Impact of Viscous Droplets on Superamphiphobic Surfaces

The impact of a liquid droplet on a solid surface is one of the most common phenomena in nature and frequently encountered in numerous technological processes. Despite the significant progress on understanding the droplet impact phenomenon over the past century, the impact dynamics, especially the coupling effects between the properties of a liquid and surface wettability on the impact process, is still poorly understood. In this work, we experimentally investigated the impact of viscous droplets on superamphiphobic surfaces, with the viscosity of liquids ranging from 0.89 to 150 mPa s. We showed that an increase in liquid viscosity will slow down the impact process and cause bouncing droplets to rebound lower and fewer times. The critical impact velocity, above which droplets can rebound from the superamphiphobic surface, was found to linearly increase with the liquid viscosity. We also showed that the maximum spreading factor increases with Weber number or Reynolds number but decreases with the liquid viscosity. Scaling analyses based on energy conservation were carried out to explain these findings, and they were found to be in good agreement with our experimental results

Size-Dependent Stiffness of Nanodroplets: A Quantitative Analysis of the Interaction between an AFM Probe and Nanodroplets

The interfacial properties of nanodroplets are very significant for the exploration of the basic law governing the fluid behavior at the nanoscale and also the applications in some important processes in novel materials fabrication by forming a special and local reaction environment. However, many basic factors such as the interfacial tension or stiffness of nanodroplets are still lacking, partially because of the difficulty of making quantitative measurements of the interfacial interactions at the nanometer scale. Here, we used a novel atomic force microscopy (AFM) mode, PeakForce mode, to control the interaction between an AFM probe and nanodroplets, by which we could obtain the morphology and stiffness of nanodroplets simultaneously. The change in the stiffness with the size of the nanodroplets was observed where the smaller nanodroplets usually had a larger stiffness. To explain this phenomenon, we then established a theoretical model based on the Young–Laplace equation in which the deformation and size-dependent stiffness could be described quantitatively and the experimental observations could be explained with our numerical calculations very well. The general methodology presented here could also be extended to analyze the relevant behavior of nanobubbles and other wetting phenomena at the nanoscale

Table_1_Epidemiological trend in scarlet fever incidence in China during the COVID-19 pandemic: A time series analysis.DOCX

ObjectiveOver the past decade, scarlet fever has caused a relatively high economic burden in various regions of China. Non-pharmaceutical interventions (NPIs) are necessary because of the absence of vaccines and specific drugs. This study aimed to characterize the demographics of patients with scarlet fever, describe its spatiotemporal distribution, and explore the impact of NPIs on the disease in the era of coronavirus disease 2019 (COVID-19) in China.MethodsUsing monthly scarlet fever data from January 2011 to December 2019, seasonal autoregressive integrated moving average (SARIMA), advanced innovation state-space modeling framework that combines Box-Cox transformations, Fourier series with time-varying coefficients, and autoregressive moving average error correction method (TBATS) models were developed to select the best model for comparing between the expected and actual incidence of scarlet fever in 2020. Interrupted time series analysis (ITSA) was used to explore whether NPIs have an effect on scarlet fever incidence, while the intervention effects of specific NPIs were explored using correlation analysis and ridge regression methods.ResultsFrom 2011 to 2017, the total number of scarlet fever cases was 400,691, with children aged 0–9 years being the main group affected. There were two annual incidence peaks (May to June and November to December). According to the best prediction model TBATS (0.002, {0, 0}, 0.801, {}), the number of scarlet fever cases was 72,148 and dual seasonality was no longer prominent. ITSA showed a significant effect of NPIs of a reduction in the number of scarlet fever episodes (β2 = −61526, P ConclusionsThe incidence of scarlet fever during COVID-19 was lower than expected, and the total incidence decreased by 80.74% in 2020. The results of this study indicate that strict NPIs may be of potential benefit in preventing scarlet fever occurrence, especially that related to public event cancellation. However, it is still important that vaccines and drugs are available in the future.</p