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Hexavalent chromium, Cr(VI), is a highly toxic carcinogen occurring in natural and industrial environments. Pathways to economical reduction to the more benign trivalent form, Cr(III), are necessary for treatment of contaminated groundwater. Magnetite’s (Fe₃O₄) mixture of Fe(II) and Fe(III) make it a promising material for remediation. This study investigated the mechanisms for reduction of Cr(VI) catalyzed by Fe₃O₄as a redox mediator in the presence of oxalic acid in HClO₄and SO₄²⁻solutions, a system where the interactions among these species are not fully understood. The reduction of Cr(VI) in different anion environments is first measured on an Au rotating disk electrode. SO₄²⁻inhibits the formation of a passivation layer and Cl^-partially inhibits passivation. The reduction of Cr(VI) on Fe₃O₄is limited by the availability of Fe(II) surface sites. Addition of oxalic acid works synergistically through liberation of Fe(II)-oxalate and soluble Cr(III)-oxalate products. A combination of Fe₃O₄activated by exposure to oxalic acid and use of an oxalic acid solution as a medium for reduction of Cr(VI) produces over 97% removal of Cr(VI). These results provide relevant insights regarding interactions of Fe₃O₄with organic acids and the anion environment which lead to the effective reduction of Cr(VI). 

Abstract The field of sustainable heterogeneous catalysis is evolving rapidly, with a strong emphasis on developing catalysts that enhance efficiency. Among various heterogeneous photocatalysts, metal‐organic frameworks (MOFs) have gained significant attention for their exceptional performance in photocatalytic reactions. In this context, contrary to the conventional homogeneous iridium or ruthenium‐based photocatalysts, which face significant challenges in terms of availability, cost, scalability, and recyclability, a new Ba/Ti MOF (ACM‐4) is developed as a heterogeneous catalyst that can mimic/outperform the conventional photocatalysts, offering a more sustainable solution for efficient chemical processes. Its redox potential and triplet energy are comparable to or higher than the conventional catalysts, organic dyes, and metal semiconductors, enabling its use in both electron transfer and energy transfer applications. It facilitates a broad range of coupling reactions involving pharmaceuticals, agrochemicals, and natural products, and is compatible with various transition metals such as nickel, copper, cobalt, and palladium as co‐catalysts. The effectiveness of theACM‐4as a photocatalyst is supported by comprehensive material studies, photophysical, and recycling experiments. These significant findings underscore the potential ofACM‐4as a highly versatile and cost‐effective photoredox catalyst, providing a sustainable, one‐material solution for efficient chemical processes. 

Abstract When the scientific dataset evolves or is reused in workflows creating derived datasets, the integrity of the dataset with its metadata information, including provenance, needs to be securely preserved while providing assurances that they are not accidentally or maliciously altered during the process. Providing a secure method to efficiently share and verify the data as well as metadata is essential for the reuse of the scientific data. The National Science Foundation (NSF) funded Open Science Chain (OSC) utilizes consortium blockchain to provide a cyberinfrastructure solution to maintain integrity of the provenance metadata for published datasets and provides a way to perform independent verification of the dataset while promoting reuse and reproducibility. The NSF- and National Institutes of Health (NIH)-funded Neuroscience Gateway (NSG) provides a freely available web portal that allows neuroscience researchers to execute computational data analysis pipeline on high performance computing resources. Combined, the OSC and NSG platforms form an efficient, integrated framework to automatically and securely preserve and verify the integrity of the artifacts used in research workflows while using the NSG platform. This paper presents the results of the first study that integrates OSC–NSG frameworks to track the provenance of neurophysiological signal data analysis to study brain network dynamics using the Neuro-Integrative Connectivity tool, which is deployed in the NSG platform. Database URL: https://www.opensciencechain.org. 

Perovskite materials are used for high temperature electrochemical applications such as solid oxide fuel cells (SOFC) and electrolyzers due to their tunable conductivity and catalytic activity. However, high temperature operation poses significant challenges in both fabrication and durable operation that is further complicated by the operating environment. We studied barium niobates with various A and B site dopants. These doped niobates showed enhanced thermochemical stability in SOFC relevant conditions and catalytic activity towards methane activation. The redox behavior of the Nb^4+/5+couple seem to be at a key reason behind this redox stability while the size and electronegativity of the dopants affect the electrical properties. The chemical stability was analyzed by TGA measurements followed by analysis of the perovskite powders using PXRD measurements. Impedance measurements were utilized to analyze their electrical conductivity. Our results demonstrate doped barium niobates as a promising candidate for stable operation in high temperature electrochemical applications. 

Abstract The development of high-resolution microscopes has made it possible to investigate cellular processes in 3D and over time. However, observing fast cellular dynamics remains challenging because of photobleaching and phototoxicity. Here we report the implementation of two content-aware frame interpolation (CAFI) deep learning networks, Zooming SlowMo and Depth-Aware Video Frame Interpolation, that are highly suited for accurately predicting images in between image pairs, therefore improving the temporal resolution of image series post-acquisition. We show that CAFI is capable of understanding the motion context of biological structures and can perform better than standard interpolation methods. We benchmark CAFI’s performance on 12 different datasets, obtained from four different microscopy modalities, and demonstrate its capabilities for single-particle tracking and nuclear segmentation. CAFI potentially allows for reduced light exposure and phototoxicity on the sample for improved long-term live-cell imaging. The models and the training and testing data are available via the ZeroCostDL4Mic platform. 

Doped perovskite metal oxide catalysts of the form A(B_xM_1-x)O_3-δhave been instrumental in the development of solid oxide electrolyzers/fuel cells. In addition, this material class has also been demonstrated to be effective as a heterogeneous catalyst. Co-doped barium niobate perovskites have shown remarkable stability in highly acidic CO₂sensing measurements/environments (1). However, the reason for their chemical stability is not well understood. Doping with transition metal cations for B site cations often leads to exsolution under reducing conditions. Many perovskites used for the oxidative coupling of methane (OCM) or the electrochemical oxidative coupling of methane (E-OCM) either lack long term stability, or catalytic activity within these highly reducing methane environments. The Mg and Fe co-doped barium niobate BaMg_0.33Nb_0.67-xFe_xO_3-δshown activity in E-OCM reactors over long periods (2) (>100 hrs) with no iron metal exsolution observed by diffraction or STEM EDX measurements. In contrast, iron decorated BaMg_0.33Nb_0.67O₃showed little C2 conversion activity.