Data Set for Optimization and Simulation of Translucent Steel Using Genetic Algorithms and DFT-Based Calculations

Dataset Description This dataset accompanies the theoretical study on the development of an innovative material called "translucent steel." The study aimed to combine high mechanical strength with optical translucency, utilizing genetic algorithms for optimizing structural and optical properties, along with Density Functional Theory (DFT)-based calculations. The dataset includes: Input parameters and results from calculations performed using the ORCA software. Python scripts used for automating analyses, generating electron density maps, and processing results. Detailed results from the genetic algorithms, including fitness evolution and optimal combinations tested. Graphs and tables illustrating refractive indices, elastic modulus, and optimized structural properties. This dataset is valuable for researchers in materials science, computational modeling, and applications of artificial intelligence in the development of advanced materials. It also provides a foundation for experimental validation of advanced metallic composites. Keywords: Translucent Steel, Genetic Algorithms, DFT, Materials Science, ORCA, Computational Modeling.