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Target biomarkers are often found at low levels (e.g., attomolar to picomolar scale) in the early stages of disease. Current biosensor technologies are limited by their ability to simply and precisely detect target biomarkers at very low concentrations though. Typical biomedical samples, like blood or urine, can also compromise the specificity and sensitivity of common diagnostic platforms without extensive sample processing to remove background contaminants. For example, there are 20,000 molecules in 30 𝜇L specimen (finger prick of blood) at 1 fM concentration, and 100 molecules is needed to get to a statistically meaningful measurement.

This e-nose sensor applies odorant receptor proteins fused to ion channels within a lipid bilayer, combined with semiconducting materials, to detect the binding of target molecules through changes in electrical conductance. Designed for sensitivity at the molecular level, it can identify a wide range of substances by mimicking the olfactory capabilities of living organisms.

      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. 

Engineers from UC San Diego have disclosed a new patent-pending technology (SHARP, VERTICALLY ALIGNED NANOWIRE ELECTRODE ARRAYS, HIGH-YIELD FABRICATION ANDINTRACELLULAR RECORDING) that minimizes the electrode size to an intracellular probe, and is scalable to integrate multiple channels at one platform and overcomes the previous disadvantages such as invasiveness and insensitivity. This newly disclosed improved technology reduces the number of steps and the number of metal layers used to increase the biocompatibility and device yield, as compared to an earlier disclosure for NEAs that were fabricated using a different process.

Scientists at UC Irvine have developed a sensitive, customizable, and user-friendly sensor for (1) strain detection as a result of cellular movement, (2) micro-fluidic device pressure detection, and (3) real-time monitoring of valve statuses in microfluidic chips. This research tool will provide new insights regarding cellular biophysics.

One of the key limitations for devices used in point-of-care diagnostics (POCD) is their limit of detection; patient samples used for POCD devices often contain too low of the target analyte. FlexThrough is a newly developed, centrifugal disk (CD)-based method that utilizes the entirety of a liquid sample via recirculation of the sample for efficient mixing as it iteratively passes through the system.

Researchers at UC Irvine have developed an optical detection system for SARS-CoV-2 and other pathogens that features improvements in screening time, cost, sensitivity, and practicality. As vaccine availability, economic pressure, and mental health considerations has gradually returned society to pre-pandemic activities that require frequent and close interactions, it is imperative that SARS-CoV-2 detection systems remain effective.

Optical chromatography (OC) is an optofluidic technique enabling label-free fractionation of microscopic particles, e.g., bioparticles from heterogenous mixtures. This technique relies on a laser beam along a microfluidic channel to create opposing optical scattering and fluidic drag forces. Variable strength and balance of these forces may be harnessed for selective sorting of bioparticles based on their size, composition, and morphology. OC has been successfully applied to fractionation of blood components such as human erythrocytes, monocytes, granulocytes, and lymphocytes. OC offers unique capabilities as a modern separation technique, especially when combined with multi-stage sequential fractionation and microfluidic network-based purification approaches, and it particularly excels in distinguishing bioparticles with subtle differences. However, there are several key limitations with OC being widely adopted. In order to create strong optical scattering forces along the microfluidic channels, expensive and sophisticated laser sources must be precisely aligned along the fluidic channel with a well-controlled beam waist profile, requiring a complicated optical alignment procedure that employs multiple multi-axis positioners. While microfluidic approaches using OC hold promise for broader use, multiplexed and high throughput systems remain overly complicated and cost-prohibitive.

Measurement of electrical activity in nervous tissue has many applications in medicine, but the implantation of a large number of sensors is traditionally very risky and costly. Devices must be large due to their necessary complexity and power requirements, driving up the risk further and discouraging adoption. To address these problems, researchers at UC Berkeley have developed devices and methods to allow small, very simple and power-efficient sensors to transmit information by backscatter feedback. That is, a much more complex and powerful external interrogator sends an electromagnetic or ultrasound signal, which is modulated by the sensor nodes and reflected back to the interrogator. Machine learning algorithms are then able to map the reflected signals to nervous activity. The asymmetric nature of this process allows most of the complexity to be offloaded to the external interrogator, which is not subject to the same constraints as implanted devices. This allows for larger networks of nodes which can generate higher resolution data at lower risks and costs than existing devices.

Cardiovascular disease is among the leading causes of death for citizens in affluent nations, and the most significant cause of morbidity in those with cardiovascular disease is hypertension. Often called the “silent killer” because it has few clinical signs in its early stages, elevated blood pressure is often in an advanced stage before it is treated, leading to a substantially worse prognosis than if it had been detected earlier.In order to address this problem, researchers at UC Berkeley have developed a wearable device which continuously monitors diastolic blood pressure, transmitting data to a portable device such as a cell phone, where it can be stored and analyzed. The device utilizes piezoelectric transducers to perform the measurement, which allows the wearable device to remain small while containing a large number of sensors in order to reduce noise.

