141 information-security-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at NIST in United States
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limited output of these devices is well suited to measuring long open-air paths and the combs themselves are becoming robust, compact, and transportable. Here we seek to employ frequency combs
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reviews. Nuclear magnetic resonance (NMR) spectroscopy has several important advantages for quantitative measurements of amount of substance: authentic material is not required for calibration, sample
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NIST only participates in the February and August reviews. The need to reduce building energy consumption is well-established and has been the subject of research for many decades. More recent
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NIST only participates in the February and August reviews. While natural and anthropogenic contaminants threaten existing freshwater supplies, the use of alternative, “dirty” sources is increasing
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performance modeling capabilities that simultaneously consider multiple performance aspects, robust IAQ and other performance metrics, and measurement methods, sensors, and data to evaluate and verify building
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crime scene hazards—require more sensitive and robust methods, especially in field environments. Another area of concern is that current analytical methods for drug testing are not agile or well-resolved
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of engineered biological systems. We are recruiting applicants for experimental and theoretical research to advance rational design for engineering biology. Of particular interest is the development of new
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interactions with the electrolyte as a function of applied potential. Despite more than a century of model development, much is still unknown about even single-crystal interfaces. We combine spectroscopic and
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designs. In addition to fabrication and characterization of these measurement tools, we also develop new readout schemes, signal and data processing, control systems, and biomimetic surfaces to improve
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are interested in project ideas that focus on the development and application of measurement techniques, physics-based or data-driven models, and standards to better understand and improve metals-based AM. Our AM