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Guided learning journeys that build knowledge step by step.
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This learning path introduces the hierarchy of electronic structure methods used in computational chemistry, from ab initio wavefunction methods to semi-empirical and density functional theory. It covers essential quantum mechanics and basis set concepts, enabling students to understand how these methods are classified and applied.
A systematic path for high school students to understand fundamental quantum mechanics principles, focusing on the Schrödinger equation, wavefunctions, operators, Born interpretation, and the particle in a box model. It includes necessary prerequisites in calculus and physics.
This path introduces the classical physics and calculus concepts needed to understand how molecules are modeled. It covers Newton's equations, potential energy, harmonic oscillators, molecular vibrations, and the force field approximations used in computational chemistry.
A systematic learning path covering the essential mathematics—basic calculus, linear algebra, and differential equations—needed to understand computational chemistry. This path builds from foundational algebra and functions through to the mathematical tools used in quantum chemistry and molecular modeling.
This learning path introduces high school students to the field of computational chemistry, covering the role of computation in chemistry, key methods (QM, MM, MD), their applications and limitations, and common software tools. It builds from basic chemical concepts to provide a systematic overview for beginners.
A comprehensive graduate-level learning path covering the essential knowledge and skills for conducting research in materials chemistry, from foundational concepts to advanced characterization, computational modeling, and scientific communication.
This learning path equips graduate students with the skills to apply machine learning to materials discovery. It covers essential chemistry, data handling, feature engineering, property prediction, generative models, and high-throughput screening, with a focus on practical, data-driven approaches.
This graduate-level path explores the chemistry underpinning quantum materials, focusing on how electronic structure gives rise to topological phenomena. It covers essential solid-state chemistry, band theory, and synthesis principles, then applies them to topological insulators, Dirac/Weyl materials, and spintronics applications.
This graduate-level path explores the materials chemistry of advanced batteries, covering cathodes, anodes, solid electrolytes, and interfacial phenomena. It starts with foundational electrochemistry and progresses through each component, emphasizing structure-property relationships and interfacial challenges.
This advanced graduate-level path explores perovskite materials, beginning with their crystal structure and electronic properties, then covering synthesis methods, their use in solar cells and optoelectronics, stability challenges, and non-photovoltaic applications. It is designed for students interested in solar energy who want a deep understanding of these materials.