Protein-based materials have the potential to change the current paradigm of materials science. However, it still remains a challenge to preserve protein hierarchical structure and function while making them readily processable. Protein structure is inherently fluid, and it is this property that contributes to their fragility outside of their native environment. Through the use of rationally designed statistically random heteropolymers, it is possible to stabilize proteins at each hierarchical level and process them in organic solvents, a common need for materials fabrication. The chemical and architectural complexities of statistically random heteropolymers provide a modular platform for tunable protein-polymer-solvent interactions. This provides opportunities not offered by small molecule surfactants or amphiphilic block copolymers. Through evaluation of horseradish peroxidase and green fluorescent protein structure, we show that statistically random heteropolymers can stabilize enzymes. Allowing for activity retention when stored in organic solvent, over 80% activity was observed after 24 hours. Furthermore, horseradish peroxidase and chymotrypsin proteins, when encapsulated in statistically random heteropolymers, are still accessible to their substrates while remaining inaccessible to the denaturing organic solvent. Statistically random heteropolymers have potential in creating stimuli-reponsive materials and nanoreactors composed of proteins and synthetic materials.

Researchers in the UCLA Department of Electrical and Computer Engineering have developed a Light Detection and Ranging (LiDAR) device capable of high resolution, high acquisition measurements with minimized walk error and adjustable detection quality.

UCLA researchers in the Department of Electrical and Computer Engineering have developed a Non-line-of-sight (NLOS) Imaging System using low cost thermal cameras that enable 3D recovery of NLOS heat source for imaging around corners.

UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a user-friendly analytical instrument that measures electrochemical impedance at rates many times faster than currently available devices and with comparable accuracy.

UCLA researchers in the Department of Bioengineering have developed a novel 3D printing method that produces customizable normal force sensors for robotic surgical applications at high speed and low cost.

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Researchers in UCLA's Department of Chemistry and Biochemistry have harnessed gel electrophoresis in order to direct and program controlled collisional reactions between pulse-like bands of molecules and/or colloidal reagent species.

UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed flexible tactile sensors for curved surfaces that are robust against fatigue and suitable for robotic applications.

UCI researchers developed a sturdy architecture and straightforward fabrication procedure for the core sensing element in microscale gyroscopes for timing and inertial navigation applications.

Rehabilitation therapy, while an important tool for the long term recovery of patients affected by brain injury or disease, is expensive and requires one-on-one attention from a certified healthcare professional. UCI researchers have developed a computer-based system that provides arm movement therapy for patients. The system allows patients to independently practice hand and arm movements, improving therapeutic outcomes, while reducing hospital visits and cost for both patients and healthcare providers.

Nanoscale multipoint structure-function analysis is essential for deciphering the complexity of multiscale physical and biological systems. Atomic force microscopy (AFM) allows nanoscale structure-function imaging in various operating environments and can be integrated seamlessly with disparate probe-based sensing and manipulation technologies. However, conventional AFMs only permit sequential single-point analysis. Widespread adoption of array AFMs for simultaneous multi-point study is still challenging due to the intrinsic limitations of existing technological approaches.

The number one cause of train derailments globally are unidentified track defects which accumulate over time under the heavy loads and weathering to which rail is exposed. For the last 100 years rail inspection has sought to identify these structural defects before they can pose a serious threat to regular rail traffic. Unfortunately, rail inspection has required specialized low-speed testing cars which can only operate at less than 25% the normal speed of a train. These inspection cars must coordinate their work around planned outages of the rail line, impacting normal rail traffic. Due to this inconvenience, rail defects are typically repaired in real-time, as identified, vs. being prioritized as to potential seriousness and repaired in order of likelihood to cause a future accident.

Piezoelectric sensors have long existed to monitor applied pressures between two objects. In large applications with malleable substrates or where low cost is key, individual piezoelectric sensors are not practical. A variety of applications exist where monitoring the pressure being applied to a soft surface would providing meaningful insights into the system or subject under observation. For instance, in a long-term care setting where patients need to be monitored for pressure ulcers, a bedding material that could sense the pressure points between a person’s body and the mattress could alert care givers that an adjustment in body position is warranted. Likewise, in a sports training application, a pressure sensitive boxing ring canvas could track a boxer’s footwork, or punching power and hand speed if applied to the inside of a punching bag.   Pressure sensitive soft toys could also benefit from feedback that might differ when a child scratches behind their stuffed animal’s ears vs. rubbing its belly.  To achieve discrete sensing in these applications, a low cost bulk sensing system is needed.

