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 method for synthesizing nanotubes that eliminates common impurities and defects, enabling faster production.

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      On-chip ultrafast light devices with a compact footprint and low cost would provide a practical platform for applications such as optical signal processing, molecular sensing, microwave generation and nonlinear optical processes. With the help of recent advances in nanofabrication techniques, the ability to reach low propagation loss on-chip has driven the development of high-quality (Q) factor microresonators. These microresonators allow for microcomb and pulse generation under intense continuous wave (CW) pumping. However, low nonlinear conversion efficiencies and high repetition rates, fixed by the resonator geometry, make achieving ultrashort pulses with high peak power remains an ongoing challenge.       To overcome these challenges, UC Berkeley researchers have demonstrated the integration of an electro-optic-comb system and dispersion-engineered nonlinear waveguides on a thin-film lithium niobate platform. The compact, on-chip device can achieve 35-fs pulse generation, corresponding to 6.7 cycles at 1550 nm, via higher-order soliton compression. The present invention facilitates development of ultrafast nano-optics and nano-electronics.

      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.

      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.

Researchers at the University of California, Davis have developed a photothermal patterning flow cell that enables precise and efficient patterning of polymer films, compatible with existing cleanroom photolithography equipment.

Researchers at the University of California, Davis have developed an artificial intelligence machine that uses a combination of electronic neuromorphic circuits and photonic neuromorphic circuits.

      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.

Optical neural networks (ONNs) are a promising computational alternative for deep learning due to their inherent massive parallelism for linear operations. However, the development of energy-efficient and highly parallel optical nonlinearities, a critical component in ONNs, remains an outstanding challenge. To address this situation, researchers at UC Berkeley and Berkeley National Lab developed a nonlinear optical microdevice array (NOMA) compatible with incoherent illumination by integrating the liquid crystal cell with silicon photodiodes at the single-pixel level. The researchers fabricated NOMA with over half a million pixels, each functioning as an optical analog of the rectified linear unit at ultralow switching energy down to 100 femtojoules/pixel. The team demonstrated an optical multilayer neural network. This work holds promise for large-scale and low-power deep ONNs, computer vision, and real-time optical image processing.

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.

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The present invention describes a novel method for acid-free pyrolytic synthesis of metal-nitrogen-carbon (M-N-C) catalysts for use in fuel cell/energy conversion applications. This method allows for rapid production of M-N-C catalysts that exhibit high activity and selectivity for CO2 electroreduction without needing harsh acids or bases.

Currently, thin films of single-crystalline (SC) alloy material are obtained using costly SC substrates made of a material chemically and physically compatible to that of a SC thin film that is deposited on the SC substrate. Formation of SC thin films of alloy materials on SC substrates are typically achieved through fairly expensive processes such as epitaxy. As a result, the use of a thin film of SC alloy materials or respective multiple thin films is contingent upon the availability of an appropriate SC substrate thereby severely limiting its utilization. Thus, there is a need for alternative methods of forming one or more thin films of SC alloy materials on arbitrary substrates. Crystallization of thin film materials by exploiting laser-induced crystallization has been advancing for the past four decades. This unique thin film technique has been predominantly used in processing thin film materials made of a single chemical element, with a significant emphasis on thin film materials comprised of a single chemical element like silicon (Si), used for the development of thin film transistors. While this approach has worked well for thin film materials comprised of a single chemical element like silicon (Si) it is not easily extended for use with thin film materials containing multiple chemical elements (e.g., metal oxides). For certain bulk manufacturing applications, it would be desirable to efficiently form thin structures on non-single-crystalline (NSC) substrates, such as glass, or on SC substrates that are highly-incompatible, such as silicon. For such applications, it is highly desirable that the treated SC alloy layer(s) have chemical compositions not significantly different from those of their original chemical compositions.

