Researchers at the University of California, Davis have developed a solid-state device that uses Cherenkov Radiation to emit light at a tunable wavelength in the THz to IR range.

Researchers at the University of California, Davis (“UC Davis”) have developed an optical absorber/emitter for thermophotovoltaics application with a tunable emission wavelength.

Researchers at the University of California, Davis have developed an algorithm for designing and identifying complex structures having custom release profiles for controlled drug delivery.

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         While nuclear magnetic resonance (NMR) is one of the most universal synthetic chemistry tools for its ability to measure highly specific kinetic and structural information nondestructively/noninvasively, it is costly and low-throughput primarily due to the small sample-size volumes and expensive equipment needed for stringent magnetic field homogeneity. Conversely, zero-to-ultralow field (ZULF) NMR is an emerging alternative offering similar chemical information but relaxing field homogeneity requirements during detection. ZULF NMR has been further propelled by recent advancements in key componentry, optically pumped magnetometers (OPMs), but suffers in scope due to its low sensitivity and its susceptibility to noise. It has not been possible to detect most organic molecules without resorting to hyperpolarization or 13C enrichment using ZULF NMR.         To overcome these challenges, UC Berkeley researchers have developed a multi-channel ZULF spectrometer that greatly improves on both the sensitivity and throughput abilities of state-of-the art ZULF NMR devices. The novel spectrometer was used in the first reported detection of organic molecules in natural isotopic abundance by ZULF NMR, with sensitivity comparable to current commercial benchtop NMR spectrometers. A proof-of-concept multichannel version of the ZULF spectrometer was capable of measuring three distinct chemical samples simultaneously. The combined sensitivity and throughput distinguish the present ZULF NMR spectrometer as a novel chemical analysis tool at unprecedented scales, potentially enabling emerging fields such as robotic chemistry, as well as meeting the demands of existing fields such as chemical manufacturing, agriculture, and pharmaceutical industries.

      Quantum sensing is rapidly reshaping our ability to discern chemical processes with high sensitivity and spatial resolution. Many quantum sensors are based on nitrogen-vacancy (NV) centers in diamond, with nanodiamonds (NDs) providing a promising approach to chemical quantum sensing compared to single crystals for benefits in cost, deployability, and facile integration with the analyte. However, high-precision chemical quantum sensing suffers from large statistical errors from particle heterogeneity, fluorescence fluctuations related to particle orientation, and other unresolved challenges.      To overcome these obstacles, UC Berkeley researchers have developed a novel microfluidic chemical quantum sensing device capable of high-precision, background-free quantum sensing at high-throughput. The microfluidic device solves problems with heterogeneity while simultaneously ensuring close interaction with the analyte. The device further yields exceptional measurement stability, which has been demonstrated over >103s measurement and across ~105 droplets.  Greatly surpassing the stability seen in conventional quantum sensing experiments, these properties are also resistant to experimental variations and temperature shifts. Finally, the required ND sensor volumes are minuscule, costing only about $0.63 for an hour of analysis. 

UC Santa Cruz investigators initially made a breakthrough discovery by which a gallium-rich alloy of gallium and aluminum containing aluminum nanoparticles that could be formed at relatively low temperatures (between 20 and 40 degrees C) could liberate nearly theoretical quantities of hydrogen in effectively any source of water (NCD 32779) through a chemical reaction requiring no outside electrical input and no corrosive byproducts. One of the eventual useful byproducts of this reaction is alumina (aluminum oxide, Al2O3) a commodity chemical with a wide variety of uses in industry. This technology describes ways of further refining aluminum oxide from the products of this reaction. 

Researchers at the University of California, Davis have developed layered 2D MoS2 nanostructures that have their light-interactive properties improved by intercalation with transition and post-transition metal atoms, specifically Copper and Tin.

Volatile organic compounds (VOCs) are released by various products and during various processes. Ethanol is one such VOC that is released as an important byproduct of alcoholic fermentation. Ethanol emitted during fermentation can be estimated using the amount of liquid lost during storage. The instrumentation needed to accurately quantify ethanol emissions is specialized and costly. Researchers at UC Santa Cruz have developed low-cost VOC sensors that are useful for the wine industry, among others.

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Researchers at UC San Diego have developed a dipeptide composed of two arginine (Arg-Arg) that is capable of inducing the assembly of citrate-capped gold nanoparticles (AuNPs-citrate). Surprisingly, the resulting Arg-Arg-AuNPs are stable over time as the peptide protects the particles from degradation. The assemblies can even be dried without any loss of particles. The assembly of AuNPs-citrate changes their optical properties and the color of the suspension turns from red to blue. Importantly, the assemblies can be dissociated with thiolated polyethylene glycol (HS-PEGs) molecules which leads to the recovery of the initial optical properties of the AuNPs, i.e. the red color of the suspension. Surprisingly, we have observed that such dissociation of AuNPs assemblies is not sensitive to the composition of the medium. It can thus be performed in biological fluids such as pure plasma, saliva, urine, bile, cell lysates or even sea water.

