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.

A novel fusion construct that fuses Cas9 to a truncated version of human PRDM9 with the purpose of improving precise genome editing via homologous direceted repair (HDR). PRDM9 is a protein that deposits histone marks H3K4me3 and H3K36me3 simultaneously during meiosis to mark recombination hot spots where crossover occurs and is resolved by homologous recombination. H3K36me3 has also been demonstrated to be required upstream of homologous recombination repair after double stranded breaks (DSBs) and during V(D)J recombination for adaptive immunity. Recent evidence suggests PRDM9 acts as a pioneer factor opening closed chromatin. The newly engineered PRDM9C-Cas9 fusion construct shows increased HDR and decreased non-homologous end joining mediated insertions and deletions (indels).

UC Berkeley researchers have discovered a novel family of proteins denoted Cas12L within the Type V CRISPR Cas superfamily distantly related to CasX, CasY and other published type V sequences.  These Cas12L proteins utilize a guide RNA to perform RNA-directed cleavage of DNA.

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.

Mutated versions of Cas12a that remove its non-specific ssDNA cleavage activity without affecting site-specific double-stranded DNA cutting activity. These mutant proteins, in which a short amino acid sequence is deleted or changed, provide improved genome editing tools that will avoid potential off-target editing due to random ssDNA nicking.

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.

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.

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.   

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;} Endocrine disrupting compounds are found in increasing amounts in our environment, originating from pesticides, plasticizers, and pharmaceuticals, among other sources. These compounds have been implicated in diseases such as obesity, diabetes, and cancer. The list of chemicals that disrupt normal hormone function is growing at an alarming rate, making it crucially important to find sources of contamination and identify new compounds that display this ability. However, there is currently no broad-spectrum, rapid test for these compounds, as they are difficult to monitor because of their high potency and chemical dissimilarity.   To address this, UC Berkeley researchers have developed a new detection system and method for the sensitive detection of trace compounds using electrochemical methods.  This platform is both fast and portable, and it requires no specialized skills to perform. This system enables both the detection of many detrimental compounds and signal amplification from impedance measurements due to the binding of bacteria to a modified electrode. The researchers were able to test the system finding sub-ppb levels of estradiol and ppm levels of bisphenol A in complex solutions. This approach should be broadly applicable to the detection of chemically diverse classes of compounds that bind to a single receptor.  

There are an estimated 130 million wooden poles that support overhead power lines in the US.  Extreme weather, aging, storms or sabotage can all lead to potential damage of these poles and power lines, which can leave large areas without basic necessities.  Due to this risk, it’s anticipated that power utility companies will deploy sensors and corresponding energy harvesters to better respond to potential damage of this critical electricity grid infrastructure. To address this anticipated mass deployment of sensors and harvesters, researchers at UC Berkeley have developed technology improvements to harvesting of electrical energy from energized conductors carrying alternating currents, such as those on overhead and underground power lines (as well as power-supplying conductors in offices and dwellings).  These enhanced harvesters would improve the economics of deploying sensors across a national power grid.  The Berkeley harvesters can readily provide enough power to supply wireless communication devices, energy storage batteries and capacitors, as well as sensors such as accelerometers, particulate matter measuring devices, and atmospheric sensors.

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.

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. 

Conventional chemical sensor discriminates different analytes by rejecting the interference using selective decorations on the sensor body. A cross-reactive chemical sensor array discriminates different analytes by interpreting the collective sensor response using signal processing technique, and solves for the interference. Commercial sensor manufacturers search for the optimal choice of material, identifier and the signal processing technique to maximize the sensor performance in terms of chemical detection and discrimination. To address the need, researchers at the University of California, Berkeley, have developed a platform with 2D material incorporated in a cross-reactive field effect transistor (FET) sensor array. By examining and manipulating the properties of the sensor array, researchers have invented a low power, high efficiency, and versatile chemical sensing technology that is promising for commercialization.

Piezoelectric Micromachined Ultrasonic Transducers (pMUTs) have attracted industry attention for their good acoustic matching, large bandwidth, miniaturization, and low cost-by-batch fabrication. pMUTs have the advantages of low power consumption and large deflection for high-acoustic power applications. However, low electromechanical coupling has been a serious drawback for pMUT applications, in some cases foreclosing key opportunities. In response to this challenge, researchers at UC Berkeley have developed a bimorph pMUT with unique advantages which dramatically improve the device capabilities: the bimorph pMUT utilizing two active AlN layers in a CMOS-compatible process. This innovative design is the first bimorph pMUT with two active piezoelectric layers separated by a common electrode. The prototype bimorph pMUT has a resonant frequency of 198.8 kHz and central displacement of 407.4 nm/V. Under the differential drive scheme using the dual electrodes at low frequency, the measured central displacement is 13.0 nm/V, which is about 400% higher than that of a unimorph AlN pMUT. This revolutionary dual electrode bimorph pMUT presents a new class of design/fabrication for exciting pMUT applications, including range finders and gesture recognition devices.

