Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Presentation on space science at Los Alamos National Laboratory
Recent improvements in the radiation effects science capability at Sandia have achieved the following: Record gamma-ray outputs at HERMES enable qualification for Life Extension Programs (LEPs) and evaluation of electromagnetic pulse (EMP) effects on electric grid elements; Completed blind comparison for model validation of cavity system generated EMP in advanced computer simulations; For the first time, new diagnostics provide a high resolution photon energy spectrum on Z (Grand Challenge LDRD); ACRR completed record number of operations, two years in a row, to support design and qualification; Installed the nation’s largest GHz electromagnetic test chamber for design and qualification.
The American public realized the magnitude at which the atom’s power could be harnessed following the detonation of Little Boy and Fat Man in August 1945. World War II ended weeks later, but the Atomic Age had just begun. Society contextualized nuclear science into pop culture as a way of processing the era’s immense technological progress. Music, among other media, became a speculative arena for expressing the awe and angst evoked by splitting the atom.
The ASCR basic research needs for Neuromorphic Computing for Science workshop was held in September 2024. The workshop brochure and report aim to inform and draft a set of grand challenges for advancing the field of neuromorphic computing and developing proof of principle neuromorphic circuits applicable for High Performance Computer (HPC) acceleration for scientific discovery, and brainstorm ideas needed for a successful, robust, and world leading basic research program. The resulting priority research directions are: (1) Neuromorphic computing circuit primitives; (2) Connectivity, communication, and hardware integration; (3) Neuroscience-derived dynamics and algorithms; and (4) Ecosystem for scalable neuromorphic co-design. Breakthroughs in understanding, designing, and prototyping the circuitry and simulation capabilities for a truly neuromorphic computer are essential to enable progress in the field.
The ASCR basic research needs for Neuromorphic Computing for Science workshop was held in September 2024. The workshop brochure and report aim to inform and draft a set of grand challenges for advancing the field of neuromorphic computing and developing proof of principle neuromorphic circuits applicable for High Performance Computer (HPC) acceleration for scientific discovery, and brainstorm ideas needed for a successful, robust, and world leading basic research program. The resulting priority research directions are: (1) Neuromorphic computing circuit primitives; (2) Connectivity, communication, and hardware integration; (3) Neuroscience-derived dynamics and algorithms; and (4) Ecosystem for scalable neuromorphic co-design. Breakthroughs in understanding, designing, and prototyping the circuitry and simulation capabilities for a truly neuromorphic computer are essential to enable progress in the field.
The immediate goal of the workshop was to elevate and identify issues and challenges that have impeded participation of diverse individuals in MSE. The longerterm goals are to continue forward by gathering and disseminating data, launching and tracking initiatives to mitigate the impediments, and increase the number of diverse individuals pursuing degrees and careers in MSE. The larger goal, however, is to create over time an ever-increasing number of role models in science fields who will, in turn, draw others in to contribute to the workforce of the future.
Macromolecular radicals, radical polymers, and polyradicals bear unique functionalities derived from their pendant radical groups. Here, the increasing need for organic functional materials is driving the growth in research interest in macromolecular radicals for batteries, electronics, memory, and imaging. This Viewpoint summarizes the current state-of-knowledge regarding the macromolecular nitroxide radicals’ redox mechanism, conductivity, chain conformation, controlled polymerization, network structure, conjugated forms, and applications. The nitroxide radical group is the focus because it is the most widely studied. Although most literature focuses upon applications, an emerging body of work is highlighting the fundamental physicochemical properties of macromolecular radicals. To this end, this Viewpoint recommends areas of opportunity in fundamental studies and best practices in reporting.
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The authors demonstrate mobilities of >45 cm{sup 2}/V s for sputtered tin-doped indium oxide (ITO) films at zero added oxygen. All films were deposited with 5 wt. % SnO{sub 2}, instead of the more conventional 8–10 wt. %, and had varying ZrO{sub 2} content from 0 to 3 wt. %, with a subsequent reduction in In{sub 2}O{sub 3} content. These films were deposited by radio-frequency magnetron sputtering from nominally stoichiometric targets with varying oxygen partial pressure in the sputter ambient. Anomalous behavior was discovered for films with no Zr-added, where a bimodality of high and low mobilities was discovered for nominally similar growth conditions. However, all films showed the lowest resistivity and highest mobilities when the oxygen partial pressure in the sputter ambient was zero. This result is contrasted with several other reports of ITO transport performance having a maximum for small but nonzero oxygen partial pressure. This result is attributed to the reduced concentration of SnO{sub 2}. The addition of ZrO{sub 2} yielded the highest mobilities at >55 cm{sup 2}/V s and the films showed a modest increase in optical transmission with increasing Zr-content.
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Earth embeddings—vector representations of geographic locations indexed in space and time—are emerging as a unifying interface for geospatial AI. However, their quality depends not only on model design, but on how multimodal Earth observation (EO) data are spatially indexed, temporally aligned, and cross-modally associated during pretraining. We introduce MOSAIC-CONUS (Multimodal Observations with Spatially Aligned Imagery, Urban Points of Interest, In-Situ Measurements and Text Captions), a large-scale EO dataset over the contiguous United States, organized around 250,000 stratified point indices that serve as stable spatial keys across seven modalities: active radar, passive optical imagery, lidar-derived elevation, land cover, functional context, hydrometeorological measurements, and textual summaries. Unlike existing EO datasets, MOSAIC-CONUS introduces four contributions not jointly addressed in prior work: 1. an open-source, large-scale multimodal EO corpus structured around point-indexed data designed to support Earth embedding learning; 2. explicit radar-optical pairing tables spanning twelve temporal alignment regimes, formalizing cross-sensor alignment as a controllable variable for analyzing how temporal mismatch across modalities influences learned embeddings quality; 3. a benchmark suite spanning cross-modal retrieval, annual nightlights regression, and basin-held-out streamflow prediction, positioning MOSAIC-CONUS as a benchmark-ready resource for multimodal AI systems; and 4. a language-based embedding layer through co-registered textual summaries, enabling Earth embeddings to function as a queryable interface for agentic AI systems. The dataset and pairing protocols are publicly released.
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