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these high resolution studies to DNA-based molecular motors and RNA-folding. In a parallel effort, we significantly enhanced the biophysical capabilities of an atomic force microscope (AFM
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, massively parallel, single-molecule peptide sequencing. This platform is not limited in dynamic range and thus will enable identification of the composition of complete proteomes through the
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informed by and feed into parallel work in macroscale thermomechanical finite element modeling, CALPHAD-based thermodynamics, and crystal plasticity and to both powder-scale and atomic-scale simulations
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time and length scales to predict the microstructure evolution during the AM build process and post build thermal-mechanical processing. Some of these modeling tools include density functional theory
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well-structured form to the final industrial users. Recent advances in AI (Artificial Intelligence), specifically in NLP (Natural Language Processing) and ML (Machine Learning), are promising for
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phased array antennas, radio frequency signals design and processing, and mutlitmodal sensing. The project welcomes expertise in robotics, serial communication protocols and microprocessors, signal
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processing with recent breakthroughs in densification of ceramics, like cold sintering[2] or ultra-fast high-temperature sintering [3]. Our effort at NIST focuses on developing predictive tools for
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. 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 the
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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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devoted to studies of quantum-state engineering and entanglement with application to quantum-information processing, quantum simulation, spectroscopy, and tests of quantum mechanics. Keywords Atomic