Upon shearing a microscale lithographically defined graphite mesa, the sheared section retracts spontaneously to minimize interface energy. Here, we demonstrate a sixfold symmetry of the ...self-retraction and provide a first experimental estimate of the frictional force involved, as direct evidence that the self-retraction is due to superlubricity, where ultralow friction occurs between incommensurate surfaces. The effect is remarkable because it occurs reproducibly under ambient conditions and over a contact area of up to 10×10 μm2, more than 7 orders of magnitude larger than previous scanning-probe-based studies of superlubricity in graphite. By analyzing the sheared interface, we show how the grain structure of highly oriented pyrolitic graphite determines the probability of self-retraction. Our results demonstrate that such self-retraction provides a novel probe of superlubricity, and the robustness of the phenomenon opens the way for practical applications of superlubricity in micromechanical systems.
Recent experiments on microscopic graphite mesas demonstrate reproducible high-speed microscale superlubricity, even under ambient conditions. Here, we explore the same phenomenon on the nanoscale, ...by studying a graphene flake sliding on a graphite substrate, using molecular dynamics. We show that superlubricity is punctuated by high-friction transients as the flake rotates through successive crystallographic alignments with the substrate. Further, we introduce two novel routes to suppress frictional scattering and achieve persistent superlubricity. We use graphitic nanoribbons to eliminate frictional scattering by constraining the flake rotation, an approach we call frictional waveguides. We can also effectively suppress frictional scattering by biaxial stretching of the graphitic substrate. These new routes to persistent superlubricity at the nanoscale may guide the design of ultra-low dissipation nanomechanical devices.
Making small liquid droplets move spontaneously on solid surfaces is a key challenge in lab-on-chip and heat exchanger technologies. Here, we report that a substrate curvature gradient can accelerate ...micro- and nanodroplets to high speeds on both hydrophilic and hydrophobic substrates. Experiments for microscale water droplets on tapered surfaces show a maximum speed of 0.42 m/s, 2 orders of magnitude higher than with a wettability gradient. We show that the total free energy and driving force exerted on a droplet are determined by the substrate curvature and substrate curvature gradient, respectively. Using molecular dynamics simulations, we predict nanoscale droplets moving spontaneously at over 100 m/s on tapered surfaces.
A sheared microscopic graphite mesa retracts spontaneously to minimize interfacial energy. Using an optical knife-edge technique, we report first measurements of the speeds of such self-retracting ...motion (SRM) from the mm/s range at room temperature to 25 m/s at 235°C corrected. This remarkably high speed is comparable with the upper theoretical limit found for sliding interfaces exhibiting structural superlubricity. We observe a strong temperature dependence of SRM speed which is consistent with a thermally activated mechanism of translational motion that involves successive pinning and depinning events at interfacial defects. The activation energy for depinning is estimated to be 0.1-1 eV.
In this article, we introduce the Open17 Challenge, an online coaching programme, inspired by the 17 United Nations (UN) Sustainable Development Goals (SDGs). This challenge has occurred roughly once ...a year since 2015, when the UN launched the SDGs. It lasts five weeks and involves five two-hour online coaching sessions as well as homework for the participants between sessions. The objective of the challenge is to coach a team of students about how to apply citizen science tools and methodologies to generate open data relevant to the SDGs. The goal of the coaching is to help each team develop their idea to the stage where they can make a compelling pitch that involves crowdsourcing of citizen-generated data. The format of the challenge has evolved as the organizing institutions have learned from each edition and improved iteratively. The purpose of this article is to describe the evolving methodology of the Open17 Challenge in the context of challenge-based learning (CBL) and more specifically discuss its relevance to e-learning. In particular, we analyse the potential of this methodology to generate new citizen science projects on issues relevant to the SDGs, with a view to enabling other organizations to adapt and apply this approach to specific SDG-related challenges.
The emergence of the field of nanofluidics in the last decade has led to the development of important applications including water desalination, ultrafiltration and osmotic energy conversion. Most ...applications make use of carbon nanotubes, boron nitride nanotubes, graphene and graphene oxide. In particular, understanding water transport in carbon nanotubes is key for designing ultrafiltration devices and energy-efficient water filters. However, although theoretical studies based on molecular dynamics simulations have revealed many mechanistic features of water transport at the molecular level, further advances in this direction are limited by the fact that the lowest flow velocities accessible by simulations are orders of magnitude higher than those measured experimentally. Here, we extend molecular dynamics studies of water transport through carbon nanotubes to flow velocities comparable with experimental ones using massive crowd-sourced computing power. We observe previously undetected oscillations in the friction force between water and carbon nanotubes and show that these oscillations result from the coupling between confined water molecules and the longitudinal phonon modes of the nanotube. This coupling can enhance the diffusion of confined water by more than 300%. Our results may serve as a theoretical framework for the design of new devices for more efficient water filtration and osmotic energy conversion devices.
Citizen scientists around the world are collecting data with their smartphones, performing scientific calculations on their home computers, and analyzing images on online platforms. These online ...citizen science projects are frequently lauded for their potential to revolutionize the scope and scale of data collection and analysis, improve scientific literacy, and democratize science. Yet, despite the attention online citizen science has attracted, it remains unclear how widespread public participation is, how it has changed over time, and how it is geographically distributed. Importantly, the demographic profile of citizen science participants remains uncertain, and thus to what extent their contributions are helping to democratize science. Here, we present the largest quantitative study of participation in citizen science based on online accounts of more than 14 million participants over two decades. We find that the trend of broad rapid growth in online citizen science participation observed in the early 2000s has since diverged by mode of participation, with consistent growth observed in nature sensing, but a decline seen in crowdsourcing and distributed computing. Most citizen science projects, except for nature sensing, are heavily dominated by men, and the vast majority of participants, male and female, have a background in science. The analysis we present here provides, for the first time, a robust 'baseline' to describe global trends in online citizen science participation. These results highlight current challenges and the future potential of citizen science. Beyond presenting our analysis of the collated data, our work identifies multiple metrics for robust examination of public participation in science and, more generally, online crowds. It also points to the limits of quantitative studies in capturing the personal, societal, and historical significance of citizen science.
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