A novel theoretical model enables efficient and cost-effective solar-driven water splitting to generate clean, storable hydrogen fuel.

A novel reactor design that enables cost-effective green hydrogen production via solar water splitting, targeting $1/kg-H2 at scale.

      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.

This technology addresses the challenge of achieving continuous, full-range output voltage regulation in flying capacitor multilevel converters. A key problem with existing control methods for these converters is the difficulty in transitioning between different operational states, which can lead to instability and poor performance. UC Berkeley researchers have developed a novel modulation technique that uses multiple reference currents to ensure a smooth transition and maintain stable steady-state operation across all nominal duty ratios. This innovation provides improved natural balancing of the flying capacitor voltages and fast balancing dynamics, which are significant advantages over other modulation schemes. The proposed method resolves the issues of steady-state discontinuity seen in preliminary implementations, making it a more robust and reliable solution for power conversion applications.

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

An innovative approach to stabilize non-precious metal catalysts for enhanced efficiency and durability in PEM electrolyzers.

This technology introduces a novel method of producing high-efficiency, durable electrodes for polymer electrolyte membrane water electrolysis (PEMWE) using electrospinning.

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 introduces a novel electrocatalyst design that significantly improves stability and activity for oxygen evolution reaction (OER) in acidic environments.

The problem of carbon dioxide (CO2​) emissions from industrial processes and mixed gas streams presents a significant global challenge, often addressed by energy-intensive and costly technologies. UC Berkeley researchers have developed an innovative solution for capturing and removing CO2​ in an energy-efficient, isothermal manner. The invention is a novel composition that uses a porous organic framework of solid molecular hexamine, specifically 2,3,6,7,14,15-hexakis(aminomethyl)triptycene, that assembles into a three-dimensional ammonium carbamate network. This unique network possesses two one-dimensional pores that selectively capture CO2​ upon exposure. This technology enables the capture and subsequent release of CO2​ without the large temperature or pressure swings required by conventional methods, offering a more sustainable and economically viable approach to carbon management.

       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).

An innovative Palladium hydride catalyst that significantly enhances the electroreduction of carbon dioxide (CO2) to formate with exceptional tolerance for carbon monoxide (CO).

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.

      The demand for miniaturized power electronics with increased efficiency and performance motivates the exploration of piezoelectric structures as alternative passive components; piezoelectric components store energy in mechanical compliance and inertia with extremely high quality factors and energy densities significantly greater than those of magnetics at small scales. Recent magnetic-less dc-dc converter designs based on single-port piezoelectric resonators (PRs) have demonstrated power stage efficiencies of 99% and PR power handling densities of up to 5.7 kW/cm3. While marking tremendous milestones, such performance has only been achieved in non-isolated dc-dc converters with mild (2:1) voltage conversion ratios, confining the utility of piezoelectric-based power conversion to a narrow subset of applications.       Piezoelectrics may be expanded to a broader set of applications through use of multi-port piezoelectric transformers (PTs), which offer the same advantages as PRs but with the added potential for galvanic isolation and inherent voltage transformation. The present invention overcomes standing performance shortcomings in isolated magnetic-less PT-based dc-dc converters, providing a framework for high-efficiency piezoelectric transformer (PT) designs (wherein isolated PTs serve as the primary passive components in isolated dc-dc converters). One of the proposed PT designs is validated in a dc-dc power converter prototype and demonstrates a peak efficiency of 97.5%. The measured performance represents a 17x reduction in loss ratio compared to previous isolated magnetic-less PT-based dc-dc converter designs, and expands the value of piezoelectrics to applications requiring isolation.

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

An innovative reactor design that converts sunlight into hydrogen fuel efficiently and cost-effectively.

Researchers at the University of California, Davis have developed an approach to generating mechanical power from the earth's ambient thermal radiation using a Stirling engine.

This invention combines the attributes of existing catalyst layer architectures to optimize reactions in solid polymer membrane electrolyzers.

      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.

      Miniaturization and performance of power electronics is fundamentally limited by magnetic components, whose power densities inherently reduce at small scales. Piezoelectric resonators (PRs), which store energy in the mechanical compliance and inertia of a piezoelectric material, offer various advantages for power conversion including high quality factors, planar form factors, opportunity for batch fabrication, and potential for integration. Contrary to magnetic components, PRs have increased power handling densities at small scales. Noteworthy advancements have been made in magnetic-less, PR-based power converter designs, demonstrating significant achievements in both power density (up to 5.7 kW/cm3) and efficiency (up to >99%). However, while PRs are promising alternative passive components, they cannot be used as drag-and-drop replacements for magnetics; achieving high performance in a PR-based converter requires complicated control of multi-stage switching sequences. A need exists for more practical ways to leverage piezoelectrics in power conversion without such added complexity.      To address this challenge, UC Berkeley researchers have developed a piezoelectric component that may be leveraged to directly emulate the dynamics of a magnetic component. The “active inductor” can serve as a drag-and-drop replacement for bulky magnetic inductors in power converters. Power density and efficiency of underlying piezoelectrics are preserved while the design complexity associated with piezoelectric-based power converters is simplified. Detailed models and control strategies for the piezoelectric-based active inductors have been developed and usage demonstrated in a classic buck converter. The active inductor is further validated with closed-loop simulation results and open-loop experimental results, confirming its inductor-like behavior.

Current methods for CO2­ ­capture and concentration (CCC) are energy intensive due to the reliance on thermal cycles, which are intrinsically Carnot limited in efficiency. Electrochemical carbon dioxide capture and concentration (eCCC) is a modular approach that can achieve significantly higher energy efficiencies than current thermal methods, however eCCC systems have been plagued by oxygen instability. The Yang lab has developed an eCCC approach that is over three times more efficient than any other reported redox carrier-based system and almost twice the efficiency of state-of-the-art alkanolamine-based systems.

Researchers at the University of California, Davis have developed a microfluidic flowmetry technology that achieves on-chip measurement with ultrahigh precision across a wide tunable range.