Mehmet Bozuyla, Alpaslan Bayrakdar, Yusuf Sert, Hasan Huseyin Kart, Sevgi Ozdemir Kart, Prasath Manivannan, Mehmet Hakkı Alma
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引用次数: 0
Abstract
The analysis and interpretation of theoretical results remain significant challenges for researchers in computational chemistry, particularly when working with molecules containing a large number of atoms. The manual selection, organization, and interpretation of desired parameters from output files generated by computational tools can be error-prone, tedious, and time-intensive, often taking days to complete. This study introduces the Computational Chemistry Parameter (CCPE), providing extraction, formatting, and presentation of the computational data obtained from Gaussian and VEDA programs. By integrating outputs from the widely used GAUSSIAN and VEDA programs, CCPE provides an efficient, user-friendly solution for extracting and organizing key data such as vibrational modes, frequency assignments, optimization parameters, and molecular orbital data. This tool significantly reduces the time required for these tasks from several days to a matter of minutes, while minimizing the likelihood of errors. The CCPE software, developed using the C# programming language, emphasizes reliability and adaptability, offering researchers a practical means of handling complex computational data. Through its ability to generate publication-ready outputs in widely accepted formats, CCPE aims to enhance productivity and data accuracy, presenting a transformative step in the field of computational chemistry.
期刊介绍:
This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.