ArticleJournal of chemical theory and computation2020
Reliable Computational Prediction of the Supramolecular Ordering of Complex Molecules under Electrochemical Conditions.
Article in Journal of chemical theory and computation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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Who cites it
3 citing papers in PubMed.
- Guided Adaptive Diffusion: An Evolutionary Framework for Multimodal Atomistic Structure Prediction.Journal of chemical information and modeling · 2026Article
- Interfacial Charge Transfer Influences Thin-Film Polymorphism.The journal of physical chemistry. C, Nanomaterials and interfaces · 2022Article
- Reliable Computational Prediction of the Supramolecular Ordering of Complex Molecules under Electrochemical Conditions.Journal of chemical theory and computation · 2020Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We propose a computationally lean, two-stage approach that reliably predicts self-assembly behavior of complex charged molecules on metallic surfaces under electrochemical conditions. Stage one uses ab initio simulations to provide reference data for the energies (evaluated for archetypical configurations) to fit the parameters of a conceptually much simpler and computationally less expensive force field of the molecules: classical, spherical particles, representing the respective atomic entities; a flat and perfectly conducting wall represents the metallic surface. Stage two feeds the energies that emerge from this force field into highly efficient and reliable optimization techniques to identify via energy minimization the ordered ground-state configurations of the molecules. We demonstrate the power of our approach by successfully reproducing, on a semiquantitative level, the intricate supramolecular ordering observed experimentally for PQP
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Registered trials
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