An innovative, nature-inspired system that efficiently captures, transports, and stores fluids while providing passive cooling through controlled fluid dynamics.

Brief description not available

A novel thermopile technology using holey silicon enables highly sensitive broadband thermal detection across the entire electromagnetic spectrum.

A novel navigation framework utilizing low Earth orbit (LEO) satellite signals to provide accurate positioning where traditional Global Navigation Satellite System (GNSS) signals fail.

A novel navigation framework leveraging LTE cellular signals enables sub-meter level accurate UAV positioning in GNSS-challenged environments.

A novel receiver architecture and navigation framework leveraging Doppler measurements from low Earth orbit (LEO) satellites to provide accurate positioning where Global Navigation Satellite System (GNSS) signals are unreliable or unavailable.

Outdoor wireless sensor and camera networks are important for environmental monitoring and public-safety surveillance, yet their real-world deployment still relies heavily on expert intuition and exhaustive simulations that fail to scale in many landscapes. Traditional coverage-maximization techniques evaluate every candidate position for every node while factoring in every other node, the task complexity becomes intractable as node count or terrain granularity grows. The challenge is sharper in three-dimensional topographies where ridges, valleys, and plateaus block line-of-sight and invalidate two-dimensional heuristics. Moreover, once nodes are in the field, relocating them is slow and costly if new blind spots emerge or missions evolve.

Brief description not available

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

An innovative system for biometric identification that utilizes intra-body communication for secure authentication.

ROMANUS is a cutting-edge methodology designed to enhance the performance and robustness of latency-critical, real-time intelligent systems through dynamic neural architectures.

The DDFB laser introduces a novel feedback mechanism for enhanced frequency selectivity and stability in laser oscillation.

      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.

The technology, known as Speech Articulatory Coding (SPARC), is a neural encoding-decoding framework for speech. It works by inferring articulatory features from audio and then synthesizing new speech from those features. The system effectively disentangles the speaker's identity from the speech's articulation, enabling accent-preserving voice conversion and providing a foundation for real-time voice privacy protection.

      Pebble bed reactors (PBRs) are an emerging advanced nuclear reactor design where fuel pebbles constantly circulate through the core, as opposed to housing static fuel assemblies, generating numerous advantages including the ability for online refueling versus expensive shutdowns. Online refueling is overall beneficial but poses an operation challenge in that the pebbles must be measured and analyzed for burnup characteristics very quickly (in under 40 seconds), without much time to cool down, challenging the high Purity Germanium (HPGe) detectors historically used for burnup measurements. HPGe detectors can normally only be operated up to tens of thousands of counts per second, far below radiation rates from freshly discharged fuel, and are therefore operated at large distances from sources, with significant shielding. Only a small fraction of detected counts comes from burnup markers, yielding high uncertainty, or can be completely masked by effects of Compton scattering within the detectors.      To overcome the challenges of using HGPe detectors to measure burnup in continuously fueled reactors, UC Berkeley researchers have developed a novel technology capable of measuring gamma rays within a fine energy ranges and without the interference of Compton scattering. The device is also significantly cheaper than HPGe detectors and offers a reduced detector footprint. Nuclides including but not limited to Np-239, Eu-156, and Zr-95 can be measured and analyzed for burnup, path information through the core, and fast and thermal fluence. Furthermore, precise measurement of the Np-239 content provides better data for reactor safeguard purposes. The technology offers meaningful improvements in measurement accuracy, footprint, and cost, for PBRs and other continuously fueled reactors, such as molten salt reactors (MSRs).

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.

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.

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

Brief description not available

      Probabilistic Seismic Hazard Analysis (PSHA) has become a foundational method for determining seismic design levels and conducting regional seismic risk analyses for insurance risk analysis, governmental hazard mapping, critical infrastructure planning, and more. PSHA traditionally relies on two computationally intensive approaches: Riemann Sum and conventional Monte Carlo (MC) integration. The former requires fine slices across magnitude, distance, and ground motion, and the latter demands extensive synthetic earthquake catalogs. Both approaches become notably resource intensive for low-probability seismic hazards, where achieving a COV of 1% for a 10−4 annual hazard probability may require 108 MC samples.       UC Berkeley researchers have developed an Adaptive Importance Sampling (AIS) PSHA, a novel framework to approximate optimal importance sampling (IS) distributions and dramatically reduce the number of MC samples to estimate hazards. Efficiency and accuracy of the proposed framework have been validated against Pacific Earthquake Engineering Research Center (PEER) PSHA benchmarks covering various seismic sources, including areal, vertical, and dipping faults, as well as combined types. Seismic hazards are calculated up to 3.7×104 and 7.1×103 times faster than Riemann Sum and traditional MC methods, respectively. Coefficients of variation (COVs) are below 1%. Enhanced “smart” AIS PSHA variants are also available that outperform “smart” implementations of Riemann Sum by a factor of up to 130.

Researchers at the University of California, Davis have developed a green technology designed for the efficient storage and discharge of heat energy sourced from intermittent green energy supplies.

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.

Rapid antimicrobial susceptibility testing (AST) is a method for quickly determining the most effective antibiotic therapy for patients with bacterial infections. These techniques enable the detection and quantification of antibiotic-resistant and susceptible bacteria metabolites at concentrations near or below ng/mL in complex media. Employing bacterial metabolites as a sensing platform, the system integrates machine learning data analysis processes to differentiate between antibiotic susceptibility and resistance in clinical infections within an hour. With the results, a clinician can prescribe appropriate medicine for the patient's bacterial infection.

An increase in threatening situations in school environments requires individuals to be ready to secure egress doors quickly to prevent intruders and other uninvited individuals from entering a space. Given the numerous variables that can affect where, when, how, or even if individuals can shelter-in-place during an emergency, there is a need for a simple, portable, lightweight, and cost-effective door security device that installs quickly and easily—without tools—on outward swinging doors from within the room being secured. The inventors have developed a device that can secure an outward swinging egress door from within a room, enabling occupants of a space to quickly barricade a room's entrance during a lockdown or other emergency requiring shelter-in-place protocols. In contrast to other known door security devices and systems for securing a hinged, outward swinging egress door, this improved door security device is portable, lightweight, easy-to-install without tools, and adaptable to doors with different handle, jamb, and casing combinations or measurements. This discrete, on-the-go security device for securing an outward swinging door is not dependent on any furnishings or security apparatus of a particular space.