Radiation detectors are typically instrumented with low noise preamplifiers that generate voltage pulses in response to energy deposits from particles (x-rays, gamma-rays, neutrons, protons, muons, etc.). This preamplifier signal must be further processed in order to improve the signal to noise ratio, and then subsequently estimate various properties of the pulse such as the pulse amplitude, timing, and shape. Historically, this “pulse processing” was carried out with complex, purpose-built analog electronics. With the advent of digital computing and fast analog to digital converters, this type of processing can be carried out in the digital domain.There are a number of commercial products that perform “hardware” digital pulse processing. The common element among these offerings is that the pulse processing algorithms are implemented in hardware (typically an FPGA or high performance DSP chip). However this hardware approach is expensive, and it's hard to tailor for a specific detector and application.To address these issues, researchers at UC Berkeley developed a solution that performs the pulse processing in software on a general purpose computer, using digital signal processing techniques. The only required hardware is a general purpose, high speed analog to digital converter that's capable of streaming the digitized detector preamplifier signal into computer memory without gaps. The Berkeley approach is agnostic to the hardware, and is implemented in such a way as to accommodate various hardware front-ends. For example, a Berkeley implementation uses the PicoScope 3000 and 5000 series USB3 oscilloscopes as the hardware front-end. That setup has been used to process the signal from a number of semiconductor and scintillator detectors, with results that are comparable to analog and hardware digital pulse processors.In comparison to current hardware solutions, this new software solution is much less expensive, and much more easily configurable. More specifically, the properties of the digital pulse shaping filter, trigger criteria, methods for estimating the pulse parameters, and formatting/filtering of the output data can be adjusted and tuned by writing simple C/C++ code.

This invention leverages the nuclease activity of CRISPR proteins for the direct, sensitive detection of specific nucleic acid sequences. This all-in-one detection modality includes an internal Nuclease Chain Reaction (NCR), which possesses an amplifying, feed-forward loop to generate an exponential signal upon detection of a target nucleic acid.Cas13 or Cas12 enzymes can be programmed with a guide RNA that recognizes a desired target sequence, activating a non-specific RNase or DNase activity. This can be used to release a detectable label. On its own, this approach is inherently limited in sensitivity and current methods require an amplification of genetic material before CRISPR-base detection. 

Robotic comfort systems have been developed which use fans to deliver heated/cooling air to building occupants to provide greater levels of personal comfort.  However, current robotic systems rely on surveys asking individuals about their comfort state through a web interface or app.  This reliance on user feedback becomes impractical due to survey fatigue on the part of the user.  Researchers at the University of California, Berkeley have developed a system which uses a visible light camera located on the nozzle of a robotic fan to detect human facial features (e.g., eyes, nose, and lips).  Images from a co-located thermal camera are then registered onto the visible light image and temperatures of different facial features are captured and used to infer the comfort state of the individual.  Accordingly, the fan/heater system blows air with a specific velocity and temperature toward the occupant via a closed-loop feedback control.  Since the system can track a person in an environment, it addresses issues with prior data collection systems that needed occupants to be positioned in a specific location.

Solutions of shear-thinning polymers are known to decrease in viscosity as a shear force is applied to the solution. In this work, the inventors show that by pre-shearing a shear-thinning polymer solution mixed with a precursor solution of a semiconducting crystal we can tune the size and morphology of the growing crystals, which governs the optoelectronic properties of the formed crystals. By pre-shearing the solution we are able to lower the viscosity of the solution, which plays a key role in the liquid phase processing (eg., coating processes). By forming a thinner, low-viscosity coating, we are able to tune the nucleation and growth rate of the crystals to form crystals that are smaller and more uniformly distributed in size, leading to a uniform and conformal coating. This approach allows us to coat a uniform layer of semiconducting crystals, which is necessary for developing functional optoelectronic devices.

Native mass spectrometry (MS), in which electrospray ionization (ESI) is used to transfer large macromolecules and macromolecular complexes directly from solution into the gas phase, is a powerful tool in structural biology.  However, charge-state distributions of individual components in mixtures of macromolecular complexes or synthetic polymers are often unresolved making it impossible to obtain mass information directly from an ESI mass spectrum. Other conventional methods can provide accurate masses of individual ions, but often at the expense of analysis time.     Weighing ions individually with charge detection mass spectrometry (CDMS) has the advantage that fast measurements are possible depending on the accuracy and sensitivity required. However, a limitation of trapping CDMS technology is the need to weigh single ions individually in order to eliminate potential interferences between the signals of multiple ions or ion-ion interactions that can potentially interfere with these measurements. UC researchers have created multiplex charge detection mass spectroscopy, particularly for high throughput single ion analysis of large molecules and measuring the masses of large molecules, macromolecular complexes and synthetic polymers that are too large or heterogeneous for conventional mass spectrometry measurements.  The new multiplexing method makes it possible to measure the masses of many ions simultaneously.  

