Researchers at the University of California, Davis have developed a technology that introduces a highly adaptable, lightweight robotic end effector designed for complex manipulation tasks in automation.

Researchers at the University of California, Davis have developed a reversed feedback amplifier design for enhanced mm-wave signal amplification.

Researchers at the University of California, Davis have developed a technology that introduces an alternative topology for Fibonacci switched-capacitor converters that significantly reduces switch losses and improves efficiency.

Researchers at the University of California, Davis have developed method for separating quasi-periodic mixed-signals using a single data trace, enhancing wearable sensor applications.

Researchers at the University of California, Davis have developed a technology that introduces new electrolyte compositions that significantly enhance the stability and efficiency of non-aqueous flow batteries.

       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.

      Microwave impedance microscopy (MIM) is an emerging scanning probe technique that enables non-contact, nanoscale measurement of local complex permittivity. By integrating an ultrasensitive, phase-resolved microwave sensor with a near-field probe, MIM has made significant contributions to diverse fundamental and applied fields. These include strongly correlated and topological materials, two-dimensional and biological systems, as well as semiconductor, acoustic, and MEMS devices. Concurrently, notable progress has been made in refining the MIM technique itself and broadening its capabilities. However, existing literature has focused exclusively on linear MIM based on homodyne architectures, where reflected or transmitted microwave is demodulated and detected at the incident frequency. As such, linear MIM lacks the ability to probe local electrical nonlinearity, which is widely present, for example, in dielectrics, semiconductors, and superconductors. Elucidating such nonlinearity with nanoscale spatial resolution would provide critical insights into semiconductor processing and diagnostics as well as fundamental phenomena like local symmetry breaking and phase separation.       To address this shortcoming, UC Berkeley researchers have introduced a novel methodology and apparatus for performing multi-harmonic MIM to locally probe electrical nonlinearities at the nanoscale. The technique achieves unprecedented spatial and spectral resolution in characterizing complex materials. It encompasses both hardware configurations enabling multi-harmonic data acquisition and the theoretical and calibration protocols to transform raw signals into accurate measures of intrinsic nonlinear permittivity and conductivity. The advance extends existing linear MIM into the nonlinear domain, providing a powerful, versatile, and minimally invasive tool for semiconductor diagnostics, materials research, and device development.

Researchers at the University of California, Davis have developed an innovative technology that incorporates advanced microchannel architecture into scalable solar thermal receiver unit cells, enabling highly efficient solar energy conversion.

      Poorly designed healthcare environments can increase patient stress and delay recovery, particularly in pediatric settings (see, e.g., Devlin & Andrade 2017; Park et al. 2018; Jafarifiroozabadi et al. 2023). Traditional methods for gathering architectural design feedback, such as interviews, surveys, and focus groups, rely heavily on subjective user input, and often fail to capture the voices of children by relying on parent proxies. Physical mock-ups, a common alternative to traditional methods, provide a full-scale model of a room or space, often constructed from materials like cardboard or foam. While these mock-ups allow for some degree of spatial exploration, they are time-intensive, and limited in their ability to replicate real-world conditions; high-fidelity mock-ups which incorporate more realistic materials and finishes add expense and limit flexibility for testing multiple design iterations.       To overcome these challenges UC Berkeley researchers have developed an innovative participatory design methodology that leverages advanced virtual reality (VR), eye-tracking, and physiological/emotional biofeedback technologies to evaluate the design of pediatric healthcare environments. This comprehensive system is further enhanced by custom-developed workflows for creating dynamic, interactive room simulations that are randomized to ensure rigorous, unbiased data collection. The methodology is uniquely capable of gathering objective, quantifiable data on how pediatric patients and their families respond physiologically and emotionally to specific environmental design features.

Researchers at the University of California Davis have developed a system designed to predict and prevent ATV rollovers, enhancing rider safety.

Researchers at the University of California Davis have developed a technology that enables the provable editing of DNNs (deep neural networks) to meet specified safety criteria without altering their architecture.

