Cloud-Based Teaching Tool of AlCu Band Gap Simulations Using GPAW: A Python-Driven Approach for Undergraduate Student

This work introduces a computational teaching module that leverages Python, Google Colab, and the GPAW package to simulate the electronic band structure of AlCu materials. While powerful, traditional Density Functional Theory (DFT) tools like Quantum ESPRESSO or VASP often present steep learning curves and software installation challenges. By contrast, GPAW operating within Python and its seamless integration with Google Colab provides a user-friendly, platform-independent environment for students to explore quantum simulations without local setup requirements. The simulation workflow is highly efficient, with key processes such as structure creation taking only 7 milliseconds, structural relaxation requiring 51.2 seconds, and band structure calculations completing in just 40 seconds. In this educational framework, students model AlCu and its doped variants, visualize band structures, and analyze changes in the electronic properties induced by doping. The approach supports active learning and reinforces core solid-state physics, quantum mechanics, and computational materials science topics. Sample notebooks, learning outcomes, and classroom integration strategies are presented, aiming to democratize access to DFT education through open-source, cloud-based tools.