In a paper published online July 4 in Nature Nanotechnology, a team led by University of Washington scientists reported the design of an energy-efficient, silicon-based non-volatile switch that manipulates light through the use of a phase-change material and graphene heater. The exceptional performance of their switch could help advance both information technology and quantum computing.
Jim De Yoreo, a Battelle fellow at Pacific Northwest National Laboratory and a UW affiliate professor of chemistry and materials science & engineering, has been nationally recognized as a scientific leader who forges partnerships between national laboratories and universities. Through advanced microscopy techniques, De Yoreo has spent his career trying to understand and predict the behavior of materials. For example, his team has determined the patterns that proteins form on a mineral surface, laying the groundwork for new strategies for synthesizing semiconductor and metallic nanoparticle circuits for photovoltaic or energy storage applications.
A team led by NanoES faculty member and UW ECE Professor Mo Li has developed a way of using sound waves to move subatomic quasiparticles known as ‘excitons’ further than ever before — leading to a faster, more energy-efficient computing circuit.
The Institute for Nano-engineered Systems (NanoES) has awarded four seed grants to researchers at Washington (UW) and Western Washington University to use nanotechnology tools to develop new, innovative technologies and devices. Awardees will receive up to $10,000 to carry out work in the UW’s Washington Nanofabrication Facility (WNF) and Molecular Analysis Facility (MAF).
Three UW researchers, including NanoES faculty member Vikram Iyer, are exploring ways to make electronics more Earth-friendly.
Researchers have discovered that light — from a laser — can trigger a form of magnetism in a normally nonmagnetic material. This magnetism centers on the behavior of electrons “spins,” which have a potential applications in quantum computing. Scientists discovered that electrons within the material became oriented in the same direction when illuminated by photons from a laser. By controlling and aligning electron spins at this level of detail and accuracy, this platform could have applications in quantum computing, quantum simulation and other fields. The experiment, led by scientists at the University of Washington, the University of Hong Kong and the Pacific Northwest National Laboratory, was published April 20 in Nature.
Bubbles for toughness? ME and A&A researchers, including NanoES faculty member Lucas Meza, are collaborating to investigate and advance nanofoams, a new tiny but mighty material.
Scientists at the University of Washington (UW) have recently developed a new nanoparticle-based drug delivery system that simultaneously delivers chemo- and immune- therapeutics directly to the tumor site, limiting harmful off-target side effects. In a paper published last November in Materials Today, they reported that their multifunctional nanoparticle can inhibit tumor growth and spread, also known as metastasis, in mouse models of triple negative breast cancer (TNBC), an exceptionally aggressive form of breast cancer with limited treatment options.
Researchers at the University of Washington have developed a new test for COVID-19 that combines the speed of over-the-counter antigen tests with the accuracy of PCR tests that are processed in medical labs and hospitals. The Harmony COVID-19 test is a diagnostic test that, like PCR tests for COVID-19, detects genetic material from the SARS-CoV-2 virus. But whereas conventional PCR tests can take several hours, the Harmony kit can provide results in less than 20 minutes for some samples and with similar accuracy.
UW ECE and Physics Professor Mo Li and his research team have developed a way to use stray photons generated by optical computing lasers (“noise”) to help enhance the creativity of artificial intelligence. This line of research holds huge potential for computing speed and efficiency, as well as the promise of reducing environmental impacts of AI and machine learning.