A fundamental limitation for the implantable brain-machine interfaces (BMI) is the wiring requirements for power transfer and signal transmission. Microelectrode arrays (MEAs), the workhorse technology in neuroscience, offer multiplexed electrophysiological recordings with high temporal resolution. However, their use is inherently limited to a few hundred electrodes as direct electronic measurements suffer from complex wiring requirements and inherent bandwidth (spatial multiplexing) limitations due to electron-electron interactions within conductors. Moreover, electrode arrays can only record from small sections of the brain and require invasive cranial surgical operations. The recent discovery of genetically encoded voltage sensitive fluorescence indicators (GEVI) has created tremendous excitement as light offers unparalleled multiplexing and information carrying capabilities. However, GEVI cannot be used in humans as it requires expression of voltage sensitive molecules by neurons and therefore genetic manipulation. In addition, attenuation of visible light in biological tissue renders much of the brain inaccessable to fluorescence based techniques.  

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The inventors have developed a scalable laser aperture that emits light perpendicular to the surface. The aperture can, in principal, scale to arbitrarily large sizes, offering a universal architecture for systems in need of small, intermediate, or high power. The technology is based on photonic crystal apertures, nanostructured apertures that exhibit a quasi-linear dispersion at the center of the Brillouin zone together with a mode-dependent loss controlled by the cavity boundaries, modes, and crystal truncation. Open Dirac cavities protect the fundamental mode and couple higher order modes to lossy bands of the photonic structure. The technology was developed with an open-Dirac electromagnetic aperture, known as a Berkeley Surface Emitting Laser (BKSEL).  The inventors demonstrate a subtle cavity-mode-dependent scaling of losses. For cavities with a quadratic dispersion, detuned from the Dirac singularity, the complex frequencies converge towards each other based on cavity size. While the convergence of the real parts of cavity modes towards each other is delayed, going quickly to zero, the normalized complex free-spectral range converge towards a constant solely governed by the loss rate of Bloch bands. The inventors show that this unique scaling of the complex frequency of cavity modes in open-Dirac electromagnetic apertures guarantees single-mode operation of large cavities. The technology demonstrates scaled up single-mode lasing, and confirmed from far-field measurements. By eliminating limits on electromagnetic aperture size, the technology will enable groundbreaking applications for devices of all sizes, operating at any power level. BACKGROUND Single aperture cavities are bounded by higher order transverse modes, fundamentally limiting the power emitted by single-mode lasers, as well as the brightness of quantum light sources. Electromagnetic apertures support cavity modes that rapidly become arbitrarily close with the size of the aperture. The free-spectral range of existing electromagnetic apertures goes to zero when the size of the aperture increases. As a result, scale-invariant apertures or lasers has remained elusive until now.  Surface-emitting lasers have advantages in scalability over commercially widespread vertical-cavity surface-emitting lasers (VCSELs). When a photonic crystal is truncated to a finite cavity, the continuous bands break up into discrete cavity modes. These higher order modes compete with the fundamental lasing mode and the device becomes more susceptible to multimode lasing response as the cavity size increases. 

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Researchers at the University of California, Irvine have fabricated a flexible and unobtrusive wearable electrode that can detect glucose at a very low limit of detection.In fact, the detection limits are the lowest ever reported for an enzyme-free sensor. This sensor is applicable for detecting glucose levels in saliva, sweat or tears, and can safely be used at home, especially by diabetic patients without the need to frequently draw blood.

Researchers from the University of California, Irvine have developed a new method and device to efficiently mix and analyze liquid samples on CD-based point of care devices.

Prof. Nosang Myung and colleagues from the University of California, Riverside have developed state-of-the-art gas sensors that may be used to create an electronic nose. This device is known as ChromaNose. ChromaNose is capable of sensing carbon monoxide, hydrogen sulfide, hydrogen gas, oxygen gas, nitrogen dioxide, and ammonia at room temperature. This technology may be used in various applications to detect harmful chemicals that people cannot see or smell. For example, ChromaNose may detect cleaning solvent residue left in masks worn by Air Force personnel. The inhalation of cleaning solvent residue causes the wearer to become ill. It would be desirable to detect and remove any cleaning solvents remaining in a mask to prevent illness. Fig 1: Image of the UCR Pt/SnO2/SWNT hybrid nanostructure sensors.