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batteries. The main objective is to develop a molecular-level understanding of electrolyte degradation and to predict chemical stability by constructing reaction networks based on density functional theory
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Computing. · Experience with High Throughput Calculations will be valued but it is not essential. · Previous knowledge of Density Functional Theory (DFT) and experience with DFT codes will be very highly
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functional theory (DFT)-based approaches, coupled with effective continuum and/or tight-binding models derived from first-principles calculations. The project is part of a large, multi-institution
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multipurpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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advanced characterization methods of inorganic materials and their assemblies, ideally with a focus on battery materials. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics
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assemblies, ideally with a focus on battery materials. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational investigation
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multi-purpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic