121 virtualization "https:" "https:" "https:" "https:" "https:" "EMBL" positions at NIST
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," Optica 12, 585-593 (2025), https://doi.org/10.1364/OPTICA.554862 A. Boes, M. Strain, L. Chang, and N. Nader; "Hybrid and heterogeneous integration in photonics: From physics to device applications." Appl
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https://www.nist.gov/programs-projects/pipeline-safety to learn more about our facilities and current research. Radiation; Metallurgy; Materials science; NDE; Modeling; Fracture; Fatigue; Corrosion
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for atmospheric measurements over kilometer to multi-kilometer scale of many trace gases that are critical to climate change and air quality. We have demonstrated open-path dual-comb spectroscopy (DCS) in the near
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NIST only participates in the February and August reviews. There is a growing need for high-performance materials for various technological applications. To address this need, the NIST-JARVIS (https
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reconstruction using Fourier domain optical normalization." Light-Science and Applications 5: el 60389, 2016. http://dx.doi.org/10.1038/Isa.2016.38 Henn MA, et al: "Optimizing the nanoscale quantitative optical
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identification of its chemical components. The most sensitive and widely employed method for making such identifications involves matching tandem spectra acquired via liquid chromatography tandem mass spectrometry
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system metrics to aid in the prioritization of investments. See https://www.nist.gov/services-resources/software/nist-arc-nist-alternatives-resilient-communities-tool . 1. Faiz, Tasnim Ibn, Kenneth W
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retardant technologies More information about the fire research group https://www.nist.gov/el/fire-research-division-73300/flammability-reduction-73304 The main projects in the group are: Exposure
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properties to them, generates a finite element mesh, and performs virtual measurements. The goal is to build a computational platform that can predict the macroscopic behavior of a material from knowledge of
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to increase usage by the community. [1] https://doi.org/10.1039/C9SM01877H [2] https://doi.org/10.1063/1.5123683 [3] https://doi.org/10.6028/jres.123.004 key words Molecular simulation; Monte Carlo