A programmable LED device that illuminates multiple spatial locations (termed wells) with user-defined light patterns whose intensity can be modulated as a function of space and time. The devices are used for optogenetic stimulation of tissue culture plates (24-well and 96-well) kept in a heated and humidified tissue culture incubator, as well as photopatterning of hydrogels. In brief, light from LEDs passes through optical elements that ensure uniform illumination of each well. Parameters of the optical system, such as LED configuration, optical diffuser elements, materials, and geometry, were modeled and optimized using the optical ray tracing software Zemax OpticStudio. An electronics subsystem allows programmed control of illumination intensity and temporal sequences, with independent control of each well. Spatial precision is conveyed through a photomask attached to the culture plate. The hardware design also includes a cooling system and vibration isolation to reduce heating and damage to the sample. Lastly, a graphical user interface (GUI) was used to wirelessly program the illumination intensity and temporal sequences for each well. The devices can thus illuminate 24 independent channels with visible, NIR, or UV light with intensity ranges of 0 to 20-100 microwatts per millimeter-squared with 16-bit intensity resolution, and a temporal resolution of 1 millisecond and spatial resolution of 100 microns. In summary, the device allows uniform illumination of multiple wells for multiplexed photoactivation or photopolymerization of various substrates (light-responsive bacterial or mammalian cells grown in tissue culture, hydrogels, dyes, etc) with user-defined patterns. The device can be combined with a robotic handler, microscope, spectrometer, etc, to enable high-throughput illumination and simultaneous recording of the sample.

The sensitivity of mobile atom interferometers for gravimetry, gradiometry and inertial sensing has been limited by a noise floor due to ground vibrations, as well as available free-fall space.    UC Berkeley researchers have developed an interferometer geometry that addresses both problems within an optical cavity. The utility of such a device lies primarily in its application as a mobile sensor, particularly for situations in the absence of a GPS signal (such as in deep-sea submarines, or in the event of a GPS system failure).  Similarly, sensing using gravitational signals has wide applicability. The configuration of this device accumulates an acceleration phase sensitive to low-frequency accelerations (i.e., gravity) while demonstrating an immunity to accelerations at higher frequencies than the held times (i.e., vibrations).

The real-time position and mobility of a user is key to providing personalized location-based services (LBSs) – such as navigation. With the pervasiveness of GPS-enabled mobile devices (MDs), LBSs in outdoor environments is common and effective. However, providing equivalent quality of LBSs using GPS in indoor environments can be problematic. The ubiquity of both WiFi in indoor environments and WiFi-enabled MDs, makes WiFi a promising alternative to GPS for indoor LBSs. The most promising approach to establishing a WiFi-based indoor positioning system requires the construction of a high quality radio map for an indoor environment. However, the conventional approach for making the radio map is labor intensive, time-consuming, and vulnerable to temporal and environmental dynamics. To address this situation, researchers at UC Berkeley developed an approach for automatic, fine-grained radio map construction and adaptation. The Berkeley technology works both (a) in free space – where people and robots can move freely (e.g. corridors and open office space); and (b) in constrained space – which is blocked or not readily accessible. In addition to its use with WiFi signals, this technology could also be used with other RF signals – for example, in densely populated and built-up urban areas where it can be suboptimal to only rely on GPS.

Capacitive-gap transduced micromechanical resonators routinely post Q several times higher than piezoelectric counterparts, making them the preferred platform for HF and low-VHF (e.g. 60-MHz) timing oscillators, as well as very narrowband (e.g. channel-select) low-loss filters. However, the small electromechanical coupling (as gauged by the resonator's motion-to-static capacitance ratio, Cx/Co) of these resonators at higher frequency prevents sub-mW GSM reference oscillators and complicates the realization of wider bandwidth filters. To address this situation, researchers at UC Berkeley developed a capacitive-gap transduced radial mode disk resonator with reduced mass and stiffness. This novel Berkeley disk resonator has a measured electromechanical coupling strength (Cx/Co) of 0.56% at 123 MHz without electrode-to-resonator gap scaling. This is an electromechanical coupling strength improvement of more than 5x compared with a conventional radial contour-mode disk at the same frequency. This increase should help improve the passbands of channel-select filters targeted for low power wireless transceivers and lower the power of MEMS-based oscillators.  

