2026-10-14T07:08:30Zhttps://www.radar-service.eu/oai/OAIHandler

10.35097/m137bhkrvh8ufk5q2026-10-09T10:55:04Zradar4kit

https://dx.doi.org/10.35097/m137bhkrvh8ufk5q Almeida de Campos, Leonardo Sheppard, Thomas L. Grunwaldt, Jan-Dierk GC-MS ABE Calculator Karlsruhe Institute of Technology 2026 Chemistry dataset Software info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc/4.0/legalcode This dataset contains a Python-based graphical user interface (GUI) workflow for the evaluation of GC–MS data obtained from catalytic upgrading of acetone–butanol–ethanol (ABE) mixtures. The tool processes classified peak tables exported as .csv files and calculates product selectivity based on user-defined filtering criteria. Only compounds labeled as KEEP are considered, while reactants are excluded from the selectivity basis. In addition, the workflow enables the calculation of reactant conversion using either a baseline (0 h) dataset or manually defined initial area percentages. The software provides multiple levels of analysis, including family-based selectivity, carbon number distributions, carbon binning (C2–C6 and C7–C15), and selected product tracking. Results are visualized through an interactive PyQt6-based interface and exported as structured .csv files. Input data must follow a tabulated GC–MS format with columns such as retention time, compound name, molecular formula, area percentage, classification, and chemical family. This repository represents the archived version associated with the corresponding scientific work. The actively maintained version of the code is available in the linked GitHub repository. LINK: (https://github.com/Leonardolac97/Gc-Ms_ABE_calculator) The workflow is implemented as a standalone Python application using PyQt6 for the graphical interface. The tool requires a single input file in .csv format containing classified GC–MS peak data. Optionally, a baseline dataset (0 h) can be provided to compute reactant conversion. Alternatively, initial reactant area percentages (A0) can be manually defined within the interface. Data are loaded from local directories, and an output folder is automatically generated to store processed results, including selectivity tables, carbon distributions, and conversion data. GC-MS ABE Catalysis Data analysis PyQt6 matplotlib https://publikationen.bibliothek.kit.edu/1000192033 application/x-tar