Researchers at the University of California, Davis have developed a technology that introduces a novel approach to hardware security using photonic physically unclonable functions for true random number generation and biometric ID.

Researchers at the University of California, Davis, have developed a novel imaging system that improves the diagnostic accuracy of PET imaging. The system combines machine learning and computed tomography (CT) imaging to reduce noise and enhance resolution. This novel technique can integrate with commercial PET imaging systems, improving diagnostic accuracy and facilitating superior treatment of various diseases.

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

Researchers at the University of California, Davis, have developed a memory system that uses optical interconnects.

Researchers at the University of California, Davis have developed an optical lens module that uses a metalens or a metalens array having a controllable angular field-of-view.

      Biologics are antibodies produced by genetically engineered cells and are widely used in therapeutic applications. Examples include pembrolizumab (Keytruda) and atezolizumab (Tecentriq), both employed in cancer immunotherapy as checkpoint inhibitors to restore T- cell immune responses against tumor cells. These biologics are produced by engineered cells in bioreactors in a process that is highly sensitive to the bioreactor environment, making it essential to integrate process analytical technologies (PAT) for closed-loop, real-time adjustments. Recent trends have focused on leveraging integrated circuit (IC) solutions for system miniaturization and enhanced functionality, for example enabling a single IC that monitors O2, pH, oxidation-reduction potential (ORP), temperature, and glucose levels. However, no current technology can directly and continuously quantify the concentration and quality of the produced biologics in real-time within the bioreactor. Such critical measurements still rely on off-line methods such as immunoassays and mass spectrometry, which are time-consuming and not suitable for real- time process control.       UC Berkeley researchers have developed a microsystem for real-time, in-vivo monitoring of antibody therapeutics using structure-switching aptamers by employing an integrator-based readout front-end. This approach effectively addresses the challenge of a 100× reduction in signal levels compared to the measurement of small-molecule drugs in prior works. The microsystem is also uniquely suited to the emerging paradigm of “living pharmacies.” In living pharmacies, drug-producing cells will be hosted on implantable devices, and real-time monitoring of drug production/diffusion rates based on an individual’s pharmokinetics will be crucial.

      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.

      Molecular dynamics (MD) is a computational materials science modality widely used in academic and industrial settings for materials discovery and more. A critical aspect of modern MD calculations are machine learning interatomic potentials (MLIPs), which learn from reference quantum mechanical calculations and predict the energy and forces of atomic configurations quickly. MLIPs allow for more accurate and comprehensive exploration of material/molecular properties at-scale. However, state-of-the-art MLIP methods mostly use a short-range approximation, which may be sufficient for describing properties of homogeneous bulk systems but fail for liquid-vapor interfaces, dielectric response, dilute ionic solutions with Debye-Huckel screening, and interactions between gas phase molecules. Short-range MLIPs neglect all long-range interactions, such as Coulomb and dispersion interactions.      To address the current shortcoming, UC Berkeley researchers have developed a straightforward and efficient algorithm to account for long-range interactions in MLIPs. The algorithm can predict system properties including those with charged, polar or apolar molecular dimers, bulk water, and water-vapor interfaces. In these cases standard short-range MLIPs lead to unphysical predictions, even when utilizing message passing algorithms. The present method eliminates artifacts while only about doubling the computational cost. Furthermore, it can be incorporated into most existing MLIP architectures, including potentials based on local atomic environments such as HDNPP, Gaussian Approximation Potentials (GAP), Moment Tensor Potentials (MTPs), atomic cluster expansion (ACE), and MPNN (e.g., NequIP, MACE).

Researchers at UC Irvine have developed a novel system leveraging dielectrophoresis through nanoelectrodes for precise manipulation of nano-scale polarizable objects.