With the emergence of the Internet of Things in smart homes and buildings, determining the identity and mobility of people are key to realizing personalized, context-aware and location-based services - such as adjusting lights and temperature as well as setting preferences of electronic devices in the vicinity. Conventional electronic user identification approaches either require proactive cooperation by users or deployment of dedicated infrastructure. Consequently, existing approaches are intrusive, inconvenient, or expensive to ubiquitously implement. For example: biometric identification requires specific hardware and physical interaction; and vision-based (video) approaches need favorable lighting and introduce privacy issues. To address this situation, researchers at UC Berkeley developed an identification system that uses existing, pervasive WiFi infrastructure and users' WiFi-enabled devices. The innovative Berkeley technology cleverly leverages attributes such as the MAC address and RSS of users' WiFi-enabled devices. Furthermore, the Berkeley approach is facilitated by an unsupervised learning scheme that maps each user identification with associated WiFi-enabled devices. This technology could serve as a vital underpinning for practical personalized context-aware and location-based services in the era of the Internet of Things.

UC Berkeley and Keck Institute researchers have reported the development and testing of a graphene-based field-effect transistor that uses CRISPR technology to enable the digital detection of a target sequence within intact genomic material. Termed CRISPR–Chip, the biosensor uses the gene-targeting capacity of catalytically deactivated Cas9 complexed with a specific single-guide RNA and immobilized on the transistor to yield a label-free nucleic-acid-testing device whose output signal can be measured with a simple handheld reader.  

In our electronically connected society, human identification systems are critical to secure authentication, and also enabling for tailored services to individuals. Conventional human identification systems, such as biometric-based or vision-based approaches, require either the deployment of dedicated infrastructure, or the active cooperation of users to carry devices. Consequently, pervasive implementation of conventional human identification systems is expensive, inconvenient, or intrusive to privacy. Recently, WiFi infrastructure, and associated WiFi-enabled mobile and IoT devices have become ubiquitous, and correspondingly, have enabled many context-aware and location-based services. To address the challenges of human identification systems and take advantage of the popularity of WiFi, researchers at UC Berkeley developed a human identification system based on analyzing signals from existing WiFi-enabled devices. This novel device-free approach uses WiFi signal analysis to reveal the unique, fine-grained gait patterns of individuals as the "fingerprint" for human identification.

A flexible reflectance oximeter array (ROA) composed of printed organic light-emitting diodes (OLEDs) and organic photodiodes (OPDs), which senses reflected light from tissue to determine the oxygen saturation. Since reflected light is used as the signal, the sensor array can be used beyond the conventional sensing locations. We implemented the ROA to measure SpO2 on the forehead with 1.1% mean error and to create two-dimensional (2D) oxygenation maps of the adult forearm under pressure cuff-induced ischemia. Due to the mechanical flexibility, 2D oxygenation mapping capability, and the ability to place the sensor in diverse places, the ROA is promising for novel medical sensing applications such as mapping oxygenation in tissues, wounds, or transplanted organs.

Water is a scarce resource in some part of the United States, and recent droughts in the Midwest and the South have elevated the issue of water scarcity to a national level. Existing water sources will face increasing strain due to population growth and climate change, and financial and regulatory barriers will prevent the development of new sources. One method to alleviate water scarcity is storm water capture. Storm water can be used for non-potable applications such as irrigation, laundry, and toilet flushing to significantly reduce domestic municipal water consumption. However, in arid regions of the US, rain comes in short, intense storms only a few months out of the year, and the duration and intensity of these storms require large storage tank volumes for storm water capture to be financially feasible.    One solution is to integrate storm water capture with greywater capture. Greywater is a reliable source of water for domestic reuse, and includes water from washbasins, laundry, and showers (kitchen sinks and water for toilet flushing are considered blackwater). Combining greywater-storm water in the same collection system allows for a much smaller storage tank. A UC Berkeley researcher, along with other researchers, have developed aforecast-integrated automated control system for combined greywater-storm water storage and reuse. A simple and reliable approach for managing greywater and storm water collection at a household or community level is provided, allowing for the near-continuous monitoring and adjustment of water quantity and quality in a combined greywater-storm water storage tank based on monitored feedback/output from individual, tank-specific sensors and/or sensors located elsewhere in the water collection system.   

