Scientific  programming with Python

Aldo Rodriguez

Abstract.

Python has become one of the most widely used programming languages in scientific research due to its simplicity, extensive ecosystem, and ability to integrate numerical computing, data analysis, visualization, and high-performance computing within a single environment. This workshop introduces the fundamental tools required to develop efficient and reproducible scientific applications using Python. Participants will learn the basics of the language, scientific libraries such as NumPy, SciPy, Matplotlib, and pandas, as well as best practices for organizing computational workflows, managing virtual environments, and creating reproducible analyses through Jupyter Notebooks. Practical examples from data science, computational physics, and materials science will illustrate how Python can accelerate research and facilitate collaboration across scientific disciplines.

References

1. Van Rossum, G., & Drake, F. L. (2009). Python 3 Reference Manual. CreateSpace.
   
2. Virtanen, P., Gommers, R., Oliphant, T. E., et al. (2020). SciPy 1.0: Fundamental algorithms for scientific computing in Python. Nature Methods, 17, 261–272.

Introduction to Density Functional Theory (DFT): Fundamentals
and Practical Applications Using VASP

Jonathan Hueso

Abstract.

Density Functional Theory (DFT) has become one of the most  mportant computational tools for studying materials at the atomic scale, enabling the prediction and understanding of their structural, electronic, and chemical properties from first principles. This workshop aims to provide an accessible introduction to the fundamentals of DFT, covering the historical developments that led to the formulation of this theory. In addition, the fundamental concepts underlying DFT will be presented, providing a general overview of its principles and its relevance in modern materials
science.

As a complement to the theoretical component, a practical session will be conducted to familiarize participants with the basic workflow employed in DFT calculations using the Vienna Ab initio Simulation Package (VASP). Through a guided example, participants will learn how to prepare and
perform calculations to obtain material properties, including structural relaxation, self-consistent field (SCF) calculations, electrostatic potential analysis, density of states, and electronic band structure calculations. By the end of the workshop, attendees will have gained an overall
understanding of both the theoretical foundations of DFT and its practical application in computational materials research, providing a solid basis for future work in molecular simulations and computational materials science.

Requirements

Participants are required to have the following software installed prior to the workshop:

• VESTA, for the visualization and analysis of structures and computational results.
• A terminal application (Windows or Linux) for the execution and management of
  computational workflows.

References

1. Jain, A., Shin, Y., & Persson, K. A. (2016). Computational predictions of energy materials using
   density functional theory. Nature Reviews Materials, 1, 15004.
   https://doi.org/10.1038/natrevmats.2015.4

Molecular spectroscopy simulations with Density Functional Theory

Luis Lopez

Abstract.

This workshot offers an introduction to molecular spectroscopy simulations, specifically infrared and UV-vis, which are powerful tools to validate experimental results, and understand chemical behaviors in material science. Participants will learn how to model, process, analyze and validate spectroscopic data from quantum chemical calculations applied to molecular examples The focus will be on developing skills to acquire valid simulated spectroscopic data employing the ORCA open access quantum chemical package. Attendees will gain hands-on experience on the software basic handling, spectra postprocessing tools, and further correlating structure with spectral information.

By the end of the workshop, participants will understand how vibrational and electronic spectra give insight structure, interactions and electronic properties of molecules.

References

1. F. Neese, The ORCA program system, WIREs Computational Molecular Science 2 (2012)
   73–78. https://doi.org/https://doi.org/10.1002/wcms.81.
   
2. H. Zhang, J. Hu, J. Zhao, Y. Zhang, Spectrometric measurements and DFT studies on new
   complex of copper (II) with 2-((E)-9-ethyl-3-(2-(6-(4-methylpyridin-2-yl)pyridin-3-yl)vinyl)-
   9H-carbazole, Spectrochim. Acta A Mol. Biomol. Spectrosc. 168 (2016) 78–85.
   https://doi.org/10.1016/j.saa.2016.05.051.