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of new and existing structures, (4) applying the Fiber Reinforced Polymer (FRP) retrofit design to improve the performance of existing structures, (5) studying the feasibility of using high strength
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cellular debris, non-EV vesicles, protein aggregates, viruses, etc., before the isolated EVs can be manufactured into high quality drug delivery vehicles and/or therapeutic agents. The most common method
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the use of laser pumping and silicon micromaching. This proejct develops compact magentic sensors than combine high sensitivity and accuracy with vector field readout and manufacturability. We design novel
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the computational determination of 3-D features of a specimen from a series of their 2-D projections. By carefully preparing the specimen, designing the experimental acquisition, and subsequent data processing, semi
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Description This program is designed to support the design, construction, and operation of high-performance sustainable buildings with good indoor environments and low levels of energy consumption. This goals
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for the world. Likewise, U.S. manufacturing depends on its 500,000+ machine tools that make precision parts. However, a major problem with these machines is that their performance, which degrades over time due
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the standard quantum limit for fast AFM, and scientific applications such as Casimir Force measurement; probes with nanoscale plasmonic resonators for efficient, high-speed optical nearfield imaging; using
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to develop traceable materials and methods to characterize the performance of magnetic resonance imaging (MRI) scanners, particularly their ability to noninvasively measure diffusion properties, such as the
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opportunities to interface with researchers at both NIST and at the National Institutes of Health (NIH). Reference Zabow G, Dodd SJ, Koretsky AP: "Shape-changing magnetic assemblies as high-sensitivity NMR
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experimentally. However, important challenges remain, such as transition-metal compounds and floppy or tautomerizing molecules. Determining the quantitative uncertainties associated with high-level predictions is