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-ray metrology will guarantee results that provide for a wide x-ray community including collaborators developing cryogenic quantum sensors (transition edge sensors: TES) at NIST. key words x-ray
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Description Combining organic monolayers with semiconductor surfaces is of interest for many differing applications including molecular electronics, sensors, and bio-electronics. Monolayers on semiconductor
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NIST only participates in the February and August reviews. The development of nanomaterials, biomaterials, sensor films, and surface measurement methods require well-defined substrates that vary in
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areas include the development of interpretable and trustworthy algorithms for Scientific Artificial Intelligence and active learning, integrating FAIR data management practices throughout the research
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resolution techniques are explored to achieve quantitative reconstruction of nanoscale structure images by developing novel DUV/EUV imaging optics and quantitative phase retrieval algorithms. A qualified
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images. However, the current limitations of desktop computers in terms of memory, disk storage and computational power, and the lack of image processing algorithms for advanced parallel and distributed
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NIST only participates in the February and August reviews. We are developing machine learning algorithms to accelerate the discovery and optimization of advanced materials. These new algorithms form
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for implementing the major types of AMO systems on chip—including miniaturized stable wavelength reverences, optical atomic clocks, quantum sensors, Rydberg atom RF imaging probes, quantum memories, and others. [1
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tracking systems based on the international standard ISO/IEC 18305. We are interested in hybrid localization methods for solving this challenging problem using a variety of sensors and technologies, such as
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, optical and e-beam lithography, magnetic sensors (e.g., GMR, MTJ, SQUIDs, atomic magnetometers), magnetic nanoparticles, and magnetic particle imaging (MPI). References: Bui TQ, Biacchi AJ, Dennis CL, Tew