ArticleBeilstein journal of nanotechnology2020
Detecting stable adsorbates of (1
Article in Beilstein journal of nanotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 27 citations in OpenAlex.
- Machine Learning Accelerated Global Search for Adsorption Geometries of Merocyanine Molecule on Hexagonal Boron Nitride.Journal of computational chemistry · 2026Article
- High-Yield WSACS applied materials & interfaces · 2024Article
- Article
- Accelerated Lignocellulosic Molecule Adsorption Structure Determination.Journal of chemical theory and computation · 2024Article
- Exploring the Conformers of an Organic Molecule on a Metal Cluster with Bayesian Optimization.Journal of chemical information and modeling · 2023Article
- Protective Coating Interfaces for Perovskite Solar Cell Materials: A First-Principles Study.ACS applied materials & interfaces · 2022Article
- Machine learning as a tool to engineer microstructures: Morphological prediction of tannin-based colloids using Bayesian surrogate models.MRS bulletin · 2022Article
- Article
- First-principles calculations of hybrid inorganic-organic interfaces: from state-of-the-art to best practice.Physical chemistry chemical physics : PCCP · 2021Article
- Efficient Amino Acid Conformer Search with Bayesian Optimization.Journal of chemical theory and computation · 2021Article
- Molecular assemblies on surfaces: towards physical and electronic decoupling of organic molecules.Beilstein journal of nanotechnology · 2021Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying the atomic structure of organic-inorganic interfaces is challenging with current research tools. Interpreting the structure of complex molecular adsorbates from microscopy images can be difficult, and using atomistic simulations to find the most stable structures is limited to partial exploration of the potential energy surface due to the high-dimensional phase space. In this study, we present the recently developed Bayesian Optimization Structure Search (BOSS) method as an efficient solution for identifying the structure of non-planar adsorbates. We apply BOSS with density-functional theory simulations to detect the stable adsorbate structures of (1
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