Researchers at the University of California, Davis have developed a sophisticated soil nitrate sensing system designed to accurately measure soil pore water nitrate concentrations, enhancing sustainable agriculture and environmental monitoring.

      Single-particle/single-molecule tracking (SPT) is a key tool for quantifying molecular motion in cells and in vitro. Wide-field SPT, in particular, can yield super-resolution mapping of physicochemical parameters and molecular interactions at the nanoscale, especially when integrated with single-molecule localization microscopy techniques like photoactivation and fluorophore exchange. However, wide-field SPT is often limited to the slow (<10 μm2/s) diffusion of molecules bound to membranes, chromosomes, or the small volume of bacteria, in part due to the ~10 ms framerate of common single-molecule cameras like electron-multiplying charge-coupled devices (EM-CCDs); for unbound diffusion in the mammalian cell and in solution, a molecule readily diffuses out of the <1 μm focal range of high-numerical-aperture objective lenses within 10 ms. While recent advances such as ultra-highspeed intensified CMOS cameras, feedback control by locking onto a molecule, trapping, and tandem excitation pulse schemes address the framerate issue, each also introduces drawbacks in light/signal efficiency, speed, uninterrupted diffusion paths, and/or trajectory resolution, e.g., number of time points.      UC Berkeley researchers have overcome these myriad challenges by introducing spatially-encoded dynamics tracking (SpeedyTrack), a strategy to enable direct microsecond wide-field single-molecule tracking/imaging on common microscopy setups. Wide-field tracking is achieved for freely diffusing molecules at down to 50 microsecond temporal resolutions for >30 timepoints, permitting trajectory analysis to quantify diffusion coefficients up to 1,000 um2/s. Concurrent acquisition of single-molecule diffusion trajectories and Forster resonance energy transfer (FRET) time traces further elucidates conformational dynamics and binding states for diffusing molecules. Moreover, spatial and temporal information is deconvolved to map long, fast single-molecule trajectories at the super-resolution level, thus resolving the diffusion mode of a fluorescent protein in live cells with nanoscale resolution. Already substantially outperforming existing approaches, SpeedyTrack stands out further for its simplicity—directly working off the built-in functionalities of EM-CCDs without the need to modify existing optics or electronics.

       Spectral machine vision collects both the spectral and spatial dependence (x,y,λ) of incident light, containing potentially useful information such as chemical composition or micro/nanoscale structure.  However, analyzing the dense 3D hypercubes of information produced by hyperspectral and multispectral imaging causes a data bottleneck and demands tradeoffs in spatial/spectral information, frame rate, and power efficiency. Furthermore, real-time applications like precision agriculture, rescue operations, and battlefields have shifting, unpredictable environments that are challenging for spectroscopy. A spectral imaging detector that can analyze raw data and learn tasks in-situ, rather than sending data out for post-processing, would overcome challenges. No intelligent device that can automatically learn complex spectral recognition tasks has been realized.       UC Berkeley researchers have met this opportunity by developing a novel photodetector capable of learning to perform machine learning analysis and provide ultimate answers in the readout photocurrent. The photodetector automatically learns from example objects to identify new samples. Devices have been experimentally built in both visible and mid-infrared (MIR) bands to perform intelligent tasks from semiconductor wafer metrology to chemometrics. Further calculations indicate 1,000x lower power consumption and 100x higher speed than existing solutions when implemented for hyperspectral imaging analysis, defining a new intelligent photodetection paradigm with intriguing possibilities.

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      Current clinical practice for detecting low-concentration molecular biomarkers requires sending samples to centralized labs, leading to high costs and delays. Successful point-of-care (POC) diagnostic technology exist, such as the paper-based lateral-flow assay (LFA) used for pregnancy tests and SARS-CoV-2 rapid antigen tests, or miniaturized instruments such as the Abbot i-Stat Alinity. However, the former provides binary results or limited quantitative accuracy, and the latter is too expensive for in-home deployment. A promising approach for POC diagnostics, offering tailored circuit optimization, multiplexed detection, and significant cost and size reductions, is millimeter-sized CMOS integrated circuits coupled with microfluidics. Recent demonstrations include protein, DNA/RNA, and cell detection. The current complexity of system packaging (e.g., wire/flip-chip bonding) makes integrating microfluidics with more sophisticated functions challenging, and often-required syringe pumps and tubing are operationally unfriendly, limiting current approaches.       UC Berkeley researchers have developed a fully integrated, multi-mode POC device that requires single-step assembly and operates autonomously. Drawing inspiration from RFID technology and implantables, they have introduced inductively-coupled wireless powering and communication functionality into a CMOS bio-analyzer. With the chip being fully wireless, the die can be easily integrated into a substrate carrier, achieving a completely flat surface that allows for seamless bonding with the microfluidic module. In the final product, the device will be sealed in a pouch inside a vacuum desiccator. The user tears the pouch, adds a drop of sample, and the system automatically begins operation. The operation window can last up to 40 minutes, making the process insensitive to time delays. The present CMOS bio-analyzer integrates pH-sensing and amperometric readout circuits for both proton-based and redox-based immunoassays.