      The demand for miniaturized power electronics with increased efficiency and performance motivates the exploration of piezoelectric structures as alternative passive components; piezoelectric components store energy in mechanical compliance and inertia with extremely high quality factors and energy densities significantly greater than those of magnetics at small scales. Recent magnetic-less dc-dc converter designs based on single-port piezoelectric resonators (PRs) have demonstrated power stage efficiencies of 99% and PR power handling densities of up to 5.7 kW/cm3. While marking tremendous milestones, such performance has only been achieved in non-isolated dc-dc converters with mild (2:1) voltage conversion ratios, confining the utility of piezoelectric-based power conversion to a narrow subset of applications.       Piezoelectrics may be expanded to a broader set of applications through use of multi-port piezoelectric transformers (PTs), which offer the same advantages as PRs but with the added potential for galvanic isolation and inherent voltage transformation. The present invention overcomes standing performance shortcomings in isolated magnetic-less PT-based dc-dc converters, providing a framework for high-efficiency piezoelectric transformer (PT) designs (wherein isolated PTs serve as the primary passive components in isolated dc-dc converters). One of the proposed PT designs is validated in a dc-dc power converter prototype and demonstrates a peak efficiency of 97.5%. The measured performance represents a 17x reduction in loss ratio compared to previous isolated magnetic-less PT-based dc-dc converter designs, and expands the value of piezoelectrics to applications requiring isolation.

Researchers at the University of California, Davis have developed a technology that introduces a novel approach to hardware security using photonic physically unclonable functions for true random number generation and biometric ID.

Researchers at the University of California, Davis have developed a photothermal patterning flow cell that enables precise and efficient patterning of polymer films, compatible with existing cleanroom photolithography equipment.

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Researchers at the University of California, Davis have developed an artificial intelligence machine that uses a combination of electronic neuromorphic circuits and photonic neuromorphic circuits.

Researchers at the University of California, Davis have developed a haptic interface designed to aid visually impaired individuals in navigating their environment using their portable electronic devices.

Researchers at the University of California, Davis have developed a Doppler radar front end to overcome detection nulls without quadrature demodulation.

      Biologics are antibodies produced by genetically engineered cells and are widely used in therapeutic applications. Examples include pembrolizumab (Keytruda) and atezolizumab (Tecentriq), both employed in cancer immunotherapy as checkpoint inhibitors to restore T- cell immune responses against tumor cells. These biologics are produced by engineered cells in bioreactors in a process that is highly sensitive to the bioreactor environment, making it essential to integrate process analytical technologies (PAT) for closed-loop, real-time adjustments. Recent trends have focused on leveraging integrated circuit (IC) solutions for system miniaturization and enhanced functionality, for example enabling a single IC that monitors O2, pH, oxidation-reduction potential (ORP), temperature, and glucose levels. However, no current technology can directly and continuously quantify the concentration and quality of the produced biologics in real-time within the bioreactor. Such critical measurements still rely on off-line methods such as immunoassays and mass spectrometry, which are time-consuming and not suitable for real- time process control.       UC Berkeley researchers have developed a microsystem for real-time, in-vivo monitoring of antibody therapeutics using structure-switching aptamers by employing an integrator-based readout front-end. This approach effectively addresses the challenge of a 100× reduction in signal levels compared to the measurement of small-molecule drugs in prior works. The microsystem is also uniquely suited to the emerging paradigm of “living pharmacies.” In living pharmacies, drug-producing cells will be hosted on implantable devices, and real-time monitoring of drug production/diffusion rates based on an individual’s pharmokinetics will be crucial.

      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.

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.

Researchers at the University of California, Davis have developed an approach to generating mechanical power from the earth's ambient thermal radiation using a Stirling engine.

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.

High flux (e.g., greater than 1012 n/s/cm2) neutrons with energies between 8 and 30 MeV are needed for a number of applications including radioisotope production. However, none of the existing neutron sources available can fulfill these requirements. Neutron flux intensities from typical neutron sources using Deuterium-Tritium (DT) fusion are typically more than 2 orders of magnitude lower in intensity than what is needed for making production practical. Deuterium-Deuterium (DD) fusion sources provide a spectrum which is too low in energy to perform the nuclear reactions needed for isotope production. High-energy proton accelerator-driven spallation sources produce isotopes with significant co-production of unwanted radioisotopes, due to a neutron spectrum which is far higher in energy than required. While accelerator-driven neutron sources using deuteron breakup have been shown to be a viable pathway for producing a range of isotopes including actinium-225 1, a limited number of machines capable of producing ~30 MeV deuteron beams exist commercially. To address this problem, researchers at UC Berkeley have developed systems and methods for producing radionuclides using accelerator-driven fast neutron sources, and more specifically for producing actinium-225, an inherently-safe, fast neutron source based on low energy proton accelerators used throughout the world to support positron emission tomography.