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Gallium nitride is an essential semiconductor material that has shown great promise in electronic and optoelectronic applications. Its synthesis traditionally requires high temperatures (~300-1000℃) and/or pressures (~1-100MPa) in order to break the strong bond in molecular nitrogen. Manufacture of gallium nitride and similar semiconductor materials under these conditions is very expensive. Additionally, artificial nitrogen fixation in the form of ammonia manufacture is critical to the global food supply, but similarly requires very expensive high temperature and/or pressure synthesis. To address these problems, researchers at UC Berkeley have developed a method to synthesize gallium nitride from molecular nitrogen at approximately room temperature (30℃) and atmospheric pressure. This process can be accomplished more cheaply than traditional methods, using only standard reagents and equipment. Researchers have confirmed that prior to the synthesis of gallium nitride, atomic nitrogen is freely dissociated. This suggests that a similar method can be used in the manufacture of other nitride semiconductor materials, or even of nitrogenous substances such as ammonia.

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The inventors have discovered a new way to generate ultrafast back-gating, by leveraging the surface band bending inherent to many semiconductor materials. This new architecture consists of a standard bulk semiconductor material and a layered material on the surface. Optical pulses generate picosecond time-varying electric fields on the surface material. The inventors have successfully applied this method to a quantum well Rashba system, as this is considered today one of the most promising candidates for spin-based devices, such as the Datta Das spin-transistor. The technology can induce an ultrafast gate and drive time-dependent Rashba and quantum well dynamics never observed before, with switching faster than 10GHz. This approach minimizes lithography and will enable light-driven electronic and spintronics devices such as transistors, spin-transistors, and photo-controlled Rashba circuitry. This method can be applied with minimal effort to any two-dimensional material, for both exfoliated and molecular beam epitaxy grown samples. Electric field gating is one of the most fundamental tuning knobs for all modern solid-state technology, and is the foundation for many solid-state devices such as transistors. Current methods for in-situ back-gated devices are difficult to fabricate, introduce unwanted contaminants, and are unsuited for picosecond time-resolved electric field studies.  

With the two-dimensional scaling of silicon field-effect transistors reaching fundamental limits, new functional improvements to transistors, as well as novel computing paradigms and vertical device integration at the architecture-level, are currently under intense study. Gate oxides play a critical role in this endeavor, as it’s a common performance booster for all devices, including silicon, new channel materials with potential for higher performance, and even materials suitable for three-dimensional integrated transistors.With the scaling of lateral dimensions in advanced transistors, an increased gate capacitance is desirable both to retain the control of the gate electrode over the channel and to reduce the operating voltage. To pursue these performance gains, UC Berkeley researchers invented a new heterostructure insulator material where: 1) the material possesses specific ferroic order such as ferroelectricity/anti-ferroelectricity or a mixture of both; 2) the overall dielectric property such as the permittivity is determined by the stacking order of different layers rather than exact volume fraction of the constituents; and 3) the material is composed of one or several repetition of ultra thin superlattice periods ranging from a few angstroms to 3 nm.

Covalent organic frameworks (COFs) are 2D or 3D extended periodic networks assembled from symmetric, shape persistent molecular 5 building blocks through strong, directional bonds. Traditional COF growth strategies heavily rely on reversible condensation reactions that guide the reticulation toward a desired thermodynamic equilibrium structure. The requirement for dynamic error correction, however, limits the choice of building blocks and thus the associated mechanical and electronic properties imbued within the periodic lattice of the COF.   UC Berkeley researchers have demonstrated the growth of crystalline 2D COFs from a polydisperse macromolecule derived from single-layer graphene, bottom-up synthesized quasi one-dimensional (1D) graphene nanoribbons (GNRs). X-ray scattering and transmission electron microscopy revealed that 2D sheets of GNR-COFs self-assembled at a liquid-l quid interface stack parallel to the layer boundary and exhibit an orthotropic crystal packing. Liquid-phase exfoliation of multilayer GNR-COF crystals gave access to large area bilayer and trilayer cGNR-COF films. The functional integration of extended 1D materials into crystalline COFs greatly expands the structural complexity and the scope of mechanical and physical materials properties.

UCLA researchers in the Department of Mechanical & Aerospace Engineering have developed a novel boron arsenide (BAs) material that has an ultra-high thermal conductivity of 1300 W/mK and low cost of synthesis and processing.