      Quantum sensing is rapidly reshaping our ability to discern chemical processes with high sensitivity and spatial resolution. Many quantum sensors are based on nitrogen-vacancy (NV) centers in diamond, with nanodiamonds (NDs) providing a promising approach to chemical quantum sensing compared to single crystals for benefits in cost, deployability, and facile integration with the analyte. However, high-precision chemical quantum sensing suffers from large statistical errors from particle heterogeneity, fluorescence fluctuations related to particle orientation, and other unresolved challenges.      To overcome these obstacles, UC Berkeley researchers have developed a novel microfluidic chemical quantum sensing device capable of high-precision, background-free quantum sensing at high-throughput. The microfluidic device solves problems with heterogeneity while simultaneously ensuring close interaction with the analyte. The device further yields exceptional measurement stability, which has been demonstrated over >103s measurement and across ~105 droplets.  Greatly surpassing the stability seen in conventional quantum sensing experiments, these properties are also resistant to experimental variations and temperature shifts. Finally, the required ND sensor volumes are minuscule, costing only about $0.63 for an hour of analysis. 

Researchers at the University of California, Davis have developed a device for multi-dimensional data extraction at the molecular level to allow one to simultaneously detect the presence of a single-molecule electrically, and to extract a chemical fingerprint to identify that molecule optically.

Researchers at the University of California, Davis have developed layered 2D MoS2 nanostructures that have their light-interactive properties improved by intercalation with transition and post-transition metal atoms, specifically Copper and Tin.

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         Positron emission tomography (PET) is a powerful tool both in biomedical research and clinical patient care, particularly in the diagnosis of cancer, search for metastases, cancer treatment monitoring, diagnosis of diffuse diseases causing dementia, or metabolic blood flow imaging. However, the poor efficiency of current PET detectors (1-2%) requires large radiotracer doses and integration times, driving both cost and patient exposure per scan. High detector capital cost also renders PET scanners prohibitively expensive. Finally, while time-of-flight PET can enhance the spatial resolution of PET by measuring temporal correlation of detected gamma photons, the modality is limited by the latency of current gamma radiation detectors (timing resolutions of ~200-500 ps). Overall, the expense and inefficiency of available gamma radiation detectors hinder the full technological capabilities of PET and its affordable use in patient care.         To address these problems, researchers at UC Berkeley have developed a new gamma radiation detector architecture with the potential for an order of magnitude improvement in both time resolution (down to 10 ps) and efficiency. The design uses novel perovskite nanomaterials and well-established nanotechnology manufacturing methods to produce a detector at a fraction of the cost of current offerings. Together, the high efficiency and timing resolution of the nanophotonic detector design should drastically improve the spatial resolution (including by time-of-flight measurements) of PET scanners and dose-suitability for elderly patients. Benefits in affordability are multiple, lowering detector cost and as well as required radiotracer dose.

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Researchers at the University of California, Davis have developed a single-use chip for the identification of protein crystals using X-ray based instruments.

Researchers at the University of California, Davis have developed a nanolaser platform built from materials that do not exhibit optical gain.

Researchers at the University of California, Davis have developed a nanophotonic-based platform for signal processing and optical computing in algorithm-based neural networks that is faster and more energy-efficient than current technologies.

UCLA researchers in the Department of Chemistry and Biochemistry have developed a photolithographic method for the high-throughput, parallel production of microscale and nanoscale objects with tailored shapes and dimensions using a single photomask.

Researchers led by Paul Weiss from the Department of Chemistry and Biochemistry at UCLA have developed a novel technique that solves the scalability issue in the fabrication of three-dimensional nanostructures.

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UCLA researchers in the department of Electrical Engineering have developed a novel magetoelectric device for use as a spin transistor.

A bioconjugation method to covalently link molecular entities to polypeptides such as antibodies using a simple one-pot process.

Researchers at the University of California, Davis have developed an active nanoplatform (F/HAPIN) for cancer diagnosis and therapy.

Medical devices are susceptible to contamination by harmful microbes, such as bacteria and fungi, which form biofilms on device surfaces. These biofilms are often resistant to antibiotics and other current treatments, resulting in over 2 million people per year suffering from diseases related to these contaminating microbes. Death rates for many of these diseases are high, often exceeding 50%. Researchers at UCI have developed a novel anti-bacterial and anti-fungal biocomposite that incorporates a nanopillared surface structure that can be applied as a coating to medical devices.