphoton or ultraviolet lithography. Volumetric point cloud patterning with spatial light modulators (SLMs) is therefore widely employed across these and other fields. However, existing hologram computation methods, such as iterative, look-up table-based and deep learning approaches, remain exceedingly slow and/or burdensome. Many require hardware-intensive resources and sacrifices to volume quality.To address this problem, UC Berkeley researchers have developed a new, non-iterative point cloud holography algorithm that employs fast deterministic calculations. Compared against existing iterative approaches, the algorithm’s relative speed advantage increases with SLM format, reaching >100,000´ for formats as low as 512x512, and optimally mobilizes time multiplexing to increase targeting throughput. 

Systems and Methods for Identifying Anomalous Nuclear Radioactive Sources

Real-time radiation monitoring is critical for public health and emergency response. High-frequency monitoring can generate large amounts of data for dozens of radioactive isotopes though. There is a growing demand for compact radiation detection devices that are also able to quickly and autonomously process these large datasets for anomalies. A UC Santa Cruz researcher has developed machine learning software that synthesizes real-time radiation monitoring data in situ to detect radioactive anomalies.

Magnetometer Based On Spin Wave Interferometer

Brief description not available

Highly Tunable Magnetic Liquid Crystals

Brief description not available

Machine Learning-Based Monte Carlo Denoising

Brief description not available

High-Frequency Imaging and Data Transmission Using a Re-configurable Array Source with Directive Beam Steering

Researchers at the University of California, Davis have developed a reconfigurable radiator array that produces a high frequency directed beam via uninterrupted, scalable, electronic beam steering.

Dynamic Target Ranging With Multi-Tone Continuous Wave Lidar Using Phase Algorithm

Researchers at the University of California, Irvine have developed a novel algorithm that is designed to be integrated with current multi-tone continuous wave (MTCW) lidar technology in order to enhance the capability of lidar to acquire range (distance) of fast-moving targets as well as simultaneous velocimetry measurements. This technology revolutionizes remote sensing by providing high precision, single-shot simultaneous ranging and velocimetry measurements without the need for sweeping.  

Phased-Locked Loop Coupled Array for Phased Array Applications

Researchers at the University of California, Davis have developed a phased-locked loop coupled array system capable of generating phase shifts in phased array antenna systems - while minimizing signal losses.

Embedded Power Amplifier

Researchers at the University of California, Davis have developed an amplifier technology that boosts power output in order to improve data transmission speeds for high-frequency communications.

Compositions and Methods of Isothermal Nucleic Acid Detection

An improved method for isothermal nucleic acid detection based on a loop mediated isothermal amplification (LAMP) technique that can be broadly applied for nucleic acid diagnostics.LAMP is an isothermal amplification method that amplifies DNA or RNA. This iteration of LAMP allows for the integration of any short DNA sequence, including tags, restriction enzyme sites, or promoters, into an isothermally amplified amplicon. The technique presented by the inventors allows for the insertion of sequence tags up to 35 nt into the flanking regions of the LAMP amplicon using the forward and backward inner primers (FIP and BIP), and loop primers. The inventors have demonstrated insertion of sequence fragments into the 5’ and middle regions of the FIP and BIP primers, and the 5’ region of the loop primers. In some embodiments, the sequence tag comprises a T7 RNA polymerase promoter, which is then incorporated into the LAMP amplicon (termed RT-LAMP/T7). With the addition of T7 polymerase, the amplicon can be in vitro transcribed, leading to additional amplification of the target molecule into an RNA substrate. This improves the efficiency of the amplification reaction and enables substrate conversion into different nucleic acid types.In other embodiments, the amplified RNA sequence can be detected by CRISPR enzymes, such as RNA-targeting Cas13 systems. 

Sub-Carrier Successive-Approximation Mm-Wave Radar For High-Resolution 3D Imaging

UCLA researchers in the Department of Electrical Engineering have developed a sub-carrier successive approximation radar (SAR) system with a sufficiently high accuracy to capture three-dimensional images of objects concealed either under the clothing of a person, or within small packages. 

External Cavity Laser Based Upon Metasurfaces

UCLA researchers in the Department of Electrical Engineering have developed a novel approach for terahertz (THz) quantum-cascade (QC) lasers to achieve scalable output power, high quality diffraction limited, and directive output beams.

