Abstract Dynamic MRI reconstruction, one of inverse problems, has seen a surge by the use of deep learning techniques. Especially, the practical difficulty of obtaining ground truth data has led to the emergence of unsupervised learning app... Read More
Abstract In the mass production of metal-based products such as automobiles, continuous welding and assembly processes are essential. The final product is created through multiple stages of welding, and the cumulative misalignment at each s... Read More
Abstract Xylene isomer separation is a long-standing challenge due to the nearly identical properties of para-xylene (PX), meta-xylene (MX), ortho-xylene (OX), and ethylbenzene (EB). Here, we report a rationally designed pillar-layered meta... Read More
Abstract Stabilization of hypoxia-inducible factor 1 alpha (HIF1α), which plays a pivotal role in regulating cellular responses to insufficient oxygen, is implicated in cancer progression, particularly epithelial-mesenchymal transition and... Read More
Abstract Nonlinear intersubband polaritonic metasurfaces based on coupling of the intersubband nonlinear optical response of quantum-engineered semiconductor heterostructures and electromagnetic modes of nanoresonators provide efficient fre... Read More
Abstract This study explored the multifaceted role of flavin adenine dinucleotide (FAD) in modulating proton-coupled electron transfer (PCET) processes for electrocatalysis. FAD demonstrated catalyst-dependent functionality, enhancing hydro... Read More
Abstract Solar desalination offers a sustainable solution for freshwater production with minimal carbon emissions by utilizing solar energy. However, the efficiency of solar-vapor generation is often limited due to its high energy demands,... Read More
Abstract Thermogalvanic (TG) cells are a promising technology for harvesting low-grade waste heat, but their practical applications have been hindered by low thermopower and output power density. Here, we report for the first time a solid-s... Read More
Abstract Meta reinforcement learning aims to develop policies that generalize to unseen tasks sampled from a task distribution. While context-based meta-RL methods improve task representation using task latents, they often struggle with out... Read More
Abstract High-energy density materials are essential for the advancement of next-generation lithium-ion batteries, which power a wide range of applications from portable electronics to electric vehicles. Among them, high-Nickel (Ni) layered... Read More
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