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.
Introduces the fundamentals of spin relaxation in magnetic resonance, covering spin-lattice and spin-spin relaxation, and rotational motion in liquids.
Explores classical and quantum mechanics, covering observables, momentum, Hamiltonian, and the Schrödinger equation, as well as quantum chemistry and the Schrödinger's cat experiment.
Explores enhancing machine learning predictions by refining error metrics and applying constraints for improved accuracy in electron density predictions.
Summarizes Generalized Gradient Approximations, Meta-GGAs, Hybrid functionals, First-Principles Molecular Dynamics, QM/MM simulations, and important features of Quantum Chemistry calculations.
Introduces the OSSCAR framework for interactive quantum mechanics simulations, showcasing current use cases and specific examples like Monte Carlo simulations and 2D diffusion.
