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. 

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.

         Positron emission tomography (PET) is a powerful tool both in biomedical research and clinical patient care, particularly in the diagnosis of cancer, search for metastases, cancer treatment monitoring, diagnosis of diffuse diseases causing dementia, or metabolic blood flow imaging. However, the poor efficiency of current PET detectors (1-2%) requires large radiotracer doses and integration times, driving both cost and patient exposure per scan. High detector capital cost also renders PET scanners prohibitively expensive. Finally, while time-of-flight PET can enhance the spatial resolution of PET by measuring temporal correlation of detected gamma photons, the modality is limited by the latency of current gamma radiation detectors (timing resolutions of ~200-500 ps). Overall, the expense and inefficiency of available gamma radiation detectors hinder the full technological capabilities of PET and its affordable use in patient care.         To address these problems, researchers at UC Berkeley have developed a new gamma radiation detector architecture with the potential for an order of magnitude improvement in both time resolution (down to 10 ps) and efficiency. The design uses novel perovskite nanomaterials and well-established nanotechnology manufacturing methods to produce a detector at a fraction of the cost of current offerings. Together, the high efficiency and timing resolution of the nanophotonic detector design should drastically improve the spatial resolution (including by time-of-flight measurements) of PET scanners and dose-suitability for elderly patients. Benefits in affordability are multiple, lowering detector cost and as well as required radiotracer dose.

Measurement of electrical activity in nervous tissue has many applications in medicine, but the implantation of a large number of sensors is traditionally very risky and costly. Devices must be large due to their necessary complexity and power requirements, driving up the risk further and discouraging adoption. To address these problems, researchers at UC Berkeley have developed devices and methods to allow small, very simple and power-efficient sensors to transmit information by backscatter feedback. That is, a much more complex and powerful external interrogator sends an electromagnetic or ultrasound signal, which is modulated by the sensor nodes and reflected back to the interrogator. Machine learning algorithms are then able to map the reflected signals to nervous activity. The asymmetric nature of this process allows most of the complexity to be offloaded to the external interrogator, which is not subject to the same constraints as implanted devices. This allows for larger networks of nodes which can generate higher resolution data at lower risks and costs than existing devices.

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.  

The inventors have constructed conjugative plasmids for intra- and inter-species delivery and expression of RNA-guided CRISPR-Cas transposases for organism- and site-specific genome editing by targeted transposon insertion. This invention enables integration of large, customizable DNA segments (encoded within a transposon) into prokaryotic genomes at specific locations and with low rates of off-target integration.

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.

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.

The inventors have developed an enzymatically catalyzed method for simple and rapid coupling of biomolecules to native amino acids on protein surfaces. This method is capable of attaching tyrosine or phenol containing molecules, peptides, or proteins to cystine or thiol containing targets at neutral pH with high yields. The inventors demonstrate the utility of this system by modifying Cas9 and other proteins with fluorophores, peptides, and whole proteins, such as green fluorescent proteins (GFPs) and antibody short chain variable fragments. This technology represents a novel paradigm in biomolecule coupling.

96 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Current methods of biomolecule delivery to mature plants are limited due to the presence of plant cell wall, and are additionally hampered by low transfection efficiency, high toxicity of the transfection material, and host range limitation. For this reason, transfection is often limited to protoplast cultures where the cell wall is removed, and not to the mature whole plant.  Unfortunately, protoplasts are not able to regenerate into fertile plants, causing these methods to have low practical applicability. Researchers at the University of California have developed a method for delivery of genetic materials into mature plant cells within a fully-developed mature plant leaf, that is species-independent. This method utilizes a nano-sized delivery vehicle for targeted and passive transport of biomolecules into mature plants of any plant species. The delivery method is inexpensive, easy, and robust, and can transfer biomolecules into all phenotypes of any plant species with high efficiency and low toxicity.

