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The epitaxial growth of SrTiO 3 on Si(100) substrates that have been lithographically patterned to realize deposition-last, lithographically defined oxide devices on Si is explored. In contrast to traditional deposition-last techniques which create a physical hard mask on top of the substrate prior to epitaxial growth, a pseudomask is instead created by texturing the Si substrate surface itself. The Si is textured through a combination of reactive ion etching and wet-etching using a tetramethylammonium hydroxide solution. Desorbing the native SiO x at high temperatures prior to epitaxial growth in ultrahigh vacuum presents no complications as the patterned substrate is comprised entirely of Si. The inverted profile in which the epitaxial oxide device layer is above the textured pseudomask circumvents shadowing during deposition associated with conventional hard masks, thereby opening a pathway for highly scaled devices to be created. 

Surface cleaning using commercial disinfectants, which has recently increased during the coronavirus disease 2019 pandemic, can generate secondary indoor pollutants both in gas and aerosol phases. It can also affect indoor air quality and health, especially for workers repeatedly exposed to disinfectants. Here, we cleaned the floor of a mechanically ventilated office room using a commercial cleaner while concurrently measuring gas-phase precursors, oxidants, radicals, secondary oxidation products, and aerosols in real time; these were detected within minutes after cleaner application. During cleaning, indoor monoterpene concentrations exceeded outdoor concentrations by two orders of magnitude, increasing the rate of ozonolysis under low (<10 ppb) ozone levels. High number concentrations of freshly nucleated sub–10-nm particles (≥105 cm−3) resulted in respiratory tract deposited dose rates comparable to or exceeding that of inhalation of vehicle-associated aerosols. 

Pure spin currents can be generated via thermal excitations of magnons. These magnon spin currents serve as carriers of information in insulating materials, and controlling them using electrical means may enable energy efficient information processing. Here, we demonstrate electric field control of magnon spin currents in the antiferromagnetic insulator Cr 2 O 3 . We show that the thermally driven magnon spin currents reveal a spin-flop transition in thin-film Cr 2 O 3 . Crucially, this spin-flop can be turned on or off by applying an electric field across the thickness of the film. Using this tunability, we demonstrate electric field–induced switching of the polarization of magnon spin currents by varying only a gate voltage while at a fixed magnetic field. We propose a model considering an electric field–dependent spin-flop transition, arising from a change in sublattice magnetizations via a magnetoelectric coupling. These results provide a different approach toward controlling magnon spin current in antiferromagnets. 

Abstract The dispersive sweep of fast radio bursts (FRBs) has been used to probe the ionized baryon content of the intergalactic medium 1 , which is assumed to dominate the total extragalactic dispersion. Although the host-galaxy contributions to the dispersion measure appear to be small for most FRBs 2 , in at least one case there is evidence for an extreme magneto-ionic local environment 3,4 and a compact persistent radio source 5 . Here we report the detection and localization of the repeating FRB 20190520B, which is co-located with a compact, persistent radio source and associated with a dwarf host galaxy of high specific-star-formation rate at a redshift of 0.241 ± 0.001. The estimated host-galaxy dispersion measure of approximately $${903}_{-111}^{+72}$$ 903 − 111 + 72 parsecs per cubic centimetre, which is nearly an order of magnitude higher than the average of FRB host galaxies 2,6 , far exceeds the dispersion-measure contribution of the intergalactic medium. Caution is thus warranted in inferring redshifts for FRBs without accurate host-galaxy identifications. 

A small area typically refers to a subpopulation or domain of interest for which a reliable direct estimate, based only on the domain-specific sample, cannot be produced due to small sample size in the domain. While traditional small area methods and models are widely used nowadays, there have also been much work and interest in robust statistical inference for small area estimation (SAE). We survey this work and provide a comprehensive review here.We begin with a brief review of the traditional SAE methods. We then discuss SAEmethods that are developed under weaker assumptions and SAE methods that are robust in certain ways, such as in terms of outliers or model failure. Our discussion also includes topics such as nonparametric SAE methods, Bayesian approaches, model selection and diagnostics, and missing data. A brief review of software packages available for implementing robust SAE methods is also given.