      Integrating microelectronics with microfluidics, especially those implemented in silicon-based CMOS technology, has driven the next generation of in vitro diagnostics. CMOS/microfluidics platforms offer (1) close interfaces between electronics and biological samples, and (2) tight integration of readout circuits with multi-channel microfluidics, both of which are crucial factors in achieving enhanced sensitivity and detection throughput. Conventionally bulky benchtop instruments are now being transformed into millimeter-sized form factors at low cost, making the deployment for Point-of-Care (PoC) applications feasible. However, conventional CMOS/microfluidics integration suffers from significant misalignment between the microfluidics and the sensing transducers on the chip, especially when the transducer sizes are reduced or the microfluidic channel width shrinks, due to limitations of current fabrication methods.       UC Berkeley researchers have developed a novel methodology for fabricating microfluidics platforms closely embedded within a silicon chip implemented in CMOS technology. The process utilizes a one-step approach to create fluidic channels directly within the CMOS technology and avoids the previously cited misalignment. Three types of structures are presented in a TSMC 180-nm CMOS chip: (1) passive microfluidics in the form of a micro-mixer and a 1:64 splitter, (2) fluidic channels with embedded ion-sensitive field-effect transistors (ISFETs) and Hall sensors, and (3) integrated on-chip impedance-sensing readout circuits including voltage drivers and a fully differential transimpedance amplifier (TIA). Sensors and transistors are functional pre- and post-etching with minimal changes in performance. Tight integration of fluidics and electronics is achieved, paving the way for future small-size, high-throughput lab-on-chip (LOC) devices.

In magnetic resonance imaging (MRI) scanners, the detection of nuclear magnetic resonance (NMR) signals is achieved using radiofrequency, or RF, coils. RF coils are often equivalently called “resonance coils” due to their circuitry being engineered for resonance at a single frequency being received, for low-noise voltage gain and performance. However, such coils are therefore limited to a small bandwidth around the center frequency, restricting MRI systems from imaging more than one type of nucleus at a time (typically just hydrogen-1, or H1), at one magnetic field strength.To overcome the inherent restriction without sacrificing performance, UC Berkeley researchers have developed an MRI coil that can perform low-noise voltage gain at arbitrary relevant frequencies. These frequencies can be programmably chosen and can include magnetic resonance signals from any of various nuclei (e.g., 1H, 13C, 23Na, 31P, etc.), at any magnetic field strength (e.g., 50 mT, 1.5T, 3T, etc.). The multi-frequency resonance can be performed in a single system. The invention has further advantages in terms of resilience due to its decoupled response relative to other coils and system elements.

Traditionally, land can be used for either crop growth or energy production. This technology optimizes the efficiency of land use by combining both. Researchers at the University of California, Davis have developed solar cell designs that absorb only specific solar photons (> 2.2 eV) to create electricity, while letting through beneficial light (< 2.2 eV) for efficient crop growth.

Researchers at the University of California, Davis have developed an operant behavioral assay to study thermosensation, pain, or avoidance and tolerance of an animal to noxious environments.

Researchers from UC San Diego have created a system to enable animal model research by reducing the physical impact of weight introduced by body worn or implanted instrumentation. It does so by dynamically counterbalancing the force introduced by the additional mass of the instrumentation. Together the dynamic counterbalance system, dynamic adjustment arm, and dynamic pulley provide a low cost system that addresses several of the pressing weight constraints of chronic small animal experiments. Together they will enable researchers to conduct experiments that would not have been possible due to weight restrictions of existing recording instruments.

In 2019, the Food and Agriculture Organization of the United Nations estimated that between 20 to 40 percent of global crop production are lost to plant diseases and pests annually, with plant diseases costing the global economy roughly $220B each year. Disease-warning systems are currently being used by growers to preemptively mitigate destructive events using chemical treatment or biological management. Meteorological factors including rainfall, humidity, and air temperature are all considered in these systems, but the measurement of leaf wetness duration (LWD) is important to its governing role in infection processes for many fungal pathogens. The longer a leaf stays wet, the higher the risk that disease will develop, because many plant pathogen propagules require several hours of continuous moisture to germinate and initiate infection The current gold standard to measuring LWD is using the capacitive leaf wetness sensor (LWS). The LWS functions by measuring a change in the capacitance seen at its surface which then yields an output signal that changes according to its surface wetness. Commercial leaf wetness sensors estimate the amount of surface water and leaf wetness duration by measuring the change in capacitance of a surface that accumulates condensed water. However, the one-size-fits-all commercial sensors do not accurately reflect the variation in leaf traits (particular shape, texture, and hydrophobicity) these traits strongly affect surface wettability (hydrophilicity) and vary widely among plant species.

