Researchers from UC San Diego present a fully-passive, miniaturized, flexible form factor sensor interface titled ZenseTag that uses minimal electronics to read and communicate analog sensor data, directly at radio frequencies (RF). The technology exploits the fundamental principle of resonance, where a sensor's terminal impedance becomes most sensitive to the measured stimulus at its resonant frequency. This enables ZenseTag to read out the sensor variation using only energy harvested from wireless signals. UCSD inventors further demonstrate its implementation with a 15x10mm flexible PCB that connects sensors to a printed antenna and passive RFID ICs, enabling near real-time readout through a performant GUI-enabled software. They showcase ZenseTag's versatility by interfacing commercial force, soil moisture and photodiode sensors. 

Researchers at the University of California, Davis have developed a solid-state device that uses Cherenkov Radiation to emit light at a tunable wavelength in the THz to IR range.

Researchers at the University of California, Davis have developed two designs capable of capturing hyperspectral images that can be processed using compressive sensing techniques. These advanced component technologies for hyper-spectral imagers realizing 100x reduced size, weight, and power while supporting 1000x framerates in support of high performance.

A revolutionary approach to sensor data processing that leverages bio-inspired computing for intelligent sensing.

A groundbreaking technology that mimics the dynamic color-changing functionality of the blue-ringed octopus for applications in camouflage, signaling, and beyond.

Researchers at the University of California, Davis have developed a technology that offers a sophisticated solution for collecting and measuring gas emissions from surfaces, particularly skin, with high sensitivity and specificity.

This technology leverages an innovative mechanism of ethylene detection to introduce a portable device that allows for the rapid and continuous monitoring of the gaseous chemical using platinum nanowires.

      Goniophotometers measure the luminance distribution of light emitted or reflected from a point in space or a material sample. Increasingly there is a need for such measurements in real-time, and in real-world situations, for example, for daylight monitoring or harvesting in commercial and residential buildings, design and optimization of greenhouses, and testing laser and display components for AR/VR and autonomous vehicles, to name a few. However, current goniophotometers are ill-suited for real-time measurements; mechanical scanning goniophotometers have a large form factor and slow acquisition times. Parallel goniophotometers take faster measurements but suffer from complexity, expense, and limited angular view ranges (dioptric angular mapping systems) or strict form factor and sample positioning requirements (catadioptric angular mapping systems). Overall, current goniophotometers are therefore limited to in-lab environments.      To overcome these challenges, UC Berkeley researchers have invented an optical sensor  for parallel goniophotometry that is compact, cost-effective, and capable of real-time daylight monitoring. The novel optical design addresses key size and flexibility constraints of current state-of-the-art catadioptric angular mapping systems, while maximizing the view angle measurement at 90°. This camera-like, angular mapping device could be deployed at many points within a building to measure reflected light from fenestrations, in agricultural greenhouses or solar farms for real-time monitoring, and in any industry benefitting from real-time daylight data.

Optical atomic clocks have taken a giant leap in recent years, with several experiments reaching uncertainties at the 10−18 level. The development of synchronized clock networks and transportable clocks that operate in extreme and distant environments would allow clocks based on different atomic standards or placed in separate locations to be compared. Such networks would enable relativistic geodesy, tests of fundamental physics, dark matter searches, and more. However, the leading neutral-atom optical clocks operate on wavelengths of 698 nm (Sr) and 578 nm (Yb). Light at these wavelengths is strongly attenuated in optical fibers, posing a challenge to long-distance time transfer. Those wavelengths are also inconvenient for constructing the ultrastable lasers that are an essential component of optical clocks. To address this problem, UC Berkeley researchers have developed a new, laser-cooled neutral atom optical atomic clock that operates in the telecommunication wavelength band. The leveraged atomic transitions are narrow and exhibit much smaller black body radiation shifts than those in alkaline earth atoms, as well as small quadratic Zeeman shifts. Furthermore, the transition wavelengths are in the low-loss S, C, and L-bands of fiber-optic telecommunication standards, allowing the clocks to be integrated with robust laser technology and optical amplifiers. Additionally, the researchers have identified magic trapping wavelengths via extensive studies and have proposed approaches to overcome magnetic dipole-dipole interactions. Together, these features support the development of fiber-linked terrestrial clock networks over continental distances.

This e-nose sensor applies odorant receptor proteins fused to ion channels within a lipid bilayer, combined with semiconducting materials, to detect the binding of target molecules through changes in electrical conductance. Designed for sensitivity at the molecular level, it can identify a wide range of substances by mimicking the olfactory capabilities of living organisms.

An innovative solution for the precise detection of glyphosate, glufosinate, and AMPA in water samples.

