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      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.

      State-of-the-art scanning probe microscopy (SPM) systems, including microwave impedance microscopy (MIM) and near-field scanning microscopy (NSOM), typically operate in a dynamic, non-contact “tapping” mode. Lock-in detection at the probe cantilever’s resonant mechanical oscillation frequency mitigates effects of drift and achieves high measurement sensitivity of local material characteristics. Electrical, mechanical, or other material properties can be measured down to the nanoscale. However, a full time-domain tip-sample response would yield a much richer data set. Unfortunately, existing methodologies require moving the entire scan head to sweep the tip-sample separation at rates far below the resonant frequency of the cantilever or tuning fork—yielding slow scan speeds and outputs vulnerable to drift, 1/f noise, and stray coupling.       To overcome these challenges, UC Berkeley researchers have leveraged high-speed data acquisition, wideband detection electronics, and modern real-time computing to acquire hyperspectral datasets at twice the mechanical resonant frequency of the probe. The invention captures up to hundreds of thousands of curves per second, without sacrificing scan speed, resolution, or stability. It can be straightforwardly integrated on most commercial SPM platforms, and for a wide range of resonantly driven probes, including cantilevers, quartz tuning forks, and qPlus sensor. Among other benefits, the technique enables novel post-processing capabilities, including retrospective enhancement of spatial resolution.

A method to manufacture stretchable circuit boards using silver ink for wearable applications.

A revolutionary enzyme technology for ambient temperature and pressure ammonia synthesis from dinitrogen gas.

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

Oxygen Evolution Reaction (OER) is crucial for various renewable energy applications, but current electrocatalysts often face issues with stability, efficiency, and cost. This invention addresses these challenges by introducing a novel method for synthesizing robust oxygen evolution electrocatalysts. The technology, developed by UC Berkeley researchers, utilizes calixarene-templated iridium compositions. This approach yields highly stable and efficient electrocatalysts, offering significant advantages over traditional iridium-based catalysts. Specifically, this innovation provides superior performance and durability, making it a valuable tool for energy systems like electrolyzers and fuel cells.

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

Dr. René Riedel and Stephen Lepore from the University of California, Riverside have developed an NMR tube/reactor that enables in-situ irradiation to photo-initiate reactions in an inert or controlled atmosphere. It allows for the data acquisition of air, moisture, and temperature-sensitive liquid samples by nuclear magnetic resonance (NMR) spectroscopy without needing to remove the sample from the spectrometer for irradiation. This technology is advantageous because it makes photochemical reactions and kinetic measurements of sensitive samples more reproducible, and it enables the previously impossible maintenance of a controlled environment during photochemical NMR investigations.

The challenge of developing materials that offer multifunctionality—specifically combining fluorescence, long-term pollutant sorption, and catalytic efficiency—is significant in materials science. This innovation addresses this by providing Coumarin-linked Covalent Organic Framework (COF) compositions. These unique COFs have crystalline porous polymers with exceptional stability and high surface area. Developed by UC Berkeley researchers, these COF compositions distinguish themselves from conventional materials by offering a highly stable, long-sustaining sorbent capable of removing pollutants over extended periods, while also serving as a highly efficient, regenerable catalyst and a versatile fluorescent material.

The increasing global energy demands and the need for sustainable practices present an opportunity for integrated systems that offer both energy efficiency and resource recovery. This Integrated Seawater Air Conditioning and Seaweed Cultivation System for Sustainable Energy and Resource Recovery addresses these challenges by utilizing the typically wasted cold deep-sea water effluent from a Seawater Air Conditioning (SWAC) system to support the cultivation of seaweed. The SWAC system itself provides highly efficient, low-energy cooling by circulating cold deep-sea water through a heat exchanger to chill a closed-loop coolant.

The challenge in utilizing α-Linolenic acid (ALA) for medical adhesives has been its poor water solubility and the high hydrophobicity of poly(ALA), typically necessitating elevated temperatures, organic solvents, or complex preparation methods for tissue application. UC Berkeley researchers have developed ALA-based powder and low-viscosity liquid superglues that overcome this limitation by polymerizing and bonding rapidly upon contact with wet tissue. The versatile adhesives are formulated using a monomeric mixture of ALA, sodium lipoate, and an activated ester of lipoic acid. These adhesives demonstrate high flexibility, cell and tissue compatibility, biodegradability, and potential for sustained drug delivery as a small molecule regenerative drug was successfully incorporated and released without altering the adhesive's properties. Additionally, the inherent ionic nature of the adhesives provides high electric conductivity and sensitivity to deformation, enabling their use as a tissue-adherent strain sensor.

The invention addresses the problem of recycling high-performance thermosets by developing a chemical process to deconstruct cycloolefin resins (CORs) that contain dicyclopentadiene (DCPD) crosslinkers. This process, developed by UC Berkeley researchers, uses a second-generation Hoveyda–Grubbs ruthenium(II) alkylidene catalyst for deconstruction via ring-closing metathesis. The method selectively reforms the cyclopentene ring in DCPD, allowing the resulting linear polyDCPD chains to be reused in new manufacturing cycles. This enables resin-to-resin circularity, with up to 84% of the linear DCPD being retrievable from end-of-life thermosets. The properties of the recycled material are comparable to the original, and the process works on various commercial and model CORs.

       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.

      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.

      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).

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

Cement manufacturing is an energy-intensive process, traditionally requiring high-temperature kilns, which contributes significantly to industrial energy consumption and emissions. This innovation, developed by UC Berkeley researchers, presents a novel, energy-efficient method for producing cementitious materials.

      Effective thermal management remains a critical challenge in designing and operating next-generation electronics, data centers, and energy systems. Devices are steadily shrinking and handling increased power densities. Traditional cooling strategies, such as heat sinks and immersive cooling systems, fall short in delivering the targeted, localized cooling needed to prevent or address thermal hotspots. Current solutions for localized hotspot cooling require active, energy-intensive methods like pumping of coolants and complex thermal architecture design.       To overcome these challenges, UC Berkeley researchers present a transformative passive method for localized, autonomous cooling of hotspots. The cooling system delivers effective, localized cooling across various device surfaces and geometries, including those geometries wherein cooling media must move against gravity. The benefits of the present system will be appreciated for computer chip and other electronics cooling, microgravity applications, battery thermal management. Beyond thermal management, the underlying system may also open novel avenues in fluid manipulation and energy harvesting.

A novel technique for the safe and efficient production of neodymium oxide microspheres, serving as a non-radioactive surrogate for americium oxide synthesis.

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.

Researchers at the University of California, Davis (“UC Davis”) have developed an optical absorber/emitter for thermophotovoltaics application with a tunable emission wavelength.

      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.

This invention describes a novel method for the inhibition of specific potassium ion channels, particularly TWIK-related arachidonic acid-activated K+ channels (TRAAK), using cannabinoid compounds. The research demonstrates that these compounds can be used to modulate the function of these channels, which are implicated in various neurological and physiological disorders, including epilepsy. This approach presents a new pharmacological strategy for targeting these channels and developing treatments for associated conditions.

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