This lecture covers the importance of computed chemical shifts in NMR spectroscopy, exploring the need for quantum mechanical computations to determine chemical shielding. It delves into Density Functional Theory (DFT) and its approximations, discussing the challenges and principles of machine learning for predicting chemical shifts.
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Explores Car-Parrinello molecular dynamics, a unified approach combining molecular dynamics and density-functional theory for simulating various systems, with a focus on historical background, technical details, and challenges in atomistic simulations.
