Researchers at UC Irvine have developed a new method to 3D-print free-form silica glass materials which produces products with unparalleled purity, optical clarity, and mechanical strength under far milder conditions than currently available techniques. The novel processing method has potential to radically transform microsystem technology by enabling development of silica-based microsystems.

Researchers from UC San Diego's Neuroelectronic Lab (https://neuroelectronics.ucsd.edu/) demonstrate that they can predict neural activity at deeper layers of the brain by only recording potentials from brain surface. This was achieved by performing multimodal experiments with an ultra-high density transparent graphene electrode technology and developing neural network methods to learn nonlinear dynamic between different modalities. They used cross modality inference to predict the activity at deep layers from surface. Prediction of neural activity at depth have the potential to open up new possibilities for developing minimally invasive neural prosthetics or targeted treatments for various neurological disorders.

Researchers from UC San Diego's Neuroelectronics Lab invented an implantable brain electrode technology which allows recording interactions between different cortex regions or interactions of cortex with other subcortical structures. The technology is called Neuro‐FITM. Flexibility and transparency of Neuro‐ FITM allow integration of electrophysiological recordings with any optical imaging (such as high resolution multiphoton imaging) or stimulation technology (such as optogenetics).

Certain difficult optimization problems, such as the traveling salesman problem, can be solved using so-called analog Ising machines, in which electronic components (such as certain arrangements of diodes or electronic switches) implement an analog of a well-studied physical system known as an Ising machine. The problem is recast so that its solution can be read off from the lowest-energy configuration of the analog Ising machine, a state which the system will naturally evolve towards. While promising, this methodology suffers major drawbacks. Firstly, the number of subunits, known as “spins”, in the analog Ising machines, as well as the number of connections between these subunits, can grow substantially with problem size. Secondly, existing implementations of this principle rely on chip constructions which are optimized for one or a few problems, and are not sufficiently reprogrammable to be repurposed efficiently for other applications. To address these problems, researchers at UC Berkeley have developed a device known as a Field-programmable Ising machine which can be adapted to implement an analog Ising machine using a variety of hardware designs, such as the diodes and switches mentioned above. These Ising machines can be effectively reprogrammed to efficiently solve a wide array of problems across various domains. The inventors have shown that this design can be applied to SAT (“Satisfiability”) problems, a class known to be similar to the traveling salesman problem, in that the number of spins needed and their level of connectivity do not grow too quickly with problem size.

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Researchers at the University of California, Irvine have developed a guided electrokinetic assembly technique that utilizes dielectrophoretic and electroosmotic forces for micro- and nanomanufacturing. This technique provides a new way for assembling microelectronics and living cells for tissue engineering applications.

Researchers at the University of California, Davis have collaborated with colleagues at the University of Washington and Emory University to develop a DNA-based, memory and data storage technology that integrates seamlessly with semiconductor-based technologies and conventional electronic devices.

This technology involves a medical device implanted in the heart’s ventricle that recharges leadless pacemakers. This device contains magnets and inductive coils whose motion is coupled to the contractions of the ventricles in order to create electricity.

A novel wearable, unobtrusive flexible patch designed to facilitate continuous monitoring of fetal heart rate (fHR) and ECG by pregnant women in a home setting.

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.

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.

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.

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.

UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a cost-effective method to produce copper-based nanocomposites with excellent mechanical, electrical and thermal properties.

This invention creates a new graphene nanoribbons (GNR)-based transistor technology capable of pushing past currently projected limits in the operation of digital electronics for combining high current (i.e. high speed) with low-power and high on/off ratio. The inventors describe the design and synthesis of molecular precursors for low band gap armchair graphene nanoribbons (AGNRs) featuring a width of N=11 and N=15 carbon atoms, their growth into AGNRs, and their integration into functional electronic devices (e.g. transistors). N is the number of carbon atoms counted in a chain across the width and perpendicular to the long axis of the ribbon.

UCLA researchers in the Department of Materials Science and Engineering have developed a nanofabrication method for improving the thermal properties of polycrystalline diamond films grown by chemical vapor deposition.

A new approach to photonic integrated circuit fabrication.

UCLA researchers in the Department of Materials Science and Engineering have developed a novel piezoelectric thin film that can control magnetic properties of individual magnetic islands.