This technology enhances indoor pedestrian localization accuracy using LTE signals by mitigating multipath errors through synthetic aperture navigation.

An innovative approach to indoor localization using LTE signals and IMU data, enhancing accuracy and reliability for navigation.

This technology offers a novel approach to navigation by using LTE signals, providing a viable alternative to traditional GPS systems.

Researchers at the University of California, Davis have developed a sustainable alternative to Portland cement by utilizing alkali-activated binders (AAB) with biomass ash, significantly reducing greenhouse gas emissions.

This technology enables precise, selective manipulation of magnetically barcoded materials, distinguishing them from background magnetic materials

Introducing a groundbreaking orthogonal redox cofactor, NMN+, to revolutionize redox reaction control in biomanufacturing.

Advances in biological research have been greatly influenced by the development of organoids, a specialized form of 3D cell culture. Created from pluripotent stem cells, organoids are effective in vitro models in replicating the structure and progression of organ development, providing an exceptional tool for studying the complexities of biology. Among these, cerebral cortex organoids (hereafter "organoid") have become particularly instrumental in providing valuable insights into brain formation, function, and pathology. Modern methods of interfacing with organoids involve any combination of encoding information, decoding information, or perturbing the underlying dynamics through various timescales of plasticity. Our knowledge of biological learning rules has not yet translated to reliable methods for consistently training neural tissue in goal-directed ways. In vivo training methods commonly exploit principles of reinforcement learning and Hebbian learning to modify biological networks. However, in vitro training has not seen comparable success, and often cannot utilize the underlying, multi-regional circuits enabling dopaminergic learning. Successfully harnessing in vitro learning methods and systems could uniquely reveal fundamental mesoscale processing and learning principles. This may have profound implications, from developing targeted stimulation protocols for therapeutic interventions to creating energy-efficient bio-electronic systems.

Researchers at the University of California, Davis have developed a technology that introduces a class of organic compounds capable of releasing clean energy upon cooling to cryogenic temperatures.

       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.

This invention introduces a unique rotor design for lift enhancement and wingtip vortex elimination without the need for additional power.

This technology offers a novel mechanical arrangement for lossless, adjustable operation of springs or inerters.

This technology encompasses a suite of patents for developing gyroscopes that offer both broad bandwidth and high sensitivity, suitable for a variety of challenging environments.

A novel manufacturing process that shapes complex components from nanostructured materials using a combination of pressure, heat, and electricity.

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 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.

      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.

An innovative approach to joining materials that enhances strength and toughness at interfaces, inspired by natural structures.

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.

      While robots have proven effective in enhancing the precision and time efficiency of MRI-guided interventions across various medical applications, safety remains a formidable challenge for robots operating within MRI environments. As the robots assume full control of medical procedures, the reliability of their operation becomes paramount. Precise control over robot forces is particularly crucial to ensure safe interaction within the MRI environment. Furthermore, the confined space in the MRI bore complicates the safe operation of human-robot interaction, presenting challenges to maneuverability. However, there exists a notable scarcity of force-controlled robot actuators specifically tailored for MRI applications.       To overcome these challenges, UC Berkeley researchers have developed a novel MRI-compatible rotary series elastic actuator module utilizing velocity-sourced ultrasonic motors for force-controlled robots operating within MRI scanners. Unlike previous MRI-compatible SEA designs, the module incorporates a transmission force sensing series elastic actuator structure, while remaining compact in size. The actuator is cylindrical in shape with a length shorter than its diameter and integrates seamlessly with a disk-shaped motor. A precision torque controller enhances the robustness of the invention’s torque control even in the presence of varying external impedance; the torque control performance has been experimentally validated in both 3 Tesla MRI and non-MRI environments, achieving a settling time of 0.1 seconds and a steady-state error within 2% of its maximum output torque. It exhibits consistent performance across low and high external impedance scenarios, compared to conventional controllers for velocity-sourced SEAs that struggle with steady-state performance under low external impedance conditions.