The Global Navigation Satellite System (GNSS) consists of a family of satellite navigation systems (like GPS, Galileo, GLONASS, BeiDou) which provide global positioning and navigation from orbiting satellites. GNSS is one of the major inputs for phone location. Accurate pedestrian localization in “urban canyons” has long been limited by GNSS multipath errors and blocked line-of-sight, especially for blind and low-vision pedestrians who need sidewalk-level accuracy. GNSS-based positioning in dense downtowns is often limited to tens of meters off because skyscrapers block satellites, create multipath, and reduce signal quality, leading to especially large errors that make it hard to know which side of a street a pedestrian is on. For blind and low‑vision users, conventional smartphone navigation (pure GNSS, camera‑based visual positioning system, or beacon infrastructure) does not offer reliable, hands‑free, street‑side-accurate guidance. Most accuracy-focused approaches to date require detailed 3D models, specialized hardware, and/or substantial map annotations, limiting the scalability across urban environments and challenging mainstream apps deployment. Moreover, for blind and low‑vision pedestrians, integrating precise localization with usable, low‑attention interaction (i.e., no constant camera use, minimal screen looks) and robust crossing guidance is still a problem.

A monoclonal antibody that selectively targets the NLRP3 pyrin domain to inhibit inflammasome activation in inflammasome-related diseases.

Researchers at the University of California, Davis in collaboration with Deutsche Telekom AG have developed a system and method for monitoring network traffic by dynamically routing traffic sub-populations over fixed monitoring locations without violating traffic engineering policies. This approach leverages existing routing flexibility to collect high-quality flow data without disrupting normal traffic engineering policies

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

Researchers at the University of California, Davis have developed a solid-state X-ray imager with high temporal resolution.

Historically, radio frequency and microwave switches have historically relied on either electromechanical switches (which suffer from limited speed and reliability) or solid-state switches such as PIN diodes and field-effect transistors (FETs), both of which require continuous bias current to maintain their states, consuming significant power in modern communication systems. In particular, solid-state switches (PIN diodes and FETs) require continuous DC power to maintain their ON or OFF states, leading to substantial energy consumption particularly problematic for battery-operated devices and large-scale systems like 5G/6G base stations and Internet of Things networks. Emerging non-volatile RF switches based on phase-change materials (PCM) and other memristive devices have shown promise but are constrained by large switching energies, limited resistance modulation ratios (typically < three orders of magnitude), volatile behavior requiring thermal maintenance above transition temperatures, and low endurance.

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.

The use of standing surface acoustic waves (SSAWs) in microfluidic channels gained significant momentum when researchers demonstrated size-based cell separation (acoustophoresis) using lateral acoustic forces. Using interdigitated transducers (IDTs) positioned on piezoelectric substrates, SSAWs were found to create pressure nodes along the channel width, allowing larger particles to experience greater acoustic radiation forces and migrate toward these nodes faster than smaller particles. Acoustic-based microfluidic devices were successfully applied to circulating tumor cell (CTC) isolation from clinical blood samples in ~2015, demonstrating recovery rates >80% using tilted-angle standing surface acoustic waves, though these systems relied primarily on size-based separation principles. The integration of acoustic methods with microfluidics offered key advantages including label-free operation, biocompatibility, non-contact manipulation, and preservation of cell viability, addressing limitations of earlier methods like centrifugation, FACS, and magnetic separation that could damage cells or require labeling. Despite these advances in acoustic microfluidics, significant challenges persist in affinity-based rare cell isolation, particularly mass transport limitations in microfluidic channels operating at high Peclet numbers (Pe>10⁶) where convective flow dominates over diffusion. In traditional microfluidic affinity capture systems, cells flow predominantly in the center of laminar flow channels where fluid velocity is highest, resulting in minimal interaction with capture agents immobilized on channel walls and requiring extremely long channels or impractically slow flow rates to achieve adequate capture efficiency. The extremely low concentration of CTCs , combined with their phenotypic heterogeneity and the low diffusion coefficients of cells creates a "needle in a haystack" challenge that existing acoustic separation methods based solely on size discrimination cannot adequately address.

The critical challenge of providing clean, potable water in arid and semi-arid regions can be addressed by technologies that efficiently harvest atmospheric water, particularly under low-humidity conditions. UC Berkeley researchers have developed novel thiazole-based Covalent Organic Frameworks (COFs) that serve as highly efficient sorbents for this purpose. These COFs are crystalline, porous materials characterized by high porosity, permanent pore structures, and a chemically tunable nature. The disclosed COFs demonstrate a significant advantage over alternatives by exhibiting a low-humidity water uptake onset, coupled with fast adsorption kinetics, a high water working capacity, and excellent cycling stability. Furthermore, the development includes scalable synthetic methods, such as microwave-assisted and reflux routes, which enable gram-level, practical production.