96 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Calibri; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} The ∼10% optical contrast of graphene on specialized substrates like oxide-capped silicon substrates, together with the high-throughput and noninvasive features of optical microscopy, have greatly facilitated the use and research of graphene research for the past decade.  However, substantially lower contrast is obtained on transparent substrates. Visualization of nanoscale defects in graphene, e.g., voids, cracks, wrinkles, and multilayers, formed during either growth or subsequent transfer and fabrication steps, represents yet another level of challenge for most device substrates.     UC Berkeley researchers have developed a facile, label-free optical microscopy method to directly visualize graphene on transparent inorganic and polymer substrates at 30−40% image contrast per graphene layer.  Their noninvasive approach overcomes typical challenges associated with transparent substrates, including insulating and rough surfaces, enables unambiguous identification of local graphene layer numbers and reveals nanoscale structures and defects with outstanding contrast and throughput. We thus demonstrate in situ monitoring of nanoscale defects in graphene, including the generation of nano-cracks under uniaxial strain, at up to 4× video rate.  

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. 

Recent advances in biomedicine and biotechnology are driving the demand for novel surface functionalization platforms for biologically active molecules. Polymer brush coatings form when macromolecular chains are end-tethered to surfaces at high grafting densities. While there have been notable successes integrating polymer brush coatings with proteins to control biological function, such strategies require covalent conjugation of the protein to the polymer, which can be inefficient and can compromise biological function. Moreover, these polymer brushes almost universally feature synthetic polymers, which are often heterogeneous and do not readily allow incorporation of chemical functionalities at precise sites along the constituent chains. To address these challenges, Researchers at the University of California, Berkeley (UCB) conducted experiments with polymer brushes based on nerve cell neurofilaments as the intrinsically disordered protein (IDP). By cloning a portion of a gene that encodes one of the neurofilament bristles, and re-engineering it such that they could attach the resulting protein to surfaces, UCB investigators have developed a biomimetic, recombinant IDP that can assemble into an environment-sensitive protein brush that swells and collapses dramatically with environmental changes in solution pH and ionic strength. Their research demonstrates that stimuli-responsive brushes can be efficiently integrated with proteins without compromising biological function, which could have broad commercial appeal as a new class of smart biomaterial building blocks.

A research team led by Alex Zettl has developed a variable pressure, powder/gas/liquid injection inductively coupled plasma system that is used to produce high quality boron nitride nanotubes (BNNTs) at continuous rates of 35 g/hour.  For example, in this system, boron powder is introduced to a directed flow of plasma and boron nitride nanostructures are formed in a chamber. This system can produce collapsed BN nanotubes (nanoribbons) and closed shell BN capsules (nanococoons).  The system is also adaptable to a large variety of feedstock materials.

The disclosure provides innovative synthesis methods to produce uniform, ultrathin and high-quality metal nanostructures. In certain embodiments, the synthesis methods disclosed herein are solution based, therefore affording scalability and allowing for the production of metal nanostructures (e.g. Cu-nanowires ) that can have varying diameters, e.g., between 1 nm to 70 nm. The resulting metal nanostructures can be used to construct transparent electrodes that have lower costs, better transparency, and superior flexibility in comparison to conventional metal-oxide conductors, such as indium tin oxide (ITO) .

Optical trapping systems are commercially available through several companies. In these systems, the optical trap precision relies on the passive stability of the instrument itself, and therefore demands costly engineering solutions to limit environmental noise that can be coupled into the optomechanical components. Consequently, high-resolution measurements are not possible in common biological laboratory settings that typically lack appropriate vibration isolation and temperature stability.  Researchers at the University of California, Berkeley have developed an invention that addresses a critical problem currently limiting the performance of high-resolution optical traps: that the mechanical drift of optical components often results in physical drift in the location of an optical trap that obscures the displacement-of-interest. The motion of biological motor proteins that are specific to interacting with DNA often take steps along the double helix that is on the order of 0.3 nanometers in size. Accurate measurement of displacements on this scale requires that drift of the trap positions be limited to no more than a few angstroms. However, the current best-performing optical traps suffer from instrumental drift that is almost twice what can be tolerated. Owing to the critical role of these components in all optical trapping systems, and the previously undetectable levels of mechanical drift they undergo, we sought to measure the trap drift with angstrom-level precision using a new approach. This new approach has successfully measured for and corrected for the mechanical drift of these components and demonstrated that this novel invention is capable of consistently reducing the noise floor to levels that have not previously been accomplished.       

