Physics-inspired Machine Learning for Materials Discovery

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Riemann Tensor and Ricci Scalar

Covers the properties of the Riemann tensor and Ricci scalar in normal coordinates.

AI for Science

Explores fundamental principles in scientific research, the impact of computers, numerical algorithms, and deep learning in solving high-dimensional problems.

Vector Transformation and Tense

Explores the transformation of vectors and tensors, including rotations and representations in quantum physics.

Special and General Relativity

Introduces special and general relativity, Einstein equations, and gravitational dynamics.

Thermodynamics: Energy Transformation

Covers energy transformation in thermodynamics, discussing laws, entropy, and spontaneity criteria for reactions.

Thermodynamics: System, Surface Actions, and Typology

Covers thermodynamic systems, surface actions, and system typology with examples.

Spherical Tensors and Wigner-Eckart Theorem

Covers the transformation of vectors and tensors in quantum physics.

Inertia Tensor: Main Axes and Principal Moments

Explains the inertia tensor, main axes, principal moments, and balancing of rotating solids.

Elements of Lie Groups and Algebras

Explores the transformation of vectors and tensors in quantum physics, emphasizing Lie groups and algebras.

Thermodynamics & Phase Diagrams

Explores thermodynamics, phase diagrams, Gibbs free energy, and their role in materials science.