A Video Based Hierarchical Vehicle Classification System

Background: Transportation and vehicle classification systems are becoming smarter and more automated. For example, electronic toll collection systems have been introduced and drivers are not required to stop, eliminating road delays. New technologies have also been added to these systems that enable service providers to acquire data on what type of vehicles are utilizing their amenities as well as vehicle identification for safety & control purposes.  Brief Description: UCR Researchers have developed a method and system for vehicle classification using video imaging. This novel invention entails a vehicle ground clearance measurement system along with a video camera that captures a travelling vehicle and categorizes it into a vehicle class. The cameras on current methods and systems rely on side views of the vehicle, which can easily be obstructed by other vehicles.

An Ultra-Sensitive Method for Detecting Molecules

To-date, plasmon detection methods have been utilized in the life sciences, electrochemistry, chemical vapor detection, and food safety. While passive surface plasmon resonators have lead to high-sensitivity detection in real time without further contaminating the environment with labels. Unfortunately, because these systems are passively excited, they are intrinsically limited by a loss of metal, which leads to decreased sensitivity. Researchers at the University of California, Berkeley have developed a novel method to detect distinct molecules in air under normal conditions to achieve sub-parts per billion detection limits, the lowest limit reported. This device can be used detecting a wide array of molecules including explosives or bio molecular diagnostics utilizing the first instance of active plasmon sensor, free of metal losses and operating deep below the diffraction limit for visible light.  This novel detection method has been shown to have superior performance than monitoring the wavelength shift, which is widely used in passive surface plasmon sensors. 

Highly Accurate Occupancy Estimation Using RF Signals and Wi-Fi

A framework that counts the number of people in an area based on RF signals and a Wi-Fi card or network. 

Distributed Scalable Interaction Paradigm for Multi-User Interaction Across Tiled Multi-Displays

The technology is a method for multiple users to interact simultaneously with multiple tiled displays.Under this technology, multiple users are allowed to interact with a tiled display with a distributed registration technique.It features easy scalability across different applications, modalities and users and user interactions involve hand gestures or are laser-based.

Image Filtering Algorithm for Enhanced Noise Removal and Feature Preservation

UCLA researchers in the Department of Chemistry & Biochemistry have developed a novel image filtering algorithm that removes image noise while preserving image features with unprecedented fidelity.   

Crystal Laser Wakefield Accelerator and Its Applications

The technology is a development of a more efficient particle accelerator in terms of energy, cost and space considerations. It is used in particle acceleration applications (cancer treatment, manufacture of components for electronic devices, etc.) The technology is an ultra-compact particle accelerator and particle source. The properties include: Laser Wakefield Accelerator in a solid medium, i.e. crystal in which the Laser Wakefield by charged particle beam bunch. The driver is a high intensity pulsed x-ray. The technology applicable to electron, proton, and ion acceleration and can be used for ultra-compact particle source (neutrons, muons, and neutrinos)

A Neuromorphic Robot that Interacts with People Through Tactile Sensing and Bi-directional Learning

The device is an interactive neuromorphic robot, using to mimic neuro-biological architectures and learning.Properties include:a spiking neural network to control robot behavior, inexpensive parts which are easily available, and two-way learning and behavior shaping.The technology is autonomous, highly mobile, and includes on-board measurement equipment.

Cacophony: A Framework for Next Generation Software Sensors

The technology is a software architecture for providing robust predictions for software systems from cloud sourced data points. Properties include:the ability to “wrap” existing software sensors with additional services. The technology is used by executing software on a cloud based server and manipulating data points from user update systems, such as Waze, and provide predictive services around these data points.

Low-Duty-Cycle Continuous-Wave Photoconductive Terahertz Imaging and Spectroscopy Systems

Professor Mona Jarrahi in the UCLA Department of Electrical Engineering has developed a technique for operating continuous-wave (CW) terahertz imaging and spectroscopy systems based on photoconductive terahertz sources and/or detectors that uses a low-duty-cycle optical pump, achieving high radiation powers and detection sensitivities without causing thermal breakdown, as well as higher quality image and spectra data.

Sensor-Assisted Facial Authentication System For Smartphones

Researchers at the University of California, Davis have developed a method using standard mobile device sensors assisting with facial authentication to overcome the limitations faced by current methods.

Superhydrophobic Induced High Numerical Plastic Lenses

The application of novel manufacturing techniques, chemical modifications and alternative materials produces the next generation of lenses. These lenses are inexpensive, contain improved numerical aperture and can be easily manufactured. Overall, these improvements create new applications for miniaturized optical and optical electronic devices.

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