DockOnSurf: A Python Code for the High-Throughput Screening of Flexible Molecules Adsorbed on Surfaces

• Published in: Journal of chemical information and modeling 2021-07, Vol.61 (7), p.3386-3396
• Main Authors: Martí, Carles, Blanck, Sarah, Staub, Ruben, Loehlé, Sophie, Michel, Carine, Steinmann, Stephan N
• Format: Article
• Language: English
• Subjects: Adsorbates; Adsorption; Chemical Sciences; Computational Chemistry; Configurations; Hematite; Nanoparticles; Optimization; or physical chemistry; Python; Screening; Sorbitol; Surface chemistry; Theoretical and; Tribology; Workflow
• ISSN: 1549-9596; 1549-960X
• DOI: 10.1021/acs.jcim.1c00256

We present the open-source python package DockOnSurf which automates the generation and optimization of low-energy adsorption configurations of molecules on extended surfaces and nanoparticles. DockOnSurf is especially geared toward handling polyfunctional flexible adsorbates. The use of this high-throughput workflow allows us to carry out the screening of adsorbate-surface configurations in a systematic, customizable, and traceable way, while keeping the focus on the chemically relevant structures. The screening strategy consists in splitting the exploration of the adsorbate-surface configurational space into chemically meaningful domains, that is, by choosing among different conformers to adsorb, surface adsorption sites, adsorbate anchoring points, and orientations and allowing dissociation of (acidic) protons. We demonstrate the performance of the main features based on varying examples, ranging from CO adsorption on a gold nanoparticle to sorbitol adsorption on hematite. Through the use of the presented program, we aim to foster efficiency, traceability, and ease of use in research within tribology, catalysis, nanoscience, and surface science in general.