Researchers at the University of California Davis have developed a technology that enables the provable editing of DNNs (deep neural networks) to meet specified safety criteria without altering their architecture.

Researchers at the University of California, Davis have developed a technology that introduces a novel approach to hardware security using photonic physically unclonable functions for true random number generation and biometric ID.

A groundbreaking technology that mimics the dynamic color-changing functionality of the blue-ringed octopus for applications in camouflage, signaling, and beyond.

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Researchers at the University of California, Davis have developed a green technology designed for the efficient storage and discharge of heat energy sourced from intermittent green energy supplies.

Optical atomic clocks have taken a giant leap in recent years, with several experiments reaching uncertainties at the 10−18 level. The development of synchronized clock networks and transportable clocks that operate in extreme and distant environments would allow clocks based on different atomic standards or placed in separate locations to be compared. Such networks would enable relativistic geodesy, tests of fundamental physics, dark matter searches, and more. However, the leading neutral-atom optical clocks operate on wavelengths of 698 nm (Sr) and 578 nm (Yb). Light at these wavelengths is strongly attenuated in optical fibers, posing a challenge to long-distance time transfer. Those wavelengths are also inconvenient for constructing the ultrastable lasers that are an essential component of optical clocks. To address this problem, UC Berkeley researchers have developed a new, laser-cooled neutral atom optical atomic clock that operates in the telecommunication wavelength band. The leveraged atomic transitions are narrow and exhibit much smaller black body radiation shifts than those in alkaline earth atoms, as well as small quadratic Zeeman shifts. Furthermore, the transition wavelengths are in the low-loss S, C, and L-bands of fiber-optic telecommunication standards, allowing the clocks to be integrated with robust laser technology and optical amplifiers. Additionally, the researchers have identified magic trapping wavelengths via extensive studies and have proposed approaches to overcome magnetic dipole-dipole interactions. Together, these features support the development of fiber-linked terrestrial clock networks over continental distances.

         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.

Rapid antimicrobial susceptibility testing (AST) is a method for quickly determining the most effective antibiotic therapy for patients with bacterial infections. These techniques enable the detection and quantification of antibiotic-resistant and susceptible bacteria metabolites at concentrations near or below ng/mL in complex media. Employing bacterial metabolites as a sensing platform, the system integrates machine learning data analysis processes to differentiate between antibiotic susceptibility and resistance in clinical infections within an hour. With the results, a clinician can prescribe appropriate medicine for the patient's bacterial infection.

Gas diffusion electrodes are used in electrochemical applications to produce value added chemicals such as H2O2. Carbon paper and carbon cloth are used as substrates in gas diffusion cathodes. However, carbon-based substrates are not mechanically sturdy as they can develop cracks under flexion. They are also expensive ($150 for a 310-micron thick carbon paper of 40cm X 40cm). UC Berkeley researchers have created air-cathodes made with a non-reacting metal mesh as the supporting conducting substrate. The metal may be in the form of an alloy or coating, such as one metal on another, or a metal coating on a non-metal substrate.  The metal air cathodes avoid the use of carbon paper altogether, are more cost effective, flexible yet strong and durable, and provide robust gas-diffusion cathodes for sustained production of H2O2 over long-periods of operation.  

An increase in threatening situations in school environments requires individuals to be ready to secure egress doors quickly to prevent intruders and other uninvited individuals from entering a space. Given the numerous variables that can affect where, when, how, or even if individuals can shelter-in-place during an emergency, there is a need for a simple, portable, lightweight, and cost-effective door security device that installs quickly and easily—without tools—on outward swinging doors from within the room being secured. The inventors have developed a device that can secure an outward swinging egress door from within a room, enabling occupants of a space to quickly barricade a room's entrance during a lockdown or other emergency requiring shelter-in-place protocols. In contrast to other known door security devices and systems for securing a hinged, outward swinging egress door, this improved door security device is portable, lightweight, easy-to-install without tools, and adaptable to doors with different handle, jamb, and casing combinations or measurements. This discrete, on-the-go security device for securing an outward swinging door is not dependent on any furnishings or security apparatus of a particular space. 

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.

