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 brain development, providing an exceptional tool for studying the complexities of biology. Among these, cortical organoids, comprising in part of neurons, have been instrumental in providing early insights into brain formation, function, and pathology. Functional characteristics of cortical organoids, such as cellular morphology and electrophysiology, provide physiological insight into cellular states and are crucial for understanding the roles of cell types within their specific niches. And while progress has been made studying engineered neuronal systems, decoding the functional properties of neuronal networks and their role in producing behaviors depends in part on recognizing neuronal cell types, their general locations within the brain, and how they connect.

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.

A novel dielectrophoresis (DEP)-based microfluidics method for efficient and label-free sorting of plant cells, leveraging unique dielectric properties.

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. Despite their potential, organoid experiments present several challenges. Organoids require a rigorous, months-long developmental process, demanding substantial resources and meticulous care to yield valuable data on aspects of biology such as neural unit electrophysiology, cytoarchitecture, and transcriptional regulation. Traditionally the data has been difficult to collect on a more frequent and consistent basis, which limits the breadth and depth of modern organoid biology. Generating and measuring organoids depend on media manipulations, imaging, and electrophysiological measurements. Historically these are labor- and skill-intensive processes which can increase risks associated with known human error and contamination.

In PET imaging, patient motion, such as respiratory and cardiac motion, are a major source of blurring and motion artifacts. Researchers at the University of California, Davis have developed a technology designed to enhance PET imaging resolution without the need for external devices by effectively mitigating these artifacts

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.

Professor Hideaki Tsutsui and colleagues from the University of California, Riverside have developed a portable handheld device for nucleic acid extraction. With its high-speed motor, knurled lysis chamber for rapid sample lysis, and quick nucleic acid extraction using paper disks, this device can yield ready-to-use extracts in just 12 minutes, significantly reducing the time required for sample preparation. This technology is advantageous over current methods as it can be expedited without the need for cumbersome specimen collection, packaging, and submission, shortening the turnaround time.  

Brief description not available

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 large-scale, energy-efficient, high-throughput, and compact tensorized optical neural network (TONN) exploiting the tensor-train decomposition architecture on an integrated III–V-on-silicon metal–oxide–semiconductor capacitor (MOSCAP) platform.

Researchers at the University of California, Davis have developed an optical lens module that uses a metalens or a metalens array having a controllable angular field-of-view.

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.

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.

      The demand for power electronics with smaller volumes, lighter weights, and lower cost has motivated ongoing investigation into alternative power passive component technologies. Miniaturization of power converters is bottlenecked by magnetics, whose power densities fundamentally reduce at small scales. Capacitors exhibit much more favorable densities at small sizes, but efficient voltage regulation and galvanic isolation are difficult to achieve without magnetics. Therefore piezoelectric components have emerged as compelling alternative passive components for power electronics. However,  their high-performance capabilities have been limited to applications of high load impedance due to the high characteristic of piezoelectric resonators (PRs) themselves.       To overcome this challenge, UC Berkeley researchers have developed novel piezoelectric resonator (PR) designs based on overtones, with enhanced power densities and reduced optimal load impedances. The overtone PRs have been demonstrated to have comparable efficiency to fundamental-mode PRs, while their capabilities for power handling density and lower optimal load impedances are increased. Use of overtone PRs can expand the utility of piezoelectrics to a wider scope of power electronics.

As the density and performance of electronics continues to increase, thermal challenges have become a primary concern. Removing heat from electronic components can be extremely challenging, given their small size, electrical activity, and mechanical constraints. This necessitates the design of cooling solutions for a wide variety of electronic designs in applications such as datacenters, renewables, aircraft, etc. To address this problem, researchers at UC Berkeley have developed a thermal test vehicle (TTV) for characterizing the performance of electronics cooling solutions under a wide variety of operating conditions. All of the TTV circuitry required to perform measurements and temperature estimations can be included on one printed circuit board (PCB). This represents a simple, highly flexible approach for thermal test vehicle design. The overall size of the array can be scaled to any desired amount. This novel TTV represents a simple, highly flexible approach for thermal test vehicle design. Furthermore, its use of standard commercial electronic components allows for a vast reduction in cost compared to existing commercial solutions.

      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.

      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.

         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.

The disclosed methods offer a robust approach to accurately quantify skin optical properties across different skin tones, facilitating improved diagnosis, monitoring, and treatment in dermatology.

During initial stages of development, the human brain self assembles from a vast network of billions of neurons into a system capable of sophisticated cognitive behaviors. The human brain maintains these capabilities over a lifetime of homeostasis, and neuroscience helps us explore the brain’s capabilities. The pace of progress in neuroscience depends on experimental toolkits available to researchers. New tools are required to explore new forms of experiments and to achieve better statistical certainty.Significant challenges remain in modern neuroscience in terms of unifying processes at the macroscopic and microscopic scale. Recently, brain organoids, three-dimensional neural tissue structures generated from human stem cells, are being used to model neural development and connectivity. Organoids are more realistic than two-dimensional cultures, recapitulating the brain, which is inherently three-dimensional. While progress has been made studying large-scale brain patterns or behaviors, as well as understanding the brain at a cellular level, it’s still unclear how smaller neural interactions (e.g., on the order of 10,000 cells) create meaningful cognition. Furthermore, systems for interrogation, observation, and data acquisition for such in vitro cultures, in addition to streaming data online to link with these analysis infrastructures, remains a challenge.

During In the last few decades, the use of miniaturized electrochemical devices has grown rapidly and found diverse applications in scientific and consumer products. The process of developing specialized electrochemical devices is often time-consuming and expensive. Experimental setups involving electrochemistry often use specialized measurement equipment such as a potentiostat. A potentiostat is an analytical instrument that controls the voltage and current between two or more electrodes in a cell. The accuracy, precision, and flexibility of applying or measuring voltages and currents depends on the quality and design of the electronic hardware, which for commercially available potentiostats, often correlate with the device’s cost and architecture. Consequently, one of the challenges faced by today’s electrochemical research community is how to perform modern experimental designs with expensive, asynchronous, and inflexible potentiostats.

Detection of single ionizing particles at rates approaching the gigahertz (GHz) range per channel has potential for applications in medical imaging and treatment as well as particle and nuclear physics. Current ionizing particle detection systems detect with maximum frame rates of ~500 MHz. As accelerators (e.g. XFELs) are upgraded to deliver trains of pulses at faster rates, detection systems will need to keep pace. Methods and devices that can detect at GHz rates will be required to meet the demands of modern societal needs and equipment.