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During our study of the synthesis of metal nanoparticles via chemical reduction methods, we found that some colloidal solutions of silver nanoparticles displayed dichroic effect. The dichroic effect is a phenomenon where a material displays two different colors in transmitted light and reflected light. In this study, dichroic silver nanoparticles were obtained via a simple chemical reduction method under ambient conditions. Ascorbic acid was used as the reducing agent and trisodium citrate was used as the stabilizing agent. A colloidal solution of synthesized silver nanoparticles showed an opaque gray color in reflected light and a translucent pink color in transmitted light. Another colloidal solution prepared in the presence of copper (II) sulphate displayed a new combination of dichroic colors: opaque blue and translucent green. To understand the formation of dichroic effect, Transmission electron microscopy (TEM) and UV-Vis spectroscopy were used to characterize and study the silver nanoparticles in these colloids. TEM study showed that silver nanoparticles with different sizes and shapes were present in the solutions that displayed dichroic effect. By comparing the morphology of dichroic silver nanoparticles with that of the silver nanoparticles that exhibited no dichroic effect, we concluded that both the sizes and the shapes of nanoparticles play important roles in the formation of dichroic effect. The small particles are responsible for the absorbance of light, which results in the color in transmitted light. While large particles account for the scattering of light and lead to the color in reflected light. Different combinations of nanoparticles with different sizes and shapes lead to different colors for the dichroic effects. 

The scattering transform is a multilayered wavelet-based architecture that acts as a model of convolutional neural networks. Recently, several works have generalized the scattering transform to graph-structured data. Our work builds on these constructions by introducing windowed and nonwindowed geometric scattering transforms for graphs based on two very general classes wavelets, which are in most cases based on asymmetric matrices. We show that these transforms have many of the same theoretical guarantees as their symmetric counterparts. As a result, the proposed construction unifies and extends known theoretical results for many of the existing graph scattering architectures. Therefore, it helps bridge the gap between geometric scattering and other graph neural networks by introducing a large family of networks with provable stability and invariance guarantees. These results lay the groundwork for future deep learning architectures for graph-structured data that have learned filters and also provably have desirable theoretical properties. 

Abstract Metal halide perovskites show promise for next-generation light-emitting diodes, particularly in the near-infrared range, where they outperform organic and quantum-dot counterparts. However, they still fall short of costly III-V semiconductor devices, which achieve external quantum efficiencies above 30% with high brightness. Among several factors, controlling grain growth and nanoscale morphology is crucial for further enhancing device performance. This study presents a grain engineering methodology that combines solvent engineering and heterostructure construction to improve light outcoupling efficiency and defect passivation. Solvent engineering enables precise control over grain size and distribution, increasing light outcoupling to ~40%. Constructing 2D/3D heterostructures with a conjugated cation reduces defect densities and accelerates radiative recombination. The resulting near-infrared perovskite light-emitting diodes achieve a peak external quantum efficiency of 31.4% and demonstrate a maximum brightness of 929 W sr⁻¹m⁻². These findings indicate that perovskite light-emitting diodes have potential as cost-effective, high-performance near-infrared light sources for practical applications. 

The 3′ untranslated regions (UTRs) of positive-strand RNA plant viruses commonly contain elements that promote viral replication and translation. The ~700 nt 3′UTR of umbravirus pea enation mosaic virus 2 (PEMV2) contains three 3′ cap-independent translation enhancers (3′CITEs), including one (PTE) found in members of several genera in the family Tombusviridae and another (the 3′TSS) found in numerous umbraviruses and several carmoviruses. In addition, three 3′ terminal replication elements are found in nearly every umbravirus and carmovirus. For this report, we have identified a set of three hairpins and a putative pseudoknot, collectively termed “Trio”, that are exclusively found in a subset of umbraviruses and are located just upstream of the 3′TSS. Modification of these elements had no impact on viral translation in wheat germ extracts or in translation of luciferase reporter constructs in vivo. In contrast, Trio hairpins were critical for viral RNA accumulation in Arabidopsis thaliana protoplasts and for replication of a non-autonomously replicating replicon using a trans-replication system in Nicotiana benthamiana leaves. Trio and other 3′ terminal elements involved in viral replication are highly conserved in umbraviruses possessing different classes of upstream 3′CITEs, suggesting conservation of replication mechanisms among umbraviruses despite variation in mechanisms for translation enhancement. 

Abstract Population growth, urbanization, and decarbonization efforts are collectively straining the supply of limited resources that are necessary to produce batteries, electronics, chemicals, fertilizers, and other important products. Securing the supply chains of these critical resources via the development of separation technologies for their recovery represents a major global challenge to ensure stability and security. Surface water, groundwater, and wastewater are emerging as potential new sources to bolster these supply chains. Recently, a variety of material‐based technologies have been developed and employed for separations and resource recovery in water. Judicious selection and design of these materials to tune their properties for targeting specific solutes is central to realizing the potential of water as a source for critical resources. Here, the materials that are developed for membranes, sorbents, catalysts, electrodes, and interfacial solar steam generators that demonstrate promise for applications in critical resource recovery are reviewed. In addition, a critical perspective is offered on the grand challenges and key research directions that need to be addressed to improve their practical viability.