Taming Two-Dimensional Polymerization by a Machine-Learning Discovered Crystallization Model.

Rapidly synthesizing high-quality two-dimensional covalent organic frameworks (2D COFs) is crucial to their practical applications. Here, we use a machine-learning approach that overcomes the challenges associated with bottom-up model derivation for the non-classical 2D COF crystallization processes. The resulting model, referred to as NEgen1, establishes correlations among the induction time, nucleation rate, growth rate, bond-forming rate constants, and common solution synthesis conditions for 2D COFs that grow by a nucleation-elongation mechanism. The results elucidate the detailed competition between the nucleation and growth dynamics in solution, which has been inappropriately described previously by classical, empirical models with assumptions invalid for 2D COF polymerization. By understanding the dynamic processes at play, the NEgen1 model reveals a simple strategy of gradually increasing monomer addition speed for growing large 2D COF crystals. This insight enables us to rapidly synthesize large COF-5 colloids, which could only be achieved previously by prolonged reaction times or by introducing chemical modulators. These results highlight the potential for systematically improving the crystal quality of 2D COFs, which has wide-reaching relevance for many of the applications for which 2D COFs are speculated to be valuable.

Intrinsically thermally conductive polymers.

Here, we describe the design features that lead to intrinsically thermally conductive polymers. Though polymers are conventionally assumed to be thermal insulators (<0.3 W m-1 K-1), significant efforts by the thermal transport community have shown that polymers can be intrinsically thermally conductive (>1.0 W m-1 K-1). However, these findings have not yet driven comprehensive synthetic efforts to expose how different macromolecular features impact thermal conductivity. Preliminary theoretical and experimental investigations have revealed that high k polymers can be realized by enhancing the alignment, crystallinity, and intermolecular interactions. While a holistic mechanistic framework does not yet exist for thermal transport in polymeric materials, contemporary literature suggests that phonon-like heat carriers may be operative in macromolecules that meet the abovementioned criteria. In this review, we offer a perspective on how high thermal conductivity polymers can be systematically engineered from this understanding. Reports for several classes of macromolecules, including linear polymers, network polymers, liquid-crystalline polymers, and two-dimensional polymers substantiate the design principles we propose. Throughout this work, we offer opportunities for continued fundamental and technological development of polymers with high thermal conductivity.