Cellulose, the major component of plant biomass, is considered the most abundant biopolymer. Certain microorganisms are able to convert the monomer of cellulose, glucose, into various products useful in the production of biofuels and other methods. Cellulose is highly stable, has a high storage potential, low cost, and plentiful supply. Based on these and other properties, cellulose and enzymes capable of degrading and hydrolyzing it are useful in the sequestration, storage, and production of bioenergy.  Crystalline cellulose is composed of linear polymers of β1-4 linked glucose, held in a tightly crosslinked crystalline lattice by a high degree of intermolecular hydrogen bonding. This structure confers stability but also hinders efficient deconstruction of cellulose. Strategies for commercial depolymerization of cellulose typically combine pretreatment to disrupt the crystalline structure, followed by enzymatic hydrolysis. Disruption of the crystalline structure and chemical hydrolysis typically requires high temperatures and low pH. Enzymatic hydrolysis generally occurs under milder conditions. The degree of pretreatment required and the expense of subsequent cleanup steps are affected by properties of the enzymes used. Bacteria capable of degrading cellulose include those belonging to the genera Aquifex, Rhodothermus, Thermobifida, Anaerocellum, and Caldicellulosiruptor. A recombinant thermostable endoglucanase of Aquifex aeolicus produced in E. coli showed maximal activity at 80° C. and pH 7.0 with a half-life of 2 h at 100° C.  UC Berkeley investigators have engineered a polypeptide having cellulase activity for hydrolysis and degradation of cellulose-containing biomass.

There are many applications in which there is the need for storage of matter prone to biological contamination for extended period, from days to years. These applications include food, agricultural products, biological matter, and biotechnological matter.  Isobaric (constant pressure) freezing is one method of food preservation, however, freezing causes the deterioration of the quality of the preserved matter. High pressure processing followed by sterilization by refrigerating it at 4 ºC is common, but microorganisms can grow at 4 ºC and the product is sterile for limited periods of time of days. Thus, there is still a need for good preservation technologies that inhibits or reduce growth of microbial contaminants while maintaining their fresh-like characteristics and nutritional value.  UC Berkeley inventors and others have developed a device and methods for long term preservation of matter that inhibits or eliminates biological contaminants with isochoric freezing. 

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.  

Plastics are essential for the modern world but are also non-sustainable products of the petrochemical industry that negatively impact our health, environment, and food chain. Natural biogenic plastics, such as polyhydroxyalkanoates (PHA), are readily biodegradable, can be produced more sustainably, and offer an attractive alternative. The global demand for bioplastics is increasing with the 2019 market value of $8.3B expected to reach a compound annual growth rate of 16.1% from 2020-2027 (https://www.grandviewresearch.com/industry-analysis/bioplastics-industry). However, current PHA production is constrained by the underlying physiology of the microorganisms which produce them, meaning bioplastic production is currently limited to inefficient, batch fermentation processes that are difficult to scale.To address this problem, UC Berkeley researchers have developed a new system for PHA production wherein the PHA are generated continuously throughout microorganism growth lifecycles. The invention allows these sustainable bioplastics to be produced via precision continuous fermentation technology, a scalable and efficient approach.

For decades, researchers have been developing “cool roof” materials to cool buildings and save on energy usage from air conditioning. Cool roof materials are engineered to maximize infrared thermal emission, allowing heat to be effectively radiated into outer space and the building to cool down. Conventional cool roof materials emit heat even when it is cold outside, which exacerbates space heating costs and can outweigh energy-saving benefits. A temperature adaptive radiative coating (TARC) material was developed in 2021 that adapts its thermal emittance to ambient temperatures using metal-insulator transitions in vanadium oxide. TARC is projected to outperform existing roof materials in most climate areas, but the complicated structure required high-cost fabrication techniques such as photolithography, pulsed laser deposition, and XeF2 etching, which are not scalable.To address this problem, UC Berkeley researchers have developed a new scalable temperature-adaptive radiative coating (STARC). STARC has the same thermal emittance switching capability as TARC, allowing the thermal emittance to be switched between high- and low- emittance states at a preset temperature. However, STARC can be produced using high-throughput, roll-to-roll methods and low-cost materials. The STARC material also has an improved lifetime. As an added benefit, while cool roof materials are often engineered with uniformly low solar-absorption, the color and solar absorption of STARC can be tuned for aesthetic purposes or to meet local climate-specific needs.

