Covers topics in Quantum Chemistry, including history, tools, color & draw techniques, shapes, and mathematical conversions.
Explores total scattering and PDF analysis in materials science, covering in-situ synthesis, data analysis techniques, and applications in host-guest systems.
Covers eigenvalues, eigenfunctions, Hermitian operators, and the measurement of observables in quantum chemistry.
Explores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.
Covers the fundamentals of spectroscopy, including tools and techniques used for internal conversion and vibrational relaxation.
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Covers quantum states, symmetries, fermions, and variational principles in quantum chemistry.
