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Phase transformations have been a prominent topic of study for both fundamental and applied science. Solid-liquid reaction-induced phase transformations can be hard to characterize, and the transformation mechanisms are often not fully understood. Here, we report reversible phase transformations between a metal (Pb) nanocrystal and a viscous liquid-like phase unveiled by in situ liquid cell transmission electron microscopy. The reversible phase transformations are obtained by modulating the electron current density (between 1000 and 3000 electrons Å-2 s-1). The metal-organic viscous liquid-like phase exhibits short-range ordering with a preferred Pb-Pb distance of 0.5 nm. Assisted by density functional theory and molecular dynamics calculations, we show that the viscous liquid-like phase results from the reactions of Pb with the CH3O fragments from the triethylene glycol solution under electron beam irradiation. Such reversible phase transformations may find broad implementations.

Teachers' instructional language is often described as key in facilitating the learning of children with disabilities. This article explored two teachers' instructional language as used in interactions with children with mild and severe language difficulties in one-on-one instructional sessions. The results showed that teachers used more declarative sentences to convey information with students with mild communication difficulties and more imperative sentences to express requests with students with severe communication difficulties. The language used across all students was mainly on the concrete level, with little opportunity to facilitate higher levels of cognitive activities. One teacher used longer sentences with a student with mild impairments than with a student with severe language difficulties. The most frequently used words reflected the use of core vocabulary in the classrooms. Implications and limitations of the study are discussed. [Note: The author and abstract found via the url is for another article and is incorrect.]

Na metal is an attractive anode material for rechargeable Na ion batteries, however, the dendritic growth of Na can cause serious safety issues. Along with modifications of solid-electrolyte interphase (SEI), engineering the electrode has been reported to be effective in suppressing Na dendritic growth, likely by reducing localized current density accumulation. However, fundamental understanding of Na growth at the nanoscale is still limited. Here, we report an in-situ study of Na electrodeposition in electrochemical liquid cells with the electrodes in different surface roughness, e.g., flat or sharp curvature. Real time observation using transmission electron microscopy (TEM) reveals the Na electrodeposition with remarkable details. Relatively large Na grains (in the micrometer scale) are achieved on the flat electrode surface. The local SEI thickness variations impact the growth rate, thus the morphology of individual grains. In contrast, small Na grains (in tens of nanometers) grow explosively on the electrode at the point with sharp curvature. The newly formed Na grains preferentially deposit at the base of existing grains close to the electrode. Further studies using continuum-based computational modeling suggest that the growth mode of an alkali metal (e.g. Na) is strongly influenced by the transport properties of SEI. Our direct observation of Na deposition in combination with the theoretical modeling provides insights for comprehensive understanding of electrode roughness and SEI effects on Na electrochemical deposition.

ObjectiveTo develop an analytical method for fast determination of banned pigment quinoline yellow in pastries by salting out assisted-high performance liquid chromatography.MethodsThe sample was extracted with 40% methanol-sodium chloride-water， precipitated with potassium ferrocyanide-zinc acetate solution， eluted with mobile phase of methanol-0.02 mol/L ammonium acetate solution， separated by X-Bridge C18 column v（150 mm×4.6 mm， 3.5 μm）， and detected with diode -array detector by external standard method.ResultsThe method showed good linearity （r>0.999） in the range of 0.4-40.0 μg/mL. The limit of detection （S/N=3） was 1.25 mg/kg and the limit of quantification （S/N=10） was 5.0 mg/kg. The average recoveries of three different concentrations level at 5.0， 10.0 and 50.0 mg/kg ranged from 89.18% to 110.10%， with relative standard deviation in the range of 2.83%-8.65%.ConclusionThe method was convenient， accurate and reproducible， and it was suitable for qualitative and quantitative analysis of banned pigment quinoline yellow in pastries.