Methods for the simultaneous printing via doctor blading of at least two different colored emissive layers for organic light emitting diodes (OLEDs) on a single substrate.

Flexible electrostatic actuators are well designed for a range of commercial applications, from small micro-mechanical robotics to large vector displays or sound wall systems. Electrostatic actuation provides efficient, low-power, fast-response driving and control of movable nano-, micro-, and macro-structures. While commercially available electrostatic actuators have the requisite high levels of mechanical energy / force for some applications, their energy requirements are typically orders of magnitude higher than what is needed in large-area, low-power applications. Moreover, conventional approaches to these types of electrostatic actuators have limited design geometries and are prone to reliability issues like electrical shorts. To address these problems, researchers at the University of California, Berkeley, have experimented with planar electrostatic actuators using novel printing and electrode patterning and engineering techniques. The team has demonstrated a repulsive-force electrostatic actuator device (100 mm x 60 mm achieved) with extremely high field strength and high voltage operation and without insulator coatings or air breakdown.

0 0 1 183 1047 UC Berkeley 8 2 1228 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:11.0pt; font-family:"Times New Roman";} Hyper-accumulation of copper in biological fluids and tissues is a hallmark of pathologies such as Wilson’s and Menkes diseases, various neurodegenerative diseases, and toxic environmental exposure. Diseases characterized by copper hyper accumulation are currently challenging to identify due to costly diagnostic tools that involve extensive technical workup.   To solve these problems, UC Berkeley researches developed a simple yet highly selective and sensitive diagnostic tool along with new materials that can enable monitoring of copper levels in biological fluid samples without complex and expensive instrumentation.  The diagnostic tool includes a robust three-dimensional porous aromatic framework (PAF) densely functionalized with thioether groups for selective capture and concentration of copper from biofluids as well as aqueous samples.  The PAF exhibits high selectivity for copper over other biologically relevant metals, with a saturation capacity reaching over 600 mg/g.  The researchers were able to use the diagnostic tool, which included a colorimetric indicator, to identify aberrant elevations of copper in urine samples from mice with Wilson’s disease and also traced exogenously added copper in serum. 

Realizing the potential of massive sensor networks requires overcoming cost and power challenges. When sleep/wake strategies can adequately limit a network node's sensor and wireless power consumption, then the power limitation comes down to the real-time clock (RTC) that synchronizes sleep/wake cycles. With typical RTC battery consumption on the order of 1µW, a low-cost printed battery with perhaps 1J of energy would last about 11 days. However, if a clock could bleed only 10nW from this battery, then it would last 3 years. To attain such a clock, researchers at UC Berkeley developed a mechanical circuit that harnesses squegging to convert received RF energy (at -58dBm) into a local clock while consuming less than 17.5nW of local battery power. The Berkeley design dispenses with the conventional closed-loop positive feedback approach to realize an RCT (along with its associated power consumption) and removes the need for a sustaining amplifier altogether. 

Piezoelectric Micromachined Ultrasonic Transducers (pMUTs) have attracted industry attention for their good acoustic matching, small geometry, low cost-by-batch fabrication, and compatibilities with CMOS and consumer electronics. While planar pMUTs have reasonable performance over bulk piezoelectric transducers, certain deficits remain in terms of coupling and acoustic pressure outputs, DC displacements, bandwidth, and power consumption. To address these deficiencies, researchers at the University of California, Berkeley, have developed a next generation of shaped pMUTs which are no longer fully defined by resonance frequency and can accommodate larger pressure outputs and bandwidths. This new pMUT apparatus can significantly boost overall performance while dramatically reducing power as compared to flat diaphragm state-of-the-art pMUTs.

Airborne particulates (such as vehicle exhaust, dust, and metallics) are a health hazard.  Monitors for measuring particulate matter (PM) concentrations in air are typically designed for stationary industrial use; and while they are quite sensitive, they are also bulky, heavy, and expensive.  Accordingly, there is a need for PM concentration monitors that are inexpensive and portable so that they can be more pervasive, and also used by mass-market consumers. Recently, various types of portable PM monitors have been developed.  One class of monitor uses optical technology to measure particulates flowing through (not deposited on) the device.  This optical technology is not sensitive to extremely small particles (with diameters of 200 nanometers or less), yet these small particles are a serious health hazard.  Another class of PM monitor uses various technologies to measure the mass of particles deposited on (not flowing through) the device.  This type of monitor can be quite sensitive, but eventually, it can become overloaded with deposited particles.  Moreover, multiple layers of particles can eliminate the possibility of determining the chemical nature of the particles. To address these shortcomings, researchers at UC Berkeley have developed a means of periodically cleaning deposited particles from mass-sensing components of deposit-based PM sensors.  The Berkeley technology results in PM sensors that are not only portable and low-cost, but also have long-lasting functionality.