0 0 1 96 540 UC Berkeley 10 4 632 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} The encapsulation of stem cells in a hydrogel substrate provides a promising future in biomedical applications. However, communications between hydrogels and stem cells is complicated, for example, factors such as porosity, different polymer types, stiffness, compatibility and degradation will lead to stem cell survival or death. Hydrogels mimic the three-dimensional extracellular matrix to provide a friendly environment for stem cells.   UC Berkeley researchers have developed hydrogel cell matrices for the support, growth, and differentiation of a stem cell or progenitor cell and methods for making such hydrogel cell matrices.

  Microfluidic constructs have proven to have many important applications. Small sample sizes can be sufficient to give a large number of laboratory results, for instance, in "lab-on-a-chip" technologies, such as those developed by Caliper. Testing and processing previously available only in specialized laboratories under highly controlled conditions with expert technicians are now available for field work using these new technologies. However, these highly minimized fluid managing devices are typically very expensive, and so are of limited availability to many potential applications. Researchers at the University of California, Berkeley achieve patterned Agarose micro-structures using photolithography and oxygen plasma. The resulting Agarose micro-structures can be then rehydrated back into the original form, if the proper conditions are maintained during processing.   Related to B09-061 and B09-058 

Nanowires are drawing tremendous interest due to their unique properties like high surface to volume ratio and dimensionality. Advances in nanowire assembly techniques have enabled devices based on nanowires to be realized. Doping of silicon nanowires is required for the fabrication of electronic devices incorporating semiconducting nanowires. One problem with doping involves accurate alignment and positioning of the appropriately doped regions of the nanowires to build functional devices using currently known assembly techniques can be extremely cumbersome. Ion-implantation allows precise control of the amount of introduced dopants and the location of suitably doped portions of nanowires.  However, ion implantation can damage the crystalline lattice of nanowires, which may require a high temperature annealing step to repair, and such high temperature processing can further damage the substrates, such as plastic substrates. To address these problems, researchers at UC Berkeley have developed methods for enabling the processing of nanowires on temperature sensitive substrates, without the damage to the nanowires and substrates that can result using conventional processing techniques.

The most widely used methods for synthesizing semiconductor nanocrystals are "bottom-up", batch-style approaches. While these methods produce high quality products, they have several drawbacks that limit their efficacy including: (1) The volume of reactants is limited resulting in exorbitant time requirements to produce substantial quantities, and severe limitations on the experimental conditions used to optimize the process. (2) The particle growth kinetics are not always reproducible resulting in the need for post-production processing to achieve the size distributions required for most applications. (3) The local conditions in the bulk solution can't be accurately measured resulting in the inability to comprehensively understand the underlying kinetics. These drawbacks have led to the investigation of continuous flow reactor methods to produce semiconductor nanocrystals. Studies have shown that this approach can produce nanocrystals with quality comparable to batch methods and also precisely control parameters such as temperature, flow, and concentrations -- leading to nanocrystals with tunable sizes. Despite these advantages, there has not been an attempt to investigate the thermodynamics, kinetics, or commercial scale-up of continuous flow approaches. To address these opportunities, researchers at UC Berkeley have developed a new continuos flow approach and reactor design for producing nanocrystals. These innovations represent a major advancement in the field in that they enable the probing of the underlying process occurring during nanocrystal synthesis, as well as the establishment of conditions capable for manufacturing a variety of particle sizes and morphologies.

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The capability to pattern closely spaced gold or other nanoparticles has significant potential in nano- electronics and photonics applications such as electrically conducting wires, and as plasmon wave guides. To address this opportunity, researchers at UC Berkeley have developed an innovative method for fabricating nanoscale patterned surfaces with nanoparticles and nanowires. Using this approach, the researchers were able to fabricate lines of closely spaced 10 nm gold nanoparticles that are a single nanoparticle in width. Furthermore, standard plating techniques can be used to transform an assembly of these nanoparticles into nanowires or other continuous patterned features. In comparison to existing methods for depositing arbitrary patterns of nanoparticles such as e-beam lithography, dip-pen nanolithography and several other atomic force microscopy-based methods, this new Berkeley method is simple and direct.

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