Observing polymerization in 2D dynamic covalent polymers


The quality of crystalline two-dimensional (2D) polymers(1-6) is intimately related to the elusive polymerization and crystallization processes. Understanding the mechanism of such processes at the (sub)molecular level is crucial to improve predictive synthesis and to tailor material properties for applications in catalysis(7-10) and (opto)electronics(11,12), among others(13-18). We characterize a model boroxine 2D dynamic covalent polymer, by using in situ scanning tunnelling microscopy, to unveil both qualitative and quantitative details of the nucleation-elongation processes in real time and under ambient conditions. Sequential data analysis enables observation of the amorphous-tocrystalline transition, the time-dependent evolution of nuclei, the existence of 'non-classical' crystallization pathways and, importantly, the experimental determination of essential crystallization parameters with excellent accuracy, including critical nucleus size, nucleation rate and growth rate. The experimental data have been further rationalized by atomistic computer models, which, taken together, provide a detailed picture of the dynamic on-surface polymerization process. Furthermore, we show how 2D crystal growth can be affected by abnormal grain growth. This finding provides support for the use of abnormal grain growth (a typical phenomenon in metallic and ceramic systems) to convert a polycrystalline structure into a single crystal in organic and 2D material systems.




Science & Technology - Other Topics


Zhan, GL; Cai, ZF; Strutynski, K; Yu, LH; Herrmann, N; Martinez-Abadia, M; Melle-Franco, M; Mateo-Alonso, A; De Feyter, S

nossos autores


We thank L. Verstraete and N. Bilbao for helpful discussions. We thank Y. Liao for helping with the preparation of the manuscript. We thank Y. Zhang for helping with data analysis. This work was supported by the Research Foundation -Flanders (FWO), in part by FWO under EOS 30489208, the Marie Sklodowska Curie ETN project ULTIMATE (GA-813036), and KU Leuven Internal Grant 3E180504, China Scholarship Council (201908350094), the Basque Foundation for Science (Ikerbasque), POLYMAT, the University of the Basque Country (Grupo de Investigacion GIU17/054), Diputacion Foral de Guipuzkoa, Gobierno Vasco (PIBA and BERC programmes), Gobierno de Espana (Ministerio de Economia y Competitividad CTQ2016-77970-R). Technical and human support provided by SGIker of UPV/EHU and European funding (ERDF and ESF) is acknowledged. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 722951). This project has received funding from the European Union ' s Horizon 2020 research and innovation programme under grant agreement no. 664878 and no. 899895. In addition, support through the project IF/00894/2015, the advanced computing CPCA/A2/2524/2020 granting access to the Navigator cluster at LCA-UC and within the scope of the project CICECO-Aveiro Institute of Materials, UIDB/50011/2020 & UIDP/50011/2020 funded by national funds through the Portuguese Foundation for Science and Technology I.P./MCTES is gratefully acknowledged.

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