         Recent advancements in nuclear magnetic resonance (NMR) spectroscopy have underscored the need for novel instrumentation, but current commercial instrumentation performs well primarily for pre-existing, mainstream applications. Modalities involving, in particular, integrated electron-nuclear spin control, dynamic nuclear polarization (DNP), and non-traditional NMR pulse sequences would benefit greatly from more flexible and capable hardware and software. Advances in these areas would allow many innovative NMR methodologies to reach the market in the coming years.          To address this opportunity, UC Berkeley researchers have developed a novel high-speed, high-memory NMR spectrometer and hyperpolarizer. The device is compact, rack-mountable and cost-effective compared to existing spectrometers. Furthermore, the spectrometer features robust, high-speed NMR transmit and receive functions, synthesizing and receiving signals at the Larmor frequency and up to 2.7GHz. The spectrometer features on-board, phase-sensitive detection and windowed acquisition that can be carried out over extended periods and across millions of pulses. These and additional features are tailored for integrated electron-nuclear spin control and DNP. The invented spectrometer/hyperpolarizer opens up new avenues for NMR pulse control and DNP, including closed-loop feedback control, electron decoupling, 3D spin tracking, and potential applications in quantum sensing.

      Quantum sensing is rapidly reshaping our ability to discern chemical processes with high sensitivity and spatial resolution. Many quantum sensors are based on nitrogen-vacancy (NV) centers in diamond, with nanodiamonds (NDs) providing a promising approach to chemical quantum sensing compared to single crystals for benefits in cost, deployability, and facile integration with the analyte. However, high-precision chemical quantum sensing suffers from large statistical errors from particle heterogeneity, fluorescence fluctuations related to particle orientation, and other unresolved challenges.      To overcome these obstacles, UC Berkeley researchers have developed a novel microfluidic chemical quantum sensing device capable of high-precision, background-free quantum sensing at high-throughput. The microfluidic device solves problems with heterogeneity while simultaneously ensuring close interaction with the analyte. The device further yields exceptional measurement stability, which has been demonstrated over >103s measurement and across ~105 droplets.  Greatly surpassing the stability seen in conventional quantum sensing experiments, these properties are also resistant to experimental variations and temperature shifts. Finally, the required ND sensor volumes are minuscule, costing only about $0.63 for an hour of analysis. 

         Recent mass evacuation events, including the 2018 Camp Fire and 2023 Maui Fire, have demonstrated shortcomings in our communication abilities during natural disasters and emergencies. Individuals fleeing dangerous areas were unable to obtain fast or accurate information pertaining to open evacuation routes and faced traffic gridlocks, while nearby communities were unprepared for the emergent situation and influx of persons. Climate change is increasing the frequency, areas subject to, and risk-level associated with natural hazards, making effective communication channels that can operate when mobile network-based systems and electric distribution systems are compromised crucial.         To address this need UC Berkeley researchers have developed a mobile network-free communication system that can function during natural disasters and be adapted to most communication devices (mobile phones and laptops). The self-organized, mesh-based and low-power network is embedded into common infrastructure monitoring device nodes (e.g., pre-existing WSN, LoRa, and other LPWAN devices) for effective local communication. Local communication contains dedicated Emergency Messaging and “walkie-talkie” functions, while higher level connectivity through robust gateway architecture and data transmission units allows for real-time internet access, communication with nearby communities, and even global connectivity. The system can provide GPS-free position information using trilateration, which can help identify the location of nodes monitoring important environmental conditions or allowing users to navigate.

Detection of sucralose (also known under its trade name Splenda®), particularly in food and beverages, is slow and involves the use of complex instrumentation. Current techniques involve high pressure liquid chromatography and/or mass spectrometry. Use of these techniques is not commercially viable. Producers want rapid and accurate responses - resulting in some producers determining sucralose concentration by taste alone. 

Volatile organic compounds (VOCs) are released by various products and during various processes. Ethanol is one such VOC that is released as an important byproduct of alcoholic fermentation. Ethanol emitted during fermentation can be estimated using the amount of liquid lost during storage. The instrumentation needed to accurately quantify ethanol emissions is specialized and costly. Researchers at UC Santa Cruz have developed low-cost VOC sensors that are useful for the wine industry, among others.

Researchers from UC San Diego have developed an invention that allows the continuous monitoring of atmospheric He, Ne, and H2 at unprecedented precision. This enables important new applications including in the understanding of the global carbon cycle, verifying reported natural gas emissions, and predicting earthquakes.

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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Real-time radiation monitoring is critical for public health and emergency response. High-frequency monitoring can generate large amounts of data for dozens of radioactive isotopes though. There is a growing demand for compact radiation detection devices that are also able to quickly and autonomously process these large datasets for anomalies. A UC Santa Cruz researcher has developed machine learning software that synthesizes real-time radiation monitoring data in situ to detect radioactive anomalies.

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.

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