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Computation Method For 3D Point-Cloud Holography

 The dynamic patterning of 3D optical point clouds has emerged as a key enabling technology in volumetric processing across a number of applications. In the context of biological microscopy, 3D point cloud patterning is employed for non-invasive all-optical interfacing with cell ensembles. In augmented and virtual reality (AR/VR), near-eye display systems can incorporate virtual 3D point cloud-based objects into real-world scenes, and in the realm of material processing, point cloud patterning can be mobilized for 3D nanofabrication via multiphoton or ultraviolet lithography. Volumetric point cloud patterning with spatial light modulators (SLMs) is therefore widely employed across these and other fields. However, existing hologram computation methods, such as iterative, look-up table-based and deep learning approaches, remain exceedingly slow and/or burdensome. Many require hardware-intensive resources and sacrifices to volume quality.To address this problem, UC Berkeley researchers have developed a new, non-iterative point cloud holography algorithm that employs fast deterministic calculations. Compared against existing iterative approaches, the algorithm’s relative speed advantage increases with SLM format, reaching >100,000´ for formats as low as 512x512, and optimally mobilizes time multiplexing to increase targeting throughput. 

Adaptive Machine Learning-Based Control For Personalized Plasma Medicine

Plasma medicine has emerged as a promising approach for treatment of biofilm-related and virus infections, assistance in cancer treatment, and treatment of wounds and skin diseases. However, an important challenge arises with the need to adapt control policies, often only determined after each treatment and using limited observations of therapeutic effects. Control policy adaptation that accounts for the variable characteristics of plasma and of target surfaces across different subjects and treatment scenarios is needed. Personalized, point-of-care plasma medicine can only advance efficaciously with new control policy strategies.To address this opportunity, UC Berkeley researchers have developed a novel control scheme for tailored and personalized plasma treatment of surfaces. The approach draws from concepts in deep learning, Bayesian optimization and embedded control. The approach has been demonstrated in experiments on a cold atmospheric plasma jet, with prototypical applications in plasma medicine.

Selective Spin-On Deposition of Polymers

Brief description not available

Magneto-Optic Modulator

Brief description not available

Light-Driven Ultrafast Electric Gating

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.  

Electric Ratchet Based Ion Pumps

UCI researchers developed a new device that uses electricity to drive ion separation across a membrane. This device can increase the energy efficiency of various applications such as artificial photosynthesis, water desalination, and chemical separations.

Diamond On Nanopatterned Substrates

UCLA researchers in the Department of Materials Science and Engineering have developed a nanofabrication method for improving the thermal properties of polycrystalline diamond films grown by chemical vapor deposition.

Selective Deposition Of Diamond In Thermal Vias

UCLA researchers in the Department of Materials Science & Engineering have developed a new method of diamond deposition in integrated circuit vias for thermal dissipation.

Controlled Homo-Epitaxial Growth Of Hybrid Halide Crystals

Organic-inorganic hybrid perovskites have demonstrated tremendous potential for next-generation electronic and optoelectronic devices due to their remarkable carrier dynamics. However, current studies of electronic and optoelectronic devices have been focused on polycrystalline materials, due to the challenges in synthesizing device compatible high quality single crystalline materials.

Photo-induced Metal Printing Technique for Creating Metal Patterns and Structures Under Room Temperature

UCLA researchers in the Department of Materials Science and Engineering have developed a low-temperature metal patterning technique.

Stroboscopic Universal Structure-Energy Flow Correlation Scattering Microscopy

Flexible semiconductors are far less costly, resource and energy intensive than conventional silicon production. Yet, as an unintended consequence of semiconductor printing, the films produced contain structural heterogeneities, or defects, which can limit their capacity to shuttle energy, or, information, over device-relevant scales. To be able to fully embrace this new, greener process, it is essential to elucidate which physical material properties most influence energy flow and which defects are most deleterious to efficient energy transport so that they can be targeted for elimination at the materials processing stage. Although some rather complex approaches have recently been used to track energy flow, the applicability of each one depends on specifics of the semiconductor properties (bandgap, excitonic vs charge carrier form of excitation, strong absorption or emission). Existing techniques cannot therefore be applied to a broad range of materials, and often necessitate adapting samples to fit the specific requirements of the technique. A broadly applicable approach is therefore needed to non-invasively and simultaneously reveal and correlate material morphology and energy flow patterns across many scales.    Researchers at the University of California, Berkeley have developed a new high-sensitivity, non-invasive, label-free, time-resolved optical scattering microscope able to map the flow of energy in any semiconductor, and correlate it in situ to the semiconductor morphology. This device has been shown as a far simpler approach to spatio-temporally characterize the flow of energy in either charge or exciton form, irrespective of the electronic properties of the material, and with few-nm precision. Furthermore, built into this approach is the unprecedented capability to perform in situ correlation to the underlying physical structure of the material. 

Mechanical Process For Creating Particles Using Two Plates

UCLA researchers in the Department of Chemistry and Biochemistry & Physics and Astronomy have developed a novel method to lithograph two polished solid surfaces by using a simple mechanical alignment jig with piezoelectric control and a method of pressing them together and solidifying a material.

Two-Step Processing With Vapor Treatment Of Thin Films Of Organic-Inorganic Perovskite Materials

Prof. Yang and colleagues have developed a novel method of preparing organic-inorganic thin films using a solution process followed by vapor treatment, presenting a low-cost, high-performance solution method of producing optoelectronic devices.

Trademark: Flexible Fan Out Wafer Processing And Structure: Flextrate

UCLA researchers in the Department of Electrical Engineering have invented a novel biocompatible flexible device fabrication method using fan-out wafer level processing (FOWLP).

High Performance and Flexible Chemical And Bio Sensors Using Metal Oxide Semiconductors

UCLA researchers in the Department of Materials Science and Engineering have developed a simple method producing thin, sensitive In2O3-based conformal biosensors based on field-effect transistors using facile solution-based processing for future wearable human technologies as well as non-invasive glucose testing.

Enhancing Photoluminescence Quantum Yield for High Performance Optoelectrics

Surface defects dominate the behavior of minority carriers in semiconductors and optoelectronic devices. Photoluminescence quantum yield (QY), which dictates efficiency of optoelectrics such as LEDs, lasers, and solar cells, is extremely low in materials with a large number of surface defects. Researchers at UC Berkeley and Lawrence Berkeley National Laboratory have developed a bis(trifluoromethane) sulfonamide (TFSI) solution for passivation/repair of surface defects in 2D transition metal dichalcogenide (TMDC). This air-stable solution-based chemical treatment provides unmatched photoluminescence QY enhancement to values near 100% without changing the surface morphology. The treatment eliminates defect-mediated non-radiative recombination, which eliminates the low performance limit of TMDC and enhances its minority carrier lifetime. This novel development can address surface passivation in numerous semiconductors which will lead to highly efficient light emitting diodes, lasers and solar cells based on 2D materials.

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