Curved pMUTs, as developed at UC Berkeley, have been shown to have 2 orders of magnitude improvement over flat pMUTs as well as the capacity for post-processing tuning. However, it is desirable to improve production methods to make this innovation more commercially applicable.To meet this challenge, investigators at Berkeley have developed a self-curved diaphragm process using stress engineering to produce highly responsive curved pMUTs. This diaphragm pMUT can boost 6X better performance compared to the flat diaphragm state-of-the-art pMUT. CMOS foundry-based process flow has produced self-curved diaphragms by engineering residual stress in thin films to construct molds for fabrication. Benefits of the invention include achieving silicon curved molds by patterning thin layers of stressed silicon nitride and silicon oxide layers on top of a silicon plate of a predetermined thickness.

Conventional metal-oxide semiconductor field-effect transistor (MOSFET) technology consists of a source, drain, gate, and substrate. The chemical field-effect transistor (chemFET) is a type of a field-effect transistor acting as a chemical sensor, and is similar to MOSFET except for the gate structures. Modern industrial players seek higher-sensitivity technologies which are small, durable, efficient, and versatile. Further advances in these materials and structures could enable many new kinds of layered semiconductors and devices. To address need, researchers at the University of California, Berkeley, have developed chemical-sensitive field-effect transistor (CS-FET) platform technology. By exploiting selective thin films incorporated into the CS-FET, researchers have created chemical sensors with commercial promise in terms of chemical-versatility and low-power. 

The increasing role of wireless technology is driving the need for reducing power consumption of wireless devices. The high-Q SAW and FBAR vibrating mechanical devices used for current RF band-pass filters are responsible for significant power savings. Still, there is room for improvement. To address this situation, researchers at UC Berkeley have developed an active resonator system with tunable quality factor, frequency, and impedance. Coupling two or more of these Berkeley resonators together enables construction of filters with arbitrarily small adjustable bandwidths and tunable insertion loss thereby achieving significant advantage over traditional filters constructed from passive resonators.

Berkeley researchers have created an electric fan with visual detection camera and movement recognition software to identify the presence and location of occupants. Occupant tracking algorithm localizes air movements to individualize comfort and conserve energy. The fan can be integrated in ceilings, wall partitions or office furniture.

Ammonia is used in many industrial and commercial applications, for example in the manufacture of fertilizers and cleaners.  However, ammonia is toxic at high concentrations and, therefore, safe storage and transportation of ammonia is required. In addition, trace amounts of ammonia in the atmosphere contaminate and interfere with certain industrial processes, such as semiconductor fabrication, which requires ultra-pure air. Proper ammonia management includes the adsorption of the gas under each of these pressure regimes: high-pressure adsorption for safe storage and transportation and low-pressure adsorption for the removal of trace contaminants from the ambient air. Current methods of adsorption include simple salts, such as MgCl2, but these are not efficient for low-pressure adsorption and furthermore their ammonia cycle is inefficient, requiring significant heat exchange and large changes in volume. Investigators at UC Berkeley have developed a novel polymer for ammonia adsorption that uses acidic materials placed in a spatial arrangement that allows for cooperative adsorption. This not only increases the efficiency of adsorption but also is effective at both high-pressure and low-pressure ammonia adsorption, resulting in multiple applications of the technology. 

In recent years, gas sensors for industrial applications have experienced great advances through rapid evolution of microelectromechanical systems (MEMS). As a result of increased government legislative pressure on industrial health and safety, commercial customers are demanding integrated smart sensor technology and systems which leverage MEMS for small footprint, low cost, and high-performance features. Market researchers suggest double-digit compound annual growth rates for MEMS sensors through 2018, with the fastest growth is expected in the semiconductor sensor base. Traditional infrared gas analyzers determine the absorption of an emitted infrared light source through a certain air sample. Nondispersive infrared technology (NDIR) detects certain gas by detecting the absorption of infrared wavelengths that is characteristic of that gas. NDIR detectors are the industry standard method of measuring the concentration of carbon oxides. Researchers at UC Berkeley and Davis have successfully demonstrated pyroelectric infrared detectors that exhibit high sensitivity and reliable performance for advanced gas analyses. The MEMS technology is well suited for constant monitoring in harsh environments where long term stability is important, such as petroleum, medical, and industrial monitoring settings.