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to predict materials properties is essential to improve materials design methods. This research will focus on the development and integration of first principle calculations; atomistic simulations; and/or
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fire growth. State-of-the-art fire models designed for these simulations also require input parameters (material properties) that describe: the decomposition reaction mechanism of combustible solids (and
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, electronic-, and transport-properties in 2D-like materials, such as MoS2. An important part of this project will be the simulation of actual devices and the determination of how transport properties
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. By leveraging material simulation and Machine Learning Interatomic Potentials (MLIPs), we aim to accelerate the interpretation of inelastic (INS) and quasi-elastic neutron scattering (QENS) data
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RAP opportunity at National Institute of Standards and Technology NIST Computational and Theoretical Approaches for Understanding Complex Fluids Location Material Measurement Laboratory
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, acoustic-electric spectroscopy, and other nonlinear materials characterization techniques. We will develop on-wafer acoustic microfluidic devices. Necessary skills include finite element simulations, digital
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Description We work with scientists in other NIST laboratories to develop tools for computer simulation and analysis of magnetic systems at the nanometer scale. Model verification is achieved by comparison
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complex permittivity and permeability characterization with on-wafer techniques, materials modeling (including finite element simulations, and theory), and the development of mm-wave and microwave
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NIST only participates in the February and August reviews. There is a growing need for high-performance materials for various technological applications. To address this need, the NIST-JARVIS (https
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. This computational approach, incorporating quantum mechanics, can help materials research by a) directly simulating and interpreting experiments, b) establishing relationships between material structure and properties