The formation of complex hierarchical nanostructures has attracted a lot of attention from both the fundamental science and potential applications point of view. Spherulite structures with radial fibrillar branches have been found in various solids; however, their growth mechanisms remain poorly understood. Here, we report real time imaging of the formation of two-dimensional (2D) iron oxide spherulite nanostructures in a liquid cell using transmission electron microscopy (TEM). By tracking the growth trajectories, we show the characteristics of the reaction front and growth kinetics. Our observations reveal that the tip of a growing branch splits as the width exceeds certain sizes (5.5–8.5 nm). The radius of a spherulite nanostructure increases linearly with time at the early stage, transitioning to nonlinear growth at the later stage. Furthermore, a thin layer of solid is accumulated at the tip and nanoparticles from secondary nucleation also appear at the growing front which later develop into fibrillar branches. The spherulite nanostructure is polycrystalline with the co-existence of ferrihydrite and Fe3O4 through-out the growth. A growth model is further established, which provides rational explanations on the linear growth at the early stage and the nonlinearity at the later stage of growth. [Figure not available: see fulltext.].

Rational design and synthesis of transition metal sulfide complex nanostructures are significant for achieving desired materials properties for a variety of applications. Herein, we synthesized nickel sulfide (NiS) nanostructures using laser irradiation in an aqueous solution and under the ambient condition. Crystalline nanostructures with high phase-purity were achieved without further calcination. Other transition metal sulfides, such as CuS and ZnS, were also successfully synthesized using the laser irradiation approach, suggesting the practical application of this method. The hydrogen evolution reaction (HER) measurements show the NiS nanostructures synthesized for 4h (NiS-4h) not only exhibited competitive overpotential (−159 mV vs. RHE at 10 A/g), lower Tafel slope (218 mV/dec) but also delivered long-term stability (14 A/g at −250 mV vs. RHE for 12h). Moreover, the NiS-4h functioned as the electrode for supercapacitor with excellent specific capacitance (3761 F/g at 10 mV/s), reversibility and rate capability (1152 F/g at 100 mV/s). These superb electrochemical performances are attributed to the remarkable value of electrochemically active surface area (ECSA) and synergistic effect of Ni3+OOH for HER electrocatalytic activities, while the co-existence of Ni2+ and Ni3+ facilitates the rich redox reactions of NiS for supercapacitor.

We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and population effects of interventions with proven individual-level efficacy. In these settings, individual-level outcomes are correlated due to shared cluster-level factors, including the exposure, as well as social or biological interactions between individuals. To flexibly and efficiently estimate the effect of a cluster-level exposure, we present two targeted maximum likelihood estimators (TMLEs). The first TMLE is developed under a non-parametric causal model, which allows for arbitrary interactions between individuals within a cluster. These interactions include direct transmission of the outcome (i.e. contagion) and influence of one individual's covariates on another's outcome (i.e. covariate interference). The second TMLE is developed under a causal sub-model assuming the cluster-level and individual-specific covariates are sufficient to control for confounding. Simulations compare the alternative estimators and illustrate the potential gains from pairing individual-level risk factors and outcomes during estimation, while avoiding unwarranted assumptions. Our results suggest that estimation under the sub-model can result in bias and misleading inference in an observational setting. Incorporating working assumptions during estimation is more robust than assuming they hold in the underlying causal model. We illustrate our approach with an application to HIV prevention and treatment.

Selective nitrogen-doping of graphene oxide with a high pyridinic N ratio (51%; L-GO) was achieved by laser irradiation of graphene oxide with ammonia. The resulting L-GO exhibited enhanced electrocatalytic properties; specifically, the overpotential of the hydrogen evolution reaction (HER) was improved by over 400 mV at 10 mA cm-2 compared to the pristine graphene oxide.

Causal mediation analysis can improve understanding of the mechanism s underlying epidemiologic associations. However, the utility of natural direct and indirect effect estimation has been limited by the assumption of no confounder of the mediator-outcome relationship that is affected by prior exposure (which we call an intermediate confounder)--an assumption frequently violated in practice. We build on recent work that identified alternative estimands that do not require this assumption and propose a flexible and double robust targeted minimum loss-based estimator for stochastic direct and indirect effects. The proposed method intervenes stochastically on the mediator using a distribution which conditions on baseline covariates and marginalizes over the intermediate confounder. We demonstrate the estimator's finite sample and robustness properties in a simple simulation study. We apply the method to an example from the Moving to Opportunity experiment. In this application, randomization to receive a housing voucher is the treatment/instrument that influenced moving with the voucher out of public housing, which is the intermediate confounder. We estimate the stochastic direct effect of randomization to the voucher group on adolescent marijuana use not mediated by change in school district and the stochastic indirect effect mediated by change in school district. We find no evidence of mediation. Our estimator is easy to implement in standard statistical software, and we provide annotated R code to further lower implementation barriers.