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they cannot intercalate into commonly used anode materials like graphite. This project aims to investigate the atomic level sodium storage mechanism in hard carbon via combined experiment and atomistic
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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development with broad, long-term impact. Not only will you gain insights into fundamental atomistic properties of alkali metals, but you’ll also contribute to pioneering computational tools that extend far
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combining: Molecular synthesis Electrical contacting of nanoscale electronics Modelling of properties on an atomistic level The IHRS NanoNet offers an international scientific environment and an excellent
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will be augmented with atomistic structure data from electronic structure theory and STEM image simulations. All data will be combined into an automated workflow that predicts thermodynamically stable
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model system: it is an inherently defective system (like almost all real catalysts) that can be anchored to supports amenable to fundamental atomistic studies. This research will build upon an ongoing
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quantum systems, collaborating with top-tier researchers in chemical synthesis, analytical method development, and atomistic simulations. Located in the Zurich Area, the Swiss Federal Laboratories
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resolution AFM experiments (PhD 1, University of Twente) and atomistic modelling (PhD 2, Leiden University) to address these challenges. Next to your AFM measurement at PCF, you can also explore