Researchers at the University of California, Davis have developed methods that leverage measured Casimir interactions combined with machine learning to accurately determine broadband optical properties of materials without direct optical excitation.

Achieving seamless robotic interaction with physical environments requires a sophisticated blend of sensory perception and logical reasoning. UC Berkeley researchers have developed "RealWorldPlay," a physical artificial intelligence system designed to enhance robotic action through a unified multimodal reasoning framework. The system integrates a visuo-tactile policy—combining sight and touch—with a large language model (LLM) that provides real-time verification feedback and strategic planning. By utilizing a "world model" to generate self-training data, the platform allows robots to autonomously set goals and learn from simulated scenarios, ensuring that their physical actions are both reasoned and verified before execution.

Determining the exact direction of a sound source typically requires large microphone arrays and significant computational power. Researchers at UC Berkeley have developed an intelligent acousto-electrical metamaterial system that simplifies this process. The technology utilizes a specialized acoustic transducer divided into multiple interconnected sections. Each section contains a unique arrangement of piezoelectric metamaterials designed to generate specific electric signals when stimulated by sound waves. Crucially, these sections possess distinct acoustic beam patterns—geometric sensitivities to sound—that allow the system to differentiate between incoming angles. Because the sections are in physical contact, they work in tandem to provide highly accurate "direction of arrival" (DOA) data within a compact, hardware-efficient form factor.

Monitoring the structural integrity of buildings traditionally requires expensive, specialized sensor networks that are difficult to deploy at scale. UC Berkeley researchers have developed a novel approach that leverages the existing network of smartphones equipped with the MyShake earthquake early warning application. By utilizing the highly sensitive accelerometers within millions of consumer devices, the system measures the natural frequencies and damping ratios of buildings through ambient vibrations. This crowdsourced data provides a real-time, large-scale assessment of structural health across entire urban environments. The platform effectively transforms everyday mobile devices into a distributed seismic monitoring array, allowing for continuous observation of building performance without the need for dedicated hardware installations.

Developing robotic hands that can safely and effectively grasp a wide variety of objects remains a significant challenge, often requiring heavy motors and complex sensor arrays. Researchers at UC Berkeley have developed an underactuated dual-finger mechanism that features a unique force-triggered carpometacarpal (CMC) joint articulation. By utilizing underactuation—where a single motor drives multiple degrees of freedom—the design achieves high dexterity with minimal mechanical complexity. The CMC joint is engineered to respond passively to contact forces, allowing the fingers to wrap around objects of varying shapes and sizes automatically. This innovation enables a natural, compliant grip that mimics human hand mechanics, providing a lightweight and cost-effective solution for advanced manipulation.

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

The implementation of cost-effective and reliable energy storage solutions, such as redox flow batteries, is often hindered by the complexity and expense of accurately monitoring their state of charge (SOC) and state of health (SOH). To address this, a novel approach using low-cost management systems and methods has been developed for electrochemical cells based on viologen, particularly pyridinium redox flow batteries. This innovation centers on pH signaling and regulation to enable real-time SOC and SOH monitoring. The viologen species' electrochemical processes naturally induce localized pH changes, and by monitoring and regulating the pH within the cell, researchers can obtain immediate, actionable data on the battery's operating condition. This pH-based system offers a simple, integrated, and economical alternative to conventional, often more complex, monitoring techniques.

Traditional imaging techniques often rely on bulky hardware or complex computational methods to resolve depth. UC Berkeley researchers have developed a three-dimensional imaging system that utilizes piezoelectric micromachined ultrasound transducers to capture high-resolution spatial data with an integrated approach that allows for compact, high-performance imaging that can be used in a variety of environments where traditional optical or radar systems might be limited.

Researchers at the University of California, Davis have developed tactile feedback systems that enhance spatial and sensory resolution in sensor arrays through unique signal modulation techniques.

Multimode optical fiber was first introduced in astrophotonics applications as “light pipes” to transport light from telescopes to instruments. The integration of multimode optical fiber helped to maximize light collection but offered little control over the propagation modes from the collected light, which affects the quality and speed of light transmission. Single-mode optical fiber used in interferometry proved invaluable for spatial filtering and wavefront correction, providing a stable, reliable, and flexible way to guide light in precision sensing and imaging. Photonic lanterns were conceived in the early 2000s to help bridge a gap between the light-gathering efficiency of multimode optical fiber and the precision of single-mode optical fiber. Photonic lantern devices have reasonably addressed the efficient conversion needs between multimode/ multi-modal and multiple single-mode light paths. However, challenges remain with respect to improving and scaling of photonic lantern devices, including coupling efficiency/losses, bandwidth limitations, and high-order mode (>20) capabilities.

A groundbreaking system that enables navigation in GPS-denied environments by using intelligent systems to mimic biological systems that recognize locations through visual cues and perform contextually appropriate actions.

This technology represents a significant leap in radar systems, offering millimeter-scale range resolution and high angular resolution.

This technology enhances the sensitivity of sensors through exceptional points of degeneracy in various circuit configurations.

Brief description not available

Brief description not available

An innovative technique for creating high-sensitivity Whispering Gallery Mode (WGM) sensors through advanced microbubble resonator fabrication.

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.

An innovative approach to vehicle localization and mapping using lidar and cellular LTE data, enhancing accuracy without relying on GNSS signals.

Traditional methods for monitoring a building's structural health, particularly its natural frequencies and damping ratios, typically rely on expensive, permanently installed sensor systems, which are not widely accessible. This innovation, developed by UC Berkeley researchers, provides a highly scalable and cost-effective method for Monitoring Building Structural Health using Smartphones and Ambient Vibrations. The method leverages smartphones equipped with the MyShake earthquake early warning application to measure the ambient vibrations of a building. By analyzing these vibrations, the application can accurately determine key structural health parameters, namely the building's natural frequencies and damping ratios. This technique transforms readily available personal devices into powerful structural monitoring tools, offering a vastly more accessible and lower-cost solution than existing dedicated sensor networks.

      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.

Sensors are used in a multitude of applications from molecular biology, chemicals detection to wireless communications. Researchers at the University of California Irvine have invented a new type of electronic circuit that utilizes exceptional points of degeneracy to improve the sensitivity of signal detection.

      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).

Traditional hydraulic actuators can be rigid, bulky, and difficult to integrate into flexible or small-scale applications, limiting their use in emerging fields like soft robotics and haptic feedback. This innovation, developed by UC Berkeley researchers, is a Flexible Hydraulic Actuator Based on Electroosmotic Pump. It addresses this limitation with a compact, flexible design that uses an electroosmotic pump (EOP) to achieve controlled shape changes. This unique structure allows the actuator to be configured to change its shape, color, and optical characteristics with low power consumption, offering a distinct advantage in flexibility and miniaturization over conventional actuators.

Current methods for designing metamaterials to achieve a specific, complex physical response curve are often time-consuming, computationally intensive, and struggle with precisely programming nonlinear functional responses. This innovation, developed by UC Berkeley researchers, addresses this by offering a novel, accelerated inverse design method that leverages a hybrid machine learning approach combining imitation learning and reinforcement learning with Monte Carlo tree search (MCTS). This unique combination allows for the rapid and precise generation of metamaterial structures that meet a plurality of target physical response features, significantly outperforming traditional iterative or purely generative design methods in efficiency and programmability. The resulting metamaterial designs exhibit highly programmable and non-intuitive functional properties.