The use of electric fields for signaling and manipulation is widespread, mediating systems spanning the action potentials of neuron and cardiac cells to battery technologies and lab-on-a-chip devices. Current FET- and dye-based techniques to detect electric field effects are systematically difficult to scale, costly, or perturbative. Researchers at the University of California Berkeley have developed an optical detection platform, based on the unique optoelectronic properties of two-dimensional materials that permits high-resolution imaging of electric fields, voltage, acidity, strain and bioelectric action potentials across a wide field-of-view.

Wireless sensors and the Internet of Things (IoT) have the potential to greatly impact society. Millimeter-scale wireless microsystems are the foundation of this vision. Accordingly, to realize this potential, these microsystems must be extremely low-cost and energy autonomous. Integrating wireless sensing systems on a single silicon chip with zero external components is a key advancement toward achieving those cost and energy requirements.  Almost all commercial microsystems today use off-chip quartz technology for precise timing and frequency reference. The quartz crystal (XTAL) is a bulky off-chip component that puts a size limitation on miniaturization and adds to the cost of the microsystem. Alternatively, MEMS technology is showing promising results for replacing the XTAL in space-constrained applications. However, the MEMS approach still requires an off-chip frequency reference and the resulting packaging adds to the cost of the microsystem.  To achieve a single-chip solution, researchers at UC Berkeley developed: (1) an approach to calibrating the frequency of an on-chip inaccurate relaxation oscillator such that it can be used as an accurate frequency reference for low-power, crystal-free wireless communications; and (2) a novel ultra-low power radio architecture that leverages the inaccurate on-chip oscillator, operates on energy harvesting, and meets the 1% packet error rate specification of the IEEE 802.15.4 standard. 

Earthquakes are unpredictable disasters. Earthquake early warning (EEW) systems have the potential to mitigate this unpredictability by providing seconds to minutes of warning. This warning could enable people to move to safe zones, and machinery (such as mass transit trains) to be slowed or shutdown. The several EEW systems operating around the world use conventional seismic and geodetic network infrastructure – that only exist in a few nations. However, the proliferation of smartphones – which contain accelerometers that could potentially detect earthquakes – offers an opportunity to create EEW systems without the need to build expensive infrastructure. To take advantage of this smartphone opportunity, researchers at the University of California, Berkeley have developed a technology to allow earthquake alerts to be issued based on detecting earthquakes underway using the sensors in smartphones. Called MyShake, this EEW system has been shown to record magnitude 5 earthquakes at distances of 10 km or less. MyShake incorporates an on-phone detection capability to distinguish earthquakes from every-day shakes. The UC Berkeley technology also collects earthquake data at a central site where a network detection algorithm confirms that an earthquake is underway as well as estimates the location and magnitude in real-time. This information can then be used to issue an alert of forthcoming ground shaking. Additionally, the seismic waveforms recorded by MyShake could be used to deliver rapid microseism maps, study impacts on buildings, and possibly image shallow earth structure and earthquake rupture kinematics.

Trillions of sensors are envisioned to achieve the potential benefits of the internet of things.  Realizing this potential requires wireless sensors with low power requirements such that there might never be a need to replace a sensor’s power supply (e.g. battery) over the lifetime of that device.  The battery lifetime of wireless communications devices is often governed by power consumption used for transmitting, and therefore transmit power amplifiers used in these devises are important to their commercial success.  The efficiencies of these power amplifiers are set by the capabilities of the semiconductor transistor devices that drive them.  To achieve improved efficiencies, researchers at UC Berkeley have developed a novel method and structure for realizing a zero-quiescent power trigger sensor and transceiver based on a micromechanical resonant switch.  This sensor/transceiver is unique in its use of a resonant switch (“resoswitch”) to receive an input, amplify it, and finally deliver power to a load.  This novel technology also greatly improves short-range communication applications, like Bluetooth.  For example, with this technology, interference between Bluetooth devices would be eliminated.  Also, Miracast would work, despite the presence of interfering Bluetooth signals.

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.