Simulation of Semiconductor Properties

What it is about

In this module you will learn to perform high-precision simulations of semiconductor materials and to analyze the results. You will apply density functional theory (DFT) to calculate electronic properties and use basic machine-learning methods to support and accelerate materials science questions. In the end you will be able to conduct DFT simulations, evaluate electronic properties, and use simple ML models for materials research.

What you will be able to do

• Understand the basic concepts of density functional theory
• Carry out DFT simulations with existing software tools (e.g., QuantumEspresso)
• Analyze electronic properties of semiconductor materials
• Understand basic concepts of various machine-learning architectures
• Apply ML techniques in semiconductor materials research

What the module consists of

• VorlesungenTransmission of the theoretical foundations of DFT and ML, supported by electronic presentations and discussions
• Tutorien/ÜbungenPractical application of DFT and ML tools, presentation and discussion of implementations
• Selbstständige Projekte und HausaufgabenApplication of what has been learned in lecture-related projects and problem solving

Teaching method

• aktive Teilnahme und Diskussionpromotes understanding through exchange and explanations among students
• Umgekehrtes Klassenzimmer (Flipped Classroom)enables in-depth engagement with challenging concepts outside of the lecture
• personalisierte Lehrmethodensupports individual learning and achievement of learning goals