The inventors have developed an engineering approach to identify novel and nonobvious membrane-associated accessory protein (MAAP) sequence variants that confer increased Adeno-associated virus (AAV) secretion during packaging. The technique is based upon the iterative process of sequence diversification and selection of functional gene variants known as directed evolution. First, the inventors generated a library of more than 1E6 MAAP variants. The variants were subjected to five rounds of packaging into an AAV2 capsid for which MAAP expression was inactivated without altering the viral protein VP1 open reading frame (ORF) (AAV2-MAAP-null). Among each iterative packaging round, the inventors observed a progressive increase in both the overall titer and ratio of secreted vector genomes conferred by the bulk selected MAAP library population. Next-generation sequencing uncovered common mutational features that were enriched up to over 10,000-fold on the amino acid level. Individual MAAP variants were isolated and systematically tested for effect on recombinant AAV2-MAAP-null packaging in HEK293 cells. The inventors predict that this work may be applicable to increasing per-cell AAV output in industrial settings, potentially reducing global costs and increasing functional vector recovery in downstream manufacturing processes.BACKGROUNDParvoviruses are small, single-stranded DNA viruses that are ubiquitously found in many animal species. AAV is a prototypic dependoparvovirus whose replication cycle requires the function of helper genes from larger co-infected viruses such as Adenoviruses or Herpesviruses. The natural genome of AAV contains ~4.7 kb of ssDNA that encodes up to ten known proteins in a highly overlapped fashion. The rep gene encodes four protein products named based on their molecular weight: Rep72 and Rep68 facilitate genomic replication, whereas Rep52, and Rep40 play essential roles in loading nascent ssDNA genomes into assembled capsids. Downstream of rep lies the cap gene, which encodes three known protein products off of overlapping reading frames: VP1, VP2, and VP3 are structural proteins that assemble to form the capsid, the assembly activating protein (AAP) targets VP proteins to the nucleus and is involved in capsid assembly. The most recently discovered AAV-encoded gene is the membrane-associated accessory protein (MAAP). MAAP is encoded by an alternative ORF in the AAV cap gene that is found in all presently reported natural serotypes. Gene delivery by recombinant AAV (rAAV) have shown significant success in both research and clinical gene therapy applications. In the rAAV system, Rep and Cap are removed from between AAV’s 5’ and 3’ inverted terminal repeats (ITRs) and provided in trans. Instead, a transgene of interest is inserted between the ITRs and subsequently packaged into the nascent AAV capsids. However, manufacturing quantities of good manufacturing practice (GMP)-grade rAAVs necessary to achieve current and projected dosing requirements–particularly in a clinical context–presents a significant hurdle to expanding rAAV-based gene therapies. Recently, evidence has emerged supporting a functional role of MAAP in AAV egress. This led to the hypothesis that MAAP could be engineered to facilitate increased levels of secreted AAV produced from HEK293 cells. 

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Researchers at the University of California, Davis have developed several blockchain paradigms that provide new approaches and expand on existing protocols to improve performance in large-scale blockchain implementations.

The inventors have developed a highly scalable multiplexed approach to increase the density of graphene nanoribbon- (GNR) based transistors. The technology forms a single device/chip (scale to 16,000 to >1,000,000 parallel transistors) on a single integrated circuit for single molecule biomolecular sensing, electrical switching, magnetic switching, and logic operations. This work relates to the synthesis and the manufacture of molecular electronic devices, more particularly sensors, switches, and complimentary metal-oxide semiconductor (CMOS) chip-based integrated circuits.Bottom-up synthesized graphene nanoribbons (GNRs) have emerged as one of the most promising materials for post-silicon integrated circuit architectures and have already demonstrated the ability to overcome many of the challenges encountered by devices based on carbon nanotubes or photolithographically patterned graphene. The new field of synthetic electronics borne out of GNRs electronic devices could enable the next generation of electronic circuits and sensors.  

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.

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.

Portable UAVs such as quad-copters have made huge inroads in the last several years in various fields of aerial photography and surveillance. Drones can efficiently and cheaply hover over/follow a target of interest and capture unique perspectives of wildlife, real-estate, sporting events and operational environments such as law enforcement or military. More challenging however is the application of UAVs for large area search and surveillance. In these scenarios, a search pattern must be established which can cover many square miles and is far too expansive for a UAVs typical battery to sustain. To make UAVs more broadly effective in large area search and target identification, new path planning algorithms are needed to efficiently eliminate areas of low probability while focusing on search areas most likely to contain the subject of interest. Likewise, improved image classifiers are needed to aid in separating targets of interest from background terrain, thus expediting the search within given battery limitations

A microfluidic platform for real time sensing of volatile airborne agents.

This technology is a new class of materials capable of thermal regulation and active camouflage. These cephalopod-inspired materials, configurable to different geometries, can be used in many sectors, ranging from consumer to industrial to military applications.

Researchers led by Dr. Potkonjak from the UCLA Department of Computer Science have developed a technique to detect hardware Trojans in integrated circuits.

Professor Jonathan Hopkins and colleagues have developed amechanical programmable metamaterial consisting of an array of actively, independently controlled micro-scale unit cells. This technology allows for the application of materials which have instantly changeable, programmable properties that can exceed those of conventional, existing materials.