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Abstract
Identifying all energetically relevant conformers is crucial for accurate quantum chemical predictions of molecular and material properties. To address this, a variety of powerful tools and methods have been developed for efficiently exploring often vast conformational spaces. Among these is the open-source toolkit OpenBabel, which offers multiple conformer generation algorithms and user-adjustable parameters that can significantly affect search outcomes. In this study, we systematically investigate how different methods and parameter choices in OpenBabel influence the conformer search results, using oligothiophenes as model systems. Oligothiophenes are ideal reference compounds due to their well-characterized conformational landscapes and scalability to larger systems. Our workflow involves: (i) generating conformers with OpenBabel, (ii) clustering them based on geometric similarity, and (iii) optimizing the most energetically favorable representatives of each cluster using density functional theory (DFT). We further explore whether additional conformational space can be accessed by reinitiating OpenBabel searches from DFT-relaxed structures, thereby possibly identifying previously overlooked but energetically relevant conformers. Finally, we demonstrate the transferability of our workflow by applying it to the more complex and technologically important non-fullerene acceptor molecule Y6. This work provides a robust framework for selecting suitable OpenBabel parameters and developing reliable workflows for conformer identification through hierarchical clustering and DFT-based refinement.
Supplementary materials
Title
Supporting Information
Description
The Supporting Information (SI) provides a comprehensive overview of the conformational search and clustering analyses conducted for oligothiophenes and Y6 molecules using the OpenBabel-based genetic algorithm workflow.
Section 1 details the results of conformer generation for dithiophene, trithiophene, and 4-thiophene, including representative structures, clustering dendrograms, and RMSD heatmaps.
Section 2 presents an extensive analysis of conformers for the Y6 molecule, with multiple genetic algorithm searches starting from different initial structures.
Section 3 compares the developed workflow to the CREST algorithm.
Section 4 contrasts hierarchical clustering and k-means clustering methods.
Section 5 lists representative structures from different conformer families across multiple searches for Y6.
Section 6 compiles the total electronic energies of the Y6 conformers obtained under various optimization protocols and initial conditions, allowing direct comparison across methods.
Figures include conformer structures, RMSD heatmaps, clustering dendrograms, and energy tables, supporting the reproducibility and clarity of the workflow and results.
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