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the phase space inhabited by complex macromolecules and blends, nano/microplastics, nanoparticles, and carbohydrates. This will be done primarily using size-based separation methods such as SEC, AF4, and HF5
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concrete structural elements under massive, real-fire loading to study scaling effects and to characterize the complex processes that drive member degradation during a fire (e.g., spalling, moisture
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Description A new capability has been developed where sheet metal can be multi-axially strained while stresses in various directions within the plane of the sheet are measured using x-ray diffraction
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guiding materials measurement experiments to acclerate learning the synthesis-process-structure-property relationship. Machine learning methods include, but are not limited to, Bayesian inference
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tabulated in x-ray fundamental parameter’s databases. The success of the fundamental parameter method for quantitative analysis depends on the accuracy and completeness of the tabulations of the used
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ionization MS, and/or related approaches) and complementary methods for the characterization of micro- and nanoplastics (MNPs). Analytical approaches for the measurement of MNPs from complex matrices will take
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, roughly), where the blackbody field is 10,000 times smaller. In this regime, Rydberg atoms could represent a factor of 100 improvement in sensitivity to 300 K blackbody fields, while being primary. Proving
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characterization tools for closed loop experiment design, execution, and analysis, where experiment design is guided by active learning, Bayesian optimization, and similar methods. A key challenge is the integration
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provides information on the abundances of the light elements produced during the Big Bang. Neutrons are used in searches for time-reversal (T) violation through a non-zero electric dipole moment or through a
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with stable isotopes such as 2 H, 13 C, 15 N, and 18 O is an important tool for structural and bioanalytical methods such as nuclear magnetic resonance (NMR), small angle neutron scattering (SANS), and