Researchers at the University of California, Davis have developed a self-assembling, fibrous photosensitizer that targets mitochondria in tumor cells for destruction via photodynamic therapy with enhanced localization and potency.

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.

Metamaterials are constructed from regular patterns of simpler constituents known as unit cells. These engineered metamaterials can exhibit exotic mechanical properties not found in naturally occurring materials, and accordingly they have the potential for use in a variety of applications from running shoe soles to automobile crumple zones to airplane wings. Practical design using metamaterials requires the specification of the desired mechanical properties based on understanding the precise unit cell structure and repeating pattern. Traditional design approaches, however, are often unable to take advantage of the full range of possible stress-strain relationships, as they are hampered by significant nonlinear behavior, process-dependent manufacturing errors, and the interplay between multiple competing design objectives. To solve these problems, researchers at UC Berkeley have developed a machine learning algorithm in which designers input a desired stress-strain curve that encodes the mechanical properties of a material. Within seconds, the algorithm outputs the digital design of a metamaterial that, once printed, fully encapsulates the desired properties from the inputted stress-strain curve. This algorithm produces results with a fidelity to the desired curve in excess of 90%, and can reproduce a variety of complex phenomena completely inaccessible to existing methods.

Widespread metal and oxyanion contaminants in groundwater due to industrial activities, land use, and natural geology have resulted in a scarcity in potable water in California and worldwide. These contaminants can be carcinogenic and highly toxic at low concentrations, presenting an urgent need for innovative water purification technologies. However, existing technologies for treating groundwater and brackish water are often energy intensive, non-selective, or not suitable for recovery. Therefore, advances in oxyanion removal technologies could significantly improve the potential of safely using groundwater as an alternative drinking water resource. To address this opportunity, researchers at UC Berkeley have developed a novel multifunctional water filter that exploits the high removal efficiency of toxic metal ions and oxyanions by using two-dimensional (2D) molybdenum disulfide (MoS2) nanosheets. MoS2 exhibits multiple removal pathways towards oxyanions such as Cr (VI) and Se (VI), including adsorption, reduction, and physical filtration. The multifunctionality of the MoS2 filters allows in-situ detoxification of the oxyanions, which could greatly reduce the pressure on waste/waste stream treatment. Moreover, MoS2 filters can be integrated into existing water treatment processes (e.g., low-pressure micro/ultrafiltration and adsorption). This integration allows for the treatment of a wide selection of non-traditional water resources, including groundwater and industrial wastewater, and also reduces the costs of the additional steps required for the removal of toxic metals in traditional water treatment processes. The innovation is more efficient, and more selective in targeting oxyanion species, in comparison to currently available technologies, such as reverse osmosis, nanofiltration, adsorption, ion exchange, and coagulation-precipitation. This novel multifunctional filter could potentially reduce operational costs, simplify maintenance, and minimize the impacts of environmental factors compared to other oxyanion treatment technologies.

Researchers at the University of California, Davis have developed an approach to improve drug delivery to tumors and metastases in the brain. Their multi-barrier tackling delivery strategy has worked to efficiently impact brain tumor management while also achieving increased survival times in anti-cancer efficacy.

Plant viral nanoparticles (plant VNPs) are promising biogenetic nanosystems for the delivery of therapeutic, immunotherapeutic, and diagnostic agents. The production of plant VNPs is simple and highly scalable through molecular farming in plants. Some of the important advances in VNP nanotechnology include genetic modification, disassembly/reassembly, and bioconjugation. Although effective, these methods often involve complex and time-consuming multi-step protocols.

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See patent information below. C-MEMS architecture having carbon structures with high surface areas due to high aspect ratios and nanoscale surface enhancements, and improved systems and methods for producing such structures are provided. Specifically, high aspect ratio carbon structures are microfabricated by pyrolyzing a patterned carbon precursor polymer. Pyrolysing the polymer preferably comprises a multi-step process in an atmosphere of inert and forming gas at high temperatures that trail the glass transition temperature (Tg) for the polymer. The surface area of the carbon microstructures is increases by nanotexturing the surface through oxygen plasma exposure, and by integrating nanoscale structures with the carbon microstructures by exposing the carbon microstructures and a catalyst to hydrocarbon gas. In a preferred embodiment, the carbon microstructures are the source of carbon gas.

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