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been in development over the past 15+ years and their capabilities have grown significantly. An important effort within the LPBF community is the use of high-fidelity multiphysics models to predict melt
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@nist.gov 301 975 2093 Description This opportunity focuses on the development of analytical methods and/or data processing techniques that could be used to advance drug detection and identification (or drug
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development of advanced models for the prediction of the above physical properties in such solid solutions. We use first-principles density functional theory calculations to uncover the microscopic physics
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further enriches the available data from which material behavior can be extracted. Separate work is being done to develop robust algorithms to quantitatively compare the physical and simulated experimental
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augmented intelligent solutions that monitor, diagnose, and predict process performances to optimize production quality and yield. Proposals are welcome to develop augmented intelligent solutions
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their processes. Smart machine tools assess and predict their health and the performance of their processes in real time to optimize production quality and yield. Proposals are welcome to develop
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, plays an important role at NIST in the development and interpretation of new measurement techniques, as well as aiding the understanding of the behavior of new materials in existing measurements. In
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, (2) interpretation of experimental spectra, (3) development of semi-empirical methods, (4) studies of reactivity indices, (5) computational electrochemistry, and (6) chemical informatics. The explosion
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are developing new methods for characterizing the structure and dynamics of the interface and interphase regions in carbon-based nanocomposite materials and in the overall conductive properties of these polymer
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provides the thermochemical foundation for new noninvasive breath analysis techniques. Law enforcement applications include the development of breath analysis devices for the quantitative measurement of drug