Nested non-covalent interactions expand the functions of supramolecular polymer networks.

Supramolecular polymer networks contain non-covalent cross-links that enable access to broadly tunable mechanical properties and stimuli-responsive behaviors; the incorporation of multiple unique non-covalent cross-links within such materials further expands their mechanical responses and functionality. To date, however, the design of such materials has been accomplished through discrete combinations of distinct interaction types in series, limiting materials design logic. Here we introduce the concept of leveraging "nested" supramolecular crosslinks, wherein two distinct types of non-covalent interactions exist in parallel, to control bulk material functions. To demonstrate this concept, we use polymer-linked Pd2L4 metal-organic cage (polyMOC) gels that form hollow metal-organic cage junctions through metal-ligand coordination and can exhibit well-defined host-guest binding within their cavity. In these "nested" supramolecular network junctions, the thermodynamics of host-guest interactions within the junctions affect the metal-ligand interactions that form those junctions, ultimately translating to substantial guest-dependent changes in bulk material properties that could not be achieved in traditional supramolecular networks with multiple interactions in series.

A Model Ensemble Approach Enables Data-Driven Property Prediction for Chemically Deconstructable Thermosets in the Low-Data Regime.

Thermosets present sustainability challenges that could potentially be addressed through the design of deconstructable variants with tunable properties; however, the combinatorial space of possible thermoset molecular building blocks (e.g., monomers, cross-linkers, and additives) and manufacturing conditions is vast, and predictive knowledge for how combinations of these molecular components translate to bulk thermoset properties is lacking. Data science could overcome these problems, but computational methods are difficult to apply to multicomponent, amorphous, statistical copolymer materials for which little data exist. Here, leveraging a data set with 101 examples, we introduce a closed-loop experimental, machine learning (ML), and virtual screening strategy to enable predictions of the glass transition temperature (Tg) of polydicyclopentadiene (pDCPD) thermosets containing cleavable bifunctional silyl ether (BSE) comonomers and/or cross-linkers with varied compositions and loadings. Molecular features and formulation variables are used as model inputs, and uncertainty is quantified through model ensembling, which together with heavy regularization helps to avoid overfitting and ultimately achieves predictions within <15 °C for thermosets with compositionally diverse BSEs. This work offers a path to predicting the properties of thermosets based on their molecular building blocks, which may accelerate the discovery of promising plastics, rubbers, and composites with improved functionality and controlled deconstructability.

Endohedrally Functionalized Metal-Organic Cage-Cross-Linked Polymer Gels as Modular Heterogeneous Catalysts.

The immobilization of homogeneous catalysts onto supports to improve recyclability while maintaining catalytic efficiency is often a trial-and-error process limited by poor control of the local catalyst environment and few strategies to append catalysts to support materials. Here, we introduce a modular heterogenous catalysis platform that addresses these challenges. Our approach leverages the well-defined interiors of self-assembled Pd12L24 metal-organic cages/polyhedra (MOCs): simple mixing of a catalyst-ligand of choice with a polymeric ligand, spacer ligands, and a Pd salt induces self-assembly of Pd12L24-cross-linked polymer gels featuring endohedrally catalyst-functionalized junctions. Semi-empirical calculations show that catalyst incorporation into the MOC junctions of these materials has minimal affect on the MOC geometry, giving rise to well-defined nanoconfined catalyst domains as confirmed experimentally using several techniques. Given the unique network topology of these freestanding gels, they are mechanically robust regardless of their endohedral catalyst composition, allowing them to be physically manipulated and transferred from one reaction to another to achieve multiple rounds of catalysis. Moreover, by decoupling the catalyst environment (interior of MOC junctions) from the physical properties of the support (the polymer matrix), this strategy enables catalysis in environments where homogeneous catalyst analogues are not viable, as demonstrated for the Au(I)-catalyzed cyclization of 4-pentynoic acid in aqueous media.

Conversion of Imine to Oxazole and Thiazole Linkages in Covalent Organic Frameworks.

Imine-linked ILCOF-1 based on 1,4-phenylenediamine and 1,3,6,8-tetrakis(4-formylphenyl)pyrene was converted through consecutive linker substitution and oxidative cyclization to two isostructural covalent organic frameworks (COFs), having thiazole and oxazole linkages. The completeness of the conversion was assessed by infrared and solid-state NMR spectroscopies, and the crystallinity of the COFs was confirmed by powder X-ray diffraction. Furthermore, the azole-linked COFs remain porous, as shown by nitrogen sorption experiments. The materials derived in this way demonstrate increased chemical stability, relative to the imine-linked starting material. This constitutes a facile method for accessing COFs and linkages that are otherwise difficult to crystallize due to their inherently limited microscopic reversibility.