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

Invention is a system and method for controlling a multi-nozzle sprayer.

Chronic wounds affect over 6.5 million people in the United States costing more than $25B annually. 23% of military blast and burn wounds do not close, affecting a military patient's bone, skin, nerves. Moreover, 64% of military trauma have abnormal bone growth into soft tissue. Slow healing of recalcitrant wounds is a known and persistent problem, with incomplete healing, scarring, and abnormal tissue regeneration. Precise control of wound healing depends on physician's evaluation, experience. Physicians generally provide conditions and time for body to either heal itself, or to accept and heal around direct transplantations, and their practice relies a lot on passive recovery. And while newer static approaches have demonstrated enhanced growth of non-regenerative tissue, they do not adapt to the changing state of wound, thus resulting in limited efficacy.

Digital integrated circuit design has evolved significantly over the past several decades, with synthesis becoming increasingly automated and sophisticated. The traditional synthesis flow emerged in the 1980s when commercial logic synthesis packages from companies like Cadence and Synopsys revolutionized chip design by automatically converting hardware description languages (HDL) into gate-level netlists. Electronic design automation (EDA) tools evolved from simple netlist extraction to complex optimization processes, progressing through gate-level optimization, register-transfer-level synthesis, and eventually algorithmic synthesis. However, as designs have grown exponentially in complexity, synthesis times have become a major bottleneck, with full synthesis often taking hours or days for large designs, significantly impacting designer productivity and iteration cycles. Long synthesis runtimes prevent designers from rapid iteration, with typical synthesis taking 3+ days for complex designs, forcing designers to carefully consider when to submit jobs and wait for delayed feedback. The traditional register-transfer level (RTL) design flow suffers from critical limitations including the inability for RTL engineers to identify and resolve top-level timing issues early in the design process, routing congestion problems that cannot be detected until placement is completed, and insufficient feedback on power consumption during early architectural phases. Additionally, even small design changes trigger full re-synthesis of large blocks, wasting computational resources on unchanged portions of the design, while inter-module optimization requirements often degrade quality-of-results (QoR) when designs are artificially partitioned.

Conventional methods for dehydrogenation often require harsh conditions and produce harmful by-products. This invention introduces a novel approach using semiconductor-based photo redox catalysts to facilitate sustainable dehydrogenation reactions. The technology, developed by researchers at UC Berkeley, offers a more efficient and environmentally friendly alternative to existing processes by using light energy to drive the dehydrogenation of alcohols and amines. This process not only operates under milder conditions but also promotes the production of valuable chemical products while minimizing waste.

This innovation addresses the limitations of producing proteins with non-natural monomers (NNMs), which have valuable applications in drug discovery and materials science. Researchers at UC Berkeley have developed novel PylRS-tRNAPyl pairs that enable the efficient incorporation of NNMs into proteins. This technology provides a significant advantage over existing methods by offering a broader range of NNM incorporation with high specificity and efficiency.Provided are compositions and methods for creating proteins that contain non-natural monomers (NNMs) using new PylRS-tRNAPyl pairs.  This technology works by introducing a subject PylRS, a tRNA, and an NNM into a host system, such as a bacterial cell, eukaryotic cell, or an in vitro translation system, allowing the tRNA to be acylated with the NNM by the PylRS.

The DALMSI framework is a novel method for inferring a user's latent mental states from their digital activity. Researchers at UC Berkeley developed this technology to address the limitations of traditional, intrusive methods like surveys or physical sensors. The system works by receiving and segmenting a stream of digital interaction data, and then uses neural encoding to transform these segments into representations, which a machine learning model maps to specific internal states like cognitive load or emotional state. This offers a non-intrusive, real-time, and scalable solution for understanding user experience without requiring a user's conscious effort or special hardware.