Ever-increasing global demand for efficient and durable information exchange has created a race to develop next-generation technology platforms. Powered by an ability to design and fabricate circuits, detectors, and actuators at the nanometer scale, CNSI researchers are breaking new ground in the creation of fast, flexible, and scalable electronic devices toward applications ranging from bio/electro/chemical sensors and neuromorphic computing to high-speed multimodal imaging and lens-free microscopy platforms for telemedicine.
The concept of flexible electronic devices has long been the domain of science fiction. Researchers at CNSI are making that vision a reality by developing new materials that enable vastly more powerful and sensitive medical devices, display technologies, computer-interfaces, solar cells and wearable devices. Efforts like those led by Xiangfeng Duan, whose team leverages the increased efficiency and capability of layered semiconductors to fabricate field effect transistors made from two-dimensional materials that are just a few atoms thick, have demonstrated performance improvements of nearly 40-50 times over conventional approaches.
Increasing the number of circuit elements, especially transistors, in electronic devices leads to the dramatic improvements in performance and efficiency that power our digital world. Teams of researchers at CNSI, like the one led by Yang Yang, aim to develop high performance electronic materials and devices. Yang’s group develops high-performance, solution-processed oxide thin film transistors through material and device engineering. Approaches like these make the promise of printable high-speed electronic devices such as displays, sensors and logic circuits a future reality.
Enzyme-linked immunosorbant assay, or ELISA, is a diagnostic tool that identifies antigens in blood samples such as HIV, West Nile virus, and hepatitis B. A team led by Dr. Aydogan Ozcan has developed a new mobile phone-based device that can read ELISA plates in the field with the same level of accuracy as the large machines normally found in clinical laboratories. The body of the device is created with a 3D printer and attaches to a smartphone, which transmits the ELISA images to UCLA servers through a custom-designed app. Images are analyzed and the diagnostic results are sent back to the phone within approximately one minute.
As computational tasks become increasingly difficult in a world of big data, systems to address modern challenges in collection, processing, and analysis of large datasets are increasingly necessary. Researchers at CNSI are attacking the challenges of next-generation computing by combining concepts of neuroscience and machine learning with nanoscale materials. An exemplar of this approach are James Gimzewski and Adam Stieg, who are developing complex nanoarchitectures that have structural similarity to neocortex and exhibit properties which make them an ideal platform to addresses the difficulty of mimicking biological neural networks in artificial computing environments.
Research News – Beyond CMOS
Understanding the possible quantum-driven behaviors of biological systems could aid in treating injuries or in developing cures for diseases, but research in the field has been pushed to the sidelines. It’s time for that to change.
Two members of the California NanoSystems Institute at UCLA are working together to understand the incredibly fast interactions between particles that take place at infinitesimally tiny scales. Professors Prineha “Pri” Narang and Sergio Carbajo aim to harness their findings by developing technology for taking measurements with previously impossible levels of sensitivity.
An international research collaboration led by UCLA has developed a way to use perovskite in solar cells while protecting it from the conditions that cause it to deteriorate. In a study published in Nature Materials, the scientists added small quantities of ions — electrically charged atoms — of a metal called neodymium directly to perovskite.
December 8, 2022 | 3D-printed decoder, AI-enabled image compression could enable higher-res displays
A UCLA team has developed a technology for projecting high-resolution computer-generated images using one-sixteenth the number of pixels contained in their source images. The system compresses images based on an artificial intelligence algorithm, and then decodes them using an optical decoder — a thin, translucent sheet of plastic produced using a 3D printer — that is designed to interact with light in a specific way as part of the same algorithm.
March 15, 2022 | UCLA Materials Scientists Lead Global Team in Finding Solutions to Biggest Hurdle for Solar Cell Technology
Materials scientists at the UCLA Samueli School of Engineering and colleagues from five other universities around the world have discovered the major reason why perovskite solar cells — which show great promise for improved energy-conversion efficiency — degrade in sunlight, causing their performance to suffer over time. The team successfully demonstrated a simple manufacturing adjustment to fix the cause of the degradation, clearing the biggest hurdle toward the widespread adoption of the thin-film solar cell technology.
February 7, 2022 | Sweating the small stuff: Smartwatch developed at UCLA measures key stress hormone
Now, a UCLA research team has developed a device that could be a major step forward: a smartwatch that assesses cortisol levels found in sweat — accurately, noninvasively and in real time. Described in a study published in Science Advances, the technology could offer wearers the ability to read and react to an essential biochemical indicator of stress.