Microfluidic devices have long been touted as a powerful analytical tool with which to characterize a wide range of analytes, including particles, and cells. Despite the apparent convenience of microfluidic technologies for applications in healthcare, such devices often rely on capital-intensive optics and other peripheral equipment that limit throughput, perhaps because the majority of microfluidic devices operate using optics-based principles, which typically require high-speed or sensitive cameras, sophisticated confocal microscopes, vibration isolation tables, and laser excitation systems.

Hyperspectral imaging is a technique combining imaging and spectroscopy resulting in images with extraordinary precision and detail. Current approaches to capture hyperspectral images are costly and time-consuming. The proposed technique makes use of inexpensive filters and reduces the number of required exposures, thereby improving the efficiency and practicability of obtaining hyperspectral images.

The sensitivity of mobile atom interferometers for gravimetry, gradiometry and inertial sensing has been limited by a noise floor due to ground vibrations, as well as available free-fall space.    UC Berkeley researchers have developed an interferometer geometry that addresses both problems within an optical cavity. The utility of such a device lies primarily in its application as a mobile sensor, particularly for situations in the absence of a GPS signal (such as in deep-sea submarines, or in the event of a GPS system failure).  Similarly, sensing using gravitational signals has wide applicability. The configuration of this device accumulates an acceleration phase sensitive to low-frequency accelerations (i.e., gravity) while demonstrating an immunity to accelerations at higher frequencies than the held times (i.e., vibrations).

UCLA researchers in the Department of Electrical & Computer Engineering have invented a novel circuit design that performs high speed and reliable data reading operations for resistive device-based memory applications.

UCLA researchers in the Department of Electrical Engineering have developed a high-responsivity photodetector that utilizes metallo-graphene nanocomposites for superior detection of infrared wavelengths.

UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel wearable biosensor capable of measuring biomarkers in real time through biofluids like sweat.

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Researchers at the University of California, Davis have developed a method for measuring in-plane and out-of-plane surface magnetic properties of thin films.

Researchers at UCI have developed a non-intrusive method for building a virtual replica of manufacturing machine, which allows for accurate diagnostics of the state of the system. This provides manufacturers with real-time information on quality control and immediately identifies any malfunctions in the system.

Ice nucleating particles (INPs) suspended in the Earth’s atmosphere influence cloud properties and can affect the overall precipitation efficiency and predictability of cloud systems worldwide. INPs induce freezing of cloud droplets at temperatures above their normal freezing-point (~-38 C), and at a relative humidity (RH) below the normal freezing RH of aqueous solution droplets at lower temperatures. These INP induced variabilities influence cloud lifetime, phase, as well as cloud optical and microphysical properties. Developing a relational model of INPs in global climate models has proven challenging as existing instrumentation systems either require too much air volume (in real-time flow instruments) or exhibit too much temperature variability (in off-line frozen assay based instruments).  Thus, there is a real urgency to address this unmet need.

Researchers at UCI have developed a fully integrated sample mount for the simultaneous high-resolution imaging and electronic and optical characterization of thin film devices.

Optical spectroscopy excels at chemical identification and is ubiquitous in the sciences as a highly specific and noninvasive probe of molecular structure. The field is moving toward the integration of miniaturized optical spectrometers into mobile platforms which will have unprecedented impact on applications ranging from unmanned aerial vehicles (UAVs) to mobile phones. To address this demand, silicon photonics stands out as platform capable of delivering compact and cost-effective devices and systems. The Fourier transform spectrometer (FTS) is largely used in free-space spectroscopy, where its high signal throughput has proven a boon to overcoming the difficulties of otherwise overwhelming detector noise. Its implementation in silicon photonics manufacturing will contribute to bringing broadband operation and fine resolution to the chip scale enabling such attributes as compactness, power efficiency, real time operation and low cost.