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301.975.3438 Description NIST has developed an integrated measurement services program for forensic and cannabis (hemp and marijuana) laboratories to help ensure the quality of routine analysis of cannabis plant
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NIST only participates in the February and August reviews. As of today, there is a plethora of cyber-physical instruments consisting of physical sensing (e.g., microscopy imaging) and cyber (digital) Artificial Intelligence (AI)-based predictions. These instruments raise concerns about safety...
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NIST only participates in the February and August reviews. Community Resilience Metrics The Community Resilience Program (https://www.nist.gov/community-resilience) is developing science-based
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-and-quality-control-materials-metqual-program key words Metabolites; Metabolic pathways; Mass spectrometry; Bioinformatics; Chemometrics; Multivariate statistics; Human health; Precision medicine
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measurements during emergencies, such as those encountered in pre- or post-detonation scenarios. The nuclear forensics program at NIST focuses largely on analytical method development, new and improved
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; Combinatorial library; Informatics; High-throughput; Composition spread; Hyperspectral data Analysis; Data mining; Functional materials; Citizenship: Open to U.S. citizens
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attracted considerable attention for potential application in nanoscale devices, including beyond-CMOS electronics, quantum computers, chemical sensors, photodetectors, etc. Prospective advantages over
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to perceive latent correlations is critical to successfully integrating the vast amount of existing data, including biochemical pathways and enzymatic substrate specificities, in next-generation computational
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transitions. Many x-ray lines and satellites remain to be experimentally verified, in comparison with theory. We have a program to carry out these investigations using TES microcalorimeter detectors with 5 eV
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on the initial crystallographic texture and uniaxial stress-strain data, thereby predicting the evolution of the yield surface in multi-axial tensile space for a real specimen. Computed constitutive models will be