Author: ["Edvinas Orentas","Marco Lista","Nai-Ti Lin","Naomi Sakai","Stefan Matile"]
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Abstract
Self-sorting on surfaces is one of the big challenges that must be addressed in preparing the organic materials of the future. Here, we introduce a theoretical framework for templated self-sorting on surfaces, and validate it experimentally. In our approach, the transcription of two-dimensional information encoded in a monolayer on the surface into three-dimensional supramolecular architectures is quantified by the intrinsic templation efficiency, a thickness-independent value describing the fidelity of transcription per layer. The theoretical prediction that exceedingly high intrinsic efficiencies will be needed to experimentally observe templated self-sorting is then confirmed experimentally. Intrinsic templation efficiencies of up to 97%, achieved with a newly introduced templated synthesis strategy, result in maximal 47% effective templation efficiency at a thickness of 70 layers. The functional relevance of surface-templated self-sorting and meaningful dependences of templation efficiencies on structural modifications are demonstrated. The self-sorting of molecular building blocks should allow 2D surface patterns to be transcribed into 3D functional materials. Here, a non-empirical approach to the templated synthesis of supramolecular architectures on surfaces is reported, starting with a theoretical model and followed by comprehensive experimental validation, including direct evidence for functional relevance of the produced materials. Cite this article
Orentas, E., Lista, M., Lin, NT. et al. A quantitative model for the transcription of 2D patterns into functional 3D architectures. Nature Chem 4, 746–750 (2012). https://doi.org/10.1038/nchem.1429 