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surfaces take advantage of the increased electrical functionality, chemical and structural robustness, wealth of fabrication knowledge, and present a less disruptive technology compared with monolayers
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with 1000× increase in time resolution and 10× improvement in spatial resolution over prototypes. Such an instrument enables to measure the structure of heterogeneous systems including ageing concrete
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are designed, constructed and operated to provide optimal spaces for living and working. The industry needs tools, metrics, and processes to create buildings that are more than just static structures but living
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-driven recommendation systems that provide: Optimal and/or safest strategies for firefighting, ventilation, and search-and-rescue operations. Dynamic decision support that adapts to changing fire
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. Chemical engineers constantly need reliable property data for process design development and optimization. This information is predominantly coming from scientific publications. Thousands of papers
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NIST only participates in the February and August reviews. Manufacturing optimized devices that incorporate newly-emerging materials requires predictable performance throughout device lifetimes
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impediments to meeting the desired manufacturing and performance standards. Digital twins (DT) are being adopted in the AM industry to optimize the entire manufacturing process and enable products with high
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Machine Learning-driven Autonomous Systems for Materials Discovery and Optimization NIST only participates in the February and August reviews. We are developing machine learning-driven autonomous
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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