Electrochemical devices have the potential to pose powerful solutions in addressing rising energy demands and counteracting environmental problems. However, currently, these devices suffer from meager performance due to poor efficiency and durability of the catalysts. These suboptimal characteristics have hampered widespread commercialization. Here we report on Pt(57.5)Cu(14.7)Ni(5.3)P(22.5) bulk metallic glass (Pt-BMG) nanowires, whose novel architecture and outstanding durability circumvent the performance problems of electrochemical devices. We fabricate Pt-BMG nanowires using a facile and scalable nanoimprinting approach to create dealloyed high surface area nanowire catalysts with high conductivity and activity for methanol and ethanol oxidation. After 1000 cycles, these nanowires maintain 96% of their performance-2.4 times as much as conventional Pt/C catalysts. Their properties make them ideal candidates for widespread commercial use such as for energy conversion/storage and sensors.

The identification of multicomponent alloys out of a vast compositional space is a daunting task, especially for bulk metallic glasses composed of three or more elements. Despite an increasing theoretical understanding of glass formation, bulk metallic glasses are predominantly developed through a sequential and time-consuming trial-and-error approach. Even for binary systems, accurate quantum mechanical approaches are still many orders of magnitude away from being able to simulate the relatively slow kinetics of glass formation. Here, we present a high-throughput strategy where ∼3,000 alloy compositions are fabricated simultaneously and characterized for thermoplastic formability through parallel blow forming. Using this approach, we identified the composition with the highest thermoplastic formability in the glass-forming system Mg-Cu-Y. The method provides a versatile toolbox for unveiling complex correlations of material properties and glass formation, and should facilitate a drastic increase in the discovery rate of metallic glasses.

No abstract

The current pandemic of the coronavirus disease (COVID-19) has highlighted the importance of rapid control of the transmission of infectious diseases. This is particularly important for COVID-19, where many individuals are asymptomatic or have only mild symptoms but can still spread the disease. Current systems for controlling transmission rely on patients to report their symptoms to medical professionals and be able to recall and trace all their contacts from the previous few days. This is unrealistic in the modern world. However, existing smartphone-based GPS and social media technology may provide a suitable alternative. We, therefore, developed a mini-program within the app WeChat. This analyzes data from all users and traces close contacts of all patients. This permits early tracing and quarantine of potential sources of infection. Data from the mini-program can also be merged with other data to predict epidemic trends, calculate individual and population risks, and provide recommendations for individual and population protection action. It may also improve our understanding of how the disease spreads. However, there are a number of unresolved questions about the use of smartphone data for health surveillance, including how to protect individual privacy and provide safeguards against data breaches.