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Brief description not available

Brief description not available

Understanding of biophysical processes in marine mammals, like elephant seals, is limited by our ability to monitor wild behavior. Elephant seals spend the majority of their life at sea, reaching depths of over 1500 m that challenge even the most recent advances in biometric monitoring devices. Many existing devices for monitoring electrophysical signals in seals are also invasive and require skin or skull perforation for electrode implantation. A UC Santa Cruz researcher has designed a water-resistant, non-invasive device that can withstand pressures of 3000 psi and is capable of monitoring over twenty electrophysiological signals in wild elephant seals.

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. 

Researchers at the University of California, Davis have developed a controller that applies environmental data to optimizing operations of livestock cooling equipment.

UCLA researchers in the Department of Electrical and Computer Engineering have developed a highly sensitive, wearable hormone monitoring platform.

Drosophila spp., also known as fruit flies, are widely used in genetic research. Drosophila lines (e.g. flies with a particular mutation) can only be stored as live animals – they cannot be frozen and remain viable. So to maintain the stocks, the live flies are manually transferred from an old vial to a new vial on a regular basis (every 1-2 weeks). Some Drosophila labs maintain hundreds or even thousands of individual lines and so maintenance of these lines can be very time consuming. A UC Santa Cruz Drosophila researcher has developed a simpler and more efficient method of transferring the flies that requires significantly less hands-on work.

Prof. Will Grover and his colleague at the University of California have developed a method to identify adulterated drugs and foods by observing how they behave when disturbed by temperature changes or other causes. Images of the sample’s behavior as it freezes over time are captured and processed into chronoprints.  Chronoprints are fundamentally bitmap images of samples on a computer, and it is possible to leverage existing image analysis and comparison techniques that have been already developed to analyze Chronoprints. Fig. 1 Producing a "chronological fingerprint" or chronoprint capturing how six samples (in this example, authentic and adulterated samples of an over-the-counter liquid cold medicine) respond to a perturbation over space and time (in this case, a rapidly changing temperature gradient). (A) A microfluidic thermometer chip containing the samples is partially immersed in liquid nitrogen to establish a rapidly changing temperature gradient along the chip. (B) The chip contains six samples (red) loaded in microfluidic channels that run parallel to the dynamic temperature gradient. (C) An inexpensive USB microscope records a video of the physical changes in the samples as they react to the dynamic temperature gradient.  Fig. 2 By reducing each channel image to a single column of pixels, and then placing these columns side-by-side, we create a bitmap image (the sample’s chronoprint) that captures how the sample changes over space (the y-axis) and time (the x-axis). Finally, by comparing the chronoprints of all six samples in the chip, we can determine whether the samples are either likely the same or definitely different.  

Researchers at UCI have developed a compact device for the rapid desalination of water which is driven entirely by renewable solar energy.

The invention consists of a multi-channel, droplet-generating microfluidic device with a strategically placed feature.The feature vibrates in order to counteract particle-trapping micro-vortices formed within the device.Counteracting these vortices allows for single particle encapsulation in the droplets formed by the device and thereby makes this technology a good candidate for use in single cell diagnostics and drug delivery systems.

Many applications, ranging from in vivo cell culture growth to drug delivery, rely on microcapsules to encapsulate and protect cells or molecules until their desired release. These microcapsules are typically generated in immiscible fluid, which must be depleted before they can be effectively used. Researchers at UCI have recently developed a paper-based microcapsule extraction technique that is quicker, cheaper, and less damaging than conventional methods.

Soft-tissue injuries and organ transplantation are common in modern combat scenarios. Organs and tissues harvested for transplantation need to be preserved during transport, which can be very difficult. Micro and nanobubbles (MNBs) offer a new technology that could supply oxygenation to such tissues prior to transplantation, thus affording better recovery and survival of patients. Described here is a novel device capable of producing MNB solutions that can be used to preserve viability and function of such organs/tissue. Additionally, these solutions may be used with negative pressure wound therapy to heal soft-tissue wounds.

Researchers at the University of California, Davis have developed a robotic system can apply signaling to the crops and detect any important needs for the plant.