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manufacturing process and enable products with high quality and performance attributes to be produced in a repeatable manner. Current methods for using AI/ML approaches for AM DT often assume a direct
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[email protected] 301.975.4393 Description There is a growing need for high-performance materials for various technological applications. To address this need, the NIST-JARVIS (https://jarvis.nist.gov
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, radiation, corrosives, and high stress, as well as low and high temperatures. We support some of society’s most critical and vulnerable reliability problems, including condition assessment of our
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. One area of interest is optomechanical sensing, where high displacement sensitivity and optomechanical interactions can be leveraged for physical measurements with fundamentally limited performance
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can be made compact and low-power through the use of laser pumping and silicon micromaching. This proejct develops compact magentic sensors than combine high sensitivity and accuracy with vector field
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researchers to contribute to the development and application of advanced measurement and automation techniques for exploring processing-structure-property-performance (PSPP) relationships in materials
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discovering new material properties, new measurements and ways for realization of efficient/high-performance electro-optical devices integrable to photonic and electronic circuitries. We offer a
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methods—Empirical Force Fields and Density Functional Theory (DFT)—frequently fail to balance the necessary accuracy with the required computational scale. Our group is developing a high-performance
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, optical spectroscopies (infrared, visible, ultraviolet, Raman, light scattering), gas chromatography/mass spectroscopy (GC/MS), high-performance liquid chromatography (HPLC), and tandem mass
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products makes mapping the high-dimensional parameter space challenging due to the sheer number of possible compositions. To enable rational design of these materials, we have developed a highly adaptable