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of failure strengths are needed to ensure reliability and maximize performance. We use numerous modeling approaches to explore the mechanical and electrical behavior of deforming nanoscale systems. Current
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the construction process and correlates to the durability and service life of the composites. The goal is to understand the interplay between structure-properties-performance within these systems
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nanoelectronics fabrication methods. Measurements are performed in diagnostic-compatible CVD and ALD reactors under realistic deposition conditions. Various in situ vibrational spectroscopic techniques are employed
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research program focuses on engineering these nanoparticles with desired physical and chemical properties and specified functionality through wet-chemistry synthesis. We are particularly interested in
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RAP opportunity at National Institute of Standards and Technology NIST Applications of Machine Learning/AI to Neutron Scattering Location NIST Center for Neutron Research opportunity location 50.61.01.C0300 Gaithersburg, MD NIST only participates in the February and August...
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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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quantitative optical response. Review of Scientific Instruments, 87:9 DOI: 10.1063/1.4962034 Asmar A, Benson Z, Chalfoun J, Peskin A, Halter M, Plant A. (2024). High-volume, label-free imaging for quantifying
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information. Our group performs research and development to extend the accuracy, wavelength range, power range, robustness, and portability of radiometric standards. We use advanced nanfabrication techniques
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301.975.4368 Description The domestic recovery of critical materials (CM) from various feed streams faces significant challenges due to the limited availability of advanced separation technologies and their high
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measurements at 18-digit accuracy using an optical clock network. Nature 591, 564–569 (2021). https://doi.org/10.1038/s41586-021-03253-4 [2] Chave, A. D. (2019). A multitaper spectral estimator for time-series