 This invention is a method includes mixing a polymer with one or more dehydrogenating reagent(s), thereby forming the dehydrogenated polymer.  Such a dehydrogenated polymer can then be made into a alkene or a dehydrogenating polymer.

In this technology, the inventors introduce additives to purposely change the morphology of polycaprolactone (PCL) by increasing the bending and twisting of crystalline lamellae. These morphological changes immobilize chain-ends preferentially at the crystalline/amorphous interfaces and limit chain-end accessibility by the embedded processive enzyme. This chain end redistribution reduces the polymer-to-monomer conversion from >95% to less than 50%, causing formation of highly crystalline plastic pieces including microplastics. By synergizing both random chain scission and processive depolymerization, it is feasible to navigate morphological changes in polymer/additive blends and to achieve near complete depolymerization. The random scission enzymes in the amorphous domains create new chain ends that are subsequently bound and depolymerized by processive enzymes. Present studies further highlight the importance to consider host polymer morphological effects on the reactions catalyzed by embedded catalytic species.This is part of a patent family in compostable plastics.  

The inventors have developed ion-selective potentiometric sensors for monitoring soil analytes with naturally degradable substrate, conductor, electrode, and encapsulant materials that minimize pollution and ecotoxicity. This novel sensor-creation method uses printing technologies for the measurement of nitrate, ammonium, sodium, calcium, potassium, phosphate, nitrite, and others. Monitoring soil analytes is key to precision agriculture and optimizing the health and growth of plant life. 

In developed countries, buildings demand a large percentage of a region's energy-generating requirements. This has led to an urgent need for efficient buildings with reduced energy requirements. In office buildings, lighting takes up 20% to 45% of the total energy consumption. Furthermore, the adoption of smart lighting control strategies such as daylight harvesting is shown to reduce lighting energy use by 30% to 50%.For most closed-loop lighting control systems, the real-time data of the daylight level at areas of interest (e.g., the office workbench) are the most important inputs. Current state-of-the-art solutions use dense arrays of luxmeters (photosensors) to monitor the daylight environment inside buildings. The luxmeters are placed on either workbenches, or ceilings and walls near working areas. Digital cameras are used in controlled laboratory environments and occasionally in common buildings to evaluate glare resulting from excessive daylight. The disadvantage of these sensor-based approaches is that they're expensive to install and commission. Additionally, the sample area of these sensors is limited to either the area of the luxmeters or the view of the cameras. Consequently, many sensors are needed to measure the daylight in a large office space.To address this situation, researchers at UC Berkeley developed a portable cyber-physical system for real time, daylight evaluation in buildings, agriculture facilities, and solar farms (collectively referred to as "structures").

 This invention is a wave powered desalination system and, in particular , a wave powered desalination systems with a low speed, high pressure rotary pump.

The inventor has developed novel algorithms and metrology methodologies, including real-time in-situ imaging of part formation, in computed axial lithography printing (CALP). CALP is a form of continuous 3D roll-based additive manufacturing which is distinct from roll-based micro/nanomanufacturing methods such as imprint lithography, gravure printing, and photo-roll lithography because it enables production of high aspect ratio reentrant features and voids in a single step that are difficult or even impossible with the existing methods.

The power demands on data centers are large and increasing rapidly. This is straining data center economic and environment impacts, and in turn driving improvements in data center power efficiencies. Data centers have been widely adopting 48 V intermediate bus architectures due to higher efficiency, good flexibility, and reduced cost. However, a major challenge in such systems is the conversion from the 48 V bus to the extreme low voltage and high current operating levels of server CPUs and GPUs.To address this challenge, UC Berkeley researchers developed a multi-phase hybrid power converter architecture. The Berkeley design uses hybrid converter topologies. A switched-capacitor network is smartly merged with a switched-inductor network, resulting in circuit component number reduction and soft-charging operation of the capacitors. Furthermore, the Berkeley architecture integrates a multi-phase control technique to achieve a higher conversion ratio of the switched-capacitor network, which can further improve the overall system efficiency without increasing the circuit size.  

