Design and development of multilayer cotton masks via machine learning.

With the ongoing COVID-19 pandemic, reusable high-performance cloth masks are recommended for the public to minimize virus spread and alleviate the demand for disposable surgical masks. However, the approach to design a high-performance cotton mask is still unclear. In this study, we aimed to find out the relationship between fabric properties and mask performance via experimental design and machine learning. Our work is the first reported work of employing machine learning to develop protective face masks. Here, we analyzed the characteristics of Egyptian cotton (EC) fabrics with different thread counts and measured the efficacy of triple-layered masks with different layer combinations and stacking orders. The filtration efficiencies of the triple-layered masks were related to the cotton properties and the layer combination. Stacking EC fabrics in the order of thread count 100-300-100 provides the best particle filtration efficiency (45.4%) and bacterial filtration efficiency (98.1%). Furthermore, these key performance metrics were correctly predicted using machine-learning models based on the physical characteristics of the constituent EC layers using Lasso and XGBoost machine-learning models. Our work showed that the machine learning-based prediction approach can be generalized to other material design problems to improve the efficiency of product development.

Extended magnetic reconnection across the dayside magnetopause.

The extent of where magnetic reconnection (MR), the dominant process responsible for energy and plasma transport into the magnetosphere, operates across Earth's dayside magnetopause has previously been only indirectly shown by observations. We report the first direct evidence of X-line structure resulting from the operation of MR at each of two widely separated locations along the tilted, subsolar line of maximum current on Earth's magnetopause, confirming the operation of MR at two or more sites across the extended region where MR is expected to occur. The evidence results from in-situ observations of the associated ion and electron plasma distributions, present within each magnetic X-line structure, taken by two spacecraft passing through the active MR regions simultaneously.

Little or no solar wind enters Venus' atmosphere at solar minimum.

Venus has no significant internal magnetic field, which allows the solar wind to interact directly with its atmosphere. A field is induced in this interaction, which partially shields the atmosphere, but we have no knowledge of how effective that shield is at solar minimum. (Our current knowledge of the solar wind interaction with Venus is derived from measurements at solar maximum.) The bow shock is close to the planet, meaning that it is possible that some solar wind could be absorbed by the atmosphere and contribute to the evolution of the atmosphere. Here we report magnetic field measurements from the Venus Express spacecraft in the plasma environment surrounding Venus. The bow shock under low solar activity conditions seems to be in the position that would be expected from a complete deflection by a magnetized ionosphere. Therefore little solar wind enters the Venus ionosphere even at solar minimum.