      The widespread occurrence of nutrient-rich and metal-contaminated wastewater presents an environmental challenge and untapped economic opportunity. Ammonia, copper, and phosphorous are prime targets. For example, ammonia is industrially produced by the Haber-Bosch process, a highly energy-intensive (~12.5 kWh/kg-N to convert N2 to ammonia, consuming 1-2% of global energy usage) and greenhouse gas-emitting (~1.2% of global CO2 emissions) technique. After use, primarily as fertilizer, nearly 50% of all U.S.-consumed ammonia ends up in municipal wastewater and animal feedlot retention systems. Technologies presently proposed for recovering critical nutrients and metals from wastewater are limited in scalability by high energy demands, costly chemicals or membrane requirements, low efficiencies, or fouling challenges.       UC Berkeley researchers have developed and demonstrated a low-cost, robust, and near-zero-energy reactor that simultaneously recovers ammonia and other valuable ions (e.g., P and Cu) from wastewater streams. The reactor is driven by sunlight or low-grade waste heat, such that it eliminates the need for external pumping—further cutting energy consumption and capital cost. The functional material is an inexpensive cloth that is also roll-to-roll compatible, making it economically scalable and easy to manufacture. The reactor can be implemented within wastewater streams including municipal wastewater, animal feedlot wastewater, and organic waste digestate. It may further be adapted to recover other valuable resources, such as lithium, from sources like mining wastewater and landfill leachate. It may even be extended beyond nutrient and metal recovery to separation or pre-concentration of volatile organic compounds such as ethanol and methanol from aqueous solutions.

Brief description not available

QAFeL is a novel asynchronous federated learning framework that combines buffered aggregation with bidirectional quantized communications, achieving up to 8× lower communication costs while preserving convergence speed and accuracy.

WiFi-based indoor positioning has been a widely researched area for the past five years, with systems traditionally relying on signal telemetry data including Received Signal Strength Indicator (RSSI), Channel State Information (CSI), and Fine Timing Measurement (FTM). However, adoption in practice has remained limited due to environmental challenges including signal fading, multipath effects, and interference that significantly impact positioning accuracy. Existing machine learning approaches typically require extensive manual feature engineering, preprocessing steps like filtering and data scaling, and struggle with missing or incomplete telemetry data while lacking flexibility across heterogeneous environments. Furthermore, there is currently no unified model capable of handling variations in telemetry data formats from different WiFi device vendors, use-case requirements, and environmental conditions, forcing practitioners to develop separate models for each specific deployment scenario.

POEM is a groundbreaking 3D bioprinting technology enabling high-resolution, multi-material, and cell-laden structure fabrication with enhanced cell viability.

EnergyShield is a pioneering framework designed to optimize energy consumption through safe, intelligent offloading of deep neural network computations for autonomous vehicles.

An innovative design automation methodology leveraging graph neural networks to enhance integrated circuit security by mitigating hardware threats and protecting intellectual property.

Current sustainable building materials often lack the high structural strength needed for demanding applications, limiting their use in load-bearing construction. Addressing this opportunity, UC Berkeley researchers have developed SEA-BOARD, a novel structural panel fabricated from marine-derived polysaccharides. This innovation utilizes a proprietary, stepwise process involving polysaccharide extraction, nanofiber alignment, and thermal densification to configure the macroalgal biomass into a high-strength, hot-pressed panel. This engineered material is structurally superior and potentially more environmentally sustainable than many traditional wood-based or synthetic alternatives.

A revolutionary method for improving the efficiency and quality of reprogramming adult cells into stem cells or other therapeutically relevant cell types via adhesome gene manipulation.

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.

This technology revolutionizes hydrogen production by using induction heating for catalytic methane decomposition, significantly increasing hydrogen yield.

High-conversion-ratio power converters used in compact Point-of-Load (PoL) applications, such as data centers or portable electronics, often face the challenge of large size and weight due to the necessary energy-storage components, particularly flying capacitors, while also struggling with switching losses that reduce efficiency. This innovation, developed by UC Berkeley researchers, addresses these issues with a novel regulating hybrid switched-capacitor (HSC) power converter topology referred to as a "Dual Inductor Switching Bus Converter" (DISB converter). The DISB converter combines an initial 2:1 switched-capacitor conversion stage with a Symmetric Dual-Inductor Hybrid (SDIH) conversion stage, capitalizing on the benefits of both. The initial 2:1 voltage reduction significantly reduces the overall volume and weight of the flying capacitors, while the SDIH stage contributes a reduced component count and an excellent switch stress figure of merit. Crucially, a proposed auxiliary circuit block enables near-zero-voltage conditions (partial soft-switching) within the initial 2:1 stage, which significantly improves the converter's overall efficiency.

Flying Capacitor Multilevel Converters (FCMLCs) are widely used in high-power applications, but they present significant control challenges, particularly in maintaining stable and balanced voltages across the numerous flying capacitors while achieving continuous and fast output voltage regulation. This innovation, developed by UC Berkeley researchers, discloses a novel current-programmed modulator with smooth bin transitions that inherently addresses these challenges. The modulator achieves continuous full-range output voltage regulation and, critically, fast flying-capacitor voltage-balancing dynamics . By programming the current and ensuring smooth transitions between the modulator's operational bins, the technology overcomes the limitations of traditional control methods, resulting in a more reliable, efficient, and robust converter topology suitable for demanding high-power applications.

Revolutionizing cement manufacturing through an energy-efficient electrochemical method that produces calcium hydroxide with reduced CO2 emissions.

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.

Brief description not available