Imaging the material property distribution of solids has a broad range of applications in materials science, biomechanical engineering, and clinical diagnosis. For example, as various diseases progress, the elasticity of human cells, tissues, and organs can change significantly. If these changes in elasticity can be measured accurately over time, early detection and diagnosis of different disease states can be achieved. Elasticity imaging is an emerging method to qualitatively image the elasticity distribution of an inhomogeneous body. A long-standing goal of this imaging is to provide alternative methods of clinical palpation (e.g. manual breast examination) for reliable tumor diagnosis. The displacement distribution of a body under externally applied forces (or displacements) can be acquired by a variety of imaging techniques such as ultrasound, magnetic resonance, and digital image correlation. A strain distribution, determined by the gradient of a displacement distribution, can be computed (or approximated) from measured displacements. If the strain and stress distributions of a body are both known, the elasticity distribution can be computed using the constitutive elasticity equations. However, there is currently no technique that can measure the stress distribution of a body in vivo. Therefore, in elastography, the stress distribution of a body is commonly assumed to be uniform and a measured strain distribution can be interpreted as a relative elasticity distribution. This approach has the advantage of being easy to implement. The uniform stress assumption in this approach, however, is inaccurate for an inhomogeneous body. The stress field of a body can be distorted significantly near a hole, inclusion, or wherever the elasticity varies. Though strain-based elastography has been deployed on many commercial ultrasound diagnostic-imaging devices, the elasticity distribution predicted based on this method is prone to inaccuracies.To address these inaccuracies, researchers at UC Berkeley have developed a de novo imaging method to learn the elasticity of solids from measured strains. Our approach involves using deep neural networks supervised by the theory of elasticity and does not require labeled data for the training process. Results show that the Berkeley method can learn the hidden elasticity of solids accurately and is robust when it comes to noisy and missing measurements.

Producing meat products using cells grown in culture (instead of via animal husbandry farming) has many benefits and great potential. Current cell-cultured approaches either: (1) use suspension culture to produce homogenous products that don't meet consumer taste expectations for a substitute meat, or (2) organ culture methods to create products that meet consumer taste expectations, but at unacceptably high prices. To address this situation, researchers at UC Berkeley have been developing a process by which cells are grown in free suspension, making possible the economies of scaling that result from using large stirred tanks. After growth, the cells can be assembled into desirable macroscopic structures by controlling the conditions under which the desired multiple cell types and scaffolds are mixed and dewatered. The macroscopic structures include features such as fat marbling and muscle fiber orientation as expected by meat consumers.

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.

The inventors have developed an iron electrocoagulation (Fe-EC) system for arsenic removal. The system offers a highly effective, low cost, robust method for removing arsenic from groundwater used for drinking, at community scale (10,000 liters per day).The main advance of this invention is to replace the assembly of inter-digited flat steel plates with an assembly of spiral-wound or folded and inter-digited two steel sheets separated only with perforated insulating spacers. This substantially reduces the energy consumption in comparison to other Fe-EC reactors, and allows for larger flow rates for a given reactor size than the standard inter-digited flat plate configuration. This advance is possible because the system relies on: externally added (ppm quantities) of oxidizer (H2O2), and a newly-discovered effect that allows consistent iron dissolution at high current densities. High current density also produces copious quantities of micro-bubbles of H2 gas, which flushes the space between the electrodes continuously during operation, preventing the clogging that has defeated earlier attempts.In a typical Fe-EC reactor, parallel inter-digited plates of mild steel are inserted into the contaminated water and a small DC voltage is applied between alternate plates to promote anodic dissolution of F(0) metal to release Fe(II) ions into the contaminated water. The Fe(II) ions react with dissolved oxygen in the water to produce Fe(III) that is used to capture the contaminants. Typically, an assembly of flat inter-digited parallel steel plates, with nearest neighbor spaced 2 cm to 5 cm, is used in Fe-EC reactors. Occasionally, externally added or in-situ produced oxidants may be used (e.g. externally added strong oxidants such as H2O2, O3, Chlorine, Permanganate, etc., or in-situ produced strong oxidants such as H2O2 using carbon based cathodes). 

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.

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. 

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.

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.