| Summary: | Abstract: Density Functional Theory (DFT) has emerged as a cornerstone in various scientific disciplines, providing invaluable insights into the electronic structure and properties of molecules and materials. In this context, the development of computational tools capable of efficiently analyzing DFT results is crucial. Here, we introduce a novel Shiny application designed to streamline the analysis and visualization of infrared spectra obtained through DFT calculations using ORCA. This application offers a user-friendly interface for researchers to interpret complex spectral data, facilitating deeper understanding and accelerating discoveries in fields ranging from chemistry and materials science to biology and environmental science. Introduction: Density Functional Theory (DFT) has revolutionized computational chemistry and materials science by offering a powerful framework for predicting and interpreting the behavior of molecules and materials at the atomic level. By solving the Schrödinger equation for the electronic structure of a system, DFT enables researchers to explore a wide range of chemical phenomena, from molecular bonding and reactivity to electronic and optical properties. One of the most valuable applications of DFT is the simulation of infrared (IR) spectra, which provides crucial information about molecular vibrations and intermolecular interactions. Significance of the Program: Our Shiny application represents a significant advancement in the field of computational chemistry and spectroscopy. By automating the process of parsing and analyzing ORCA output files, researchers can now effortlessly generate and interpret IR spectra with unprecedented efficiency and accuracy. The program extracts essential spectral parameters, such as peak frequencies and intensities, and visualizes them in an intuitive manner, allowing users to identify functional groups, characterize molecular structures, and explore chemical reactivity. Features and Functionality: The Shiny application offers a range of features ...
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