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We report that differences in ring strain enthalpy betweencisandtransisomers of sila-cycloheptene provide a driving force for both polymerization and depolymerizationviaolefin metathesis. 

Flexible and lightweight sensors can assess their environment for applications that include wearables for health monitoring and soft robotics. 

Four unsaturated poly(carbooligosilane)s (P1–P4) were prepared via acyclic diene metathesis polycondensation of new oligosilane diene monomers (1–4). These novel polymers with varying main-chain Si incorporation have high trans internal olefin stereochemistry (ca. 80%) and molecular weights (9500–21,700 g mol–1). Postpolymerization epoxidation converted all alkene moieties to epoxides and rendered the polymers (P5–P8) more electrophilic, which allowed for single-molecule force spectroscopy studies via a modified atomic force microscope setup with a silicon tip and cantilever. The single-chain elasticity of the polycarbooligosilanes decreased with increasing numbers of Si–Si bonds, a finding reproduced by quantum chemical calculations. 

Over the past 20 years, the field of polymer mechanochemistry has amassed a toolbox of mechanophores that translate mechanical energy into a variety of functional responses ranging from color change to small-molecule release. These productive chemical changes typically occur at the length scale of a few covalent bonds (Å) but require large energy inputs and strains on the micro-to-macro scale in order to achieve even low levels of mechanophore activation. The minimal activation hinders the translation of the available chemical responses into materials and device applications. The mechanophore activation challenge inspires core questions at yet another length scale of chemical control, namely: What are the molecular-scale features of a polymeric material that determine the extent of mechanophore activation? Further, how do we marry advances in the chemistry of polymer networks with the chemistry of mechanophores to create stress-responsive materials that are well suited for an intended application? In this Perspective, we speculate as to the potential match between covalent polymer mechanochemistry and recent advances in polymer network chemistry, specifically, topologically controlled networks and the hierarchical material responses enabled by multi-network architectures and mechanically interlocked polymers. Both fundamental and applied opportunities unique to the union of these two fields are discussed. 

The cis- and trans-isomers of a silacycloheptene were selectively synthesized by the alkylation of a silyl dianion, a novel approach to strained cycloalkenes. The trans-silacycloheptene (trans-SiCH) was significantly more strained than the cis isomer, as predicted by quantum chemical calculations and confirmed by crystallographic signatures of a twisted alkene. Each isomer exhibited distinct reactivity toward ring-opening metathesis polymerization (ROMP), where only trans-SiCH afforded high-molar-mass polymer under enthalpy-driven ROMP. Hypothesizing that the introduction of silicon might result in increased molecular compliance at large extensions, we compared poly(trans-SiCH) to organic polymers by single-molecule force spectroscopy (SMFS). Force-extension curves from SMFS showed that poly(trans-SiCH) is more easily overstretched than two carbon-based analogues, polycyclooctene and polybutadiene, with stretching constants that agree well with the results of computational simulations. 

As a machine-recognizable representation of polymer connectivity, BigSMILES line notation extends SMILES from deterministic to stochastic structures. The same framework that allows BigSMILES to accommodate stochastic covalent connectivity can be extended to non-covalent bonds, enhancing its value for polymers, supramolecular materials, and colloidal chemistry. Non-covalent bonds are captured through the inclusion of annotations to pseudo atoms serving as complementary binding pairs, minimal key/value pairs to elaborate other relevant attributes, and indexes to specify the pairing among potential donors and acceptors or bond delocalization. Incorporating these annotations into BigSMILES line notation enables the representation of four common classes of non-covalent bonds in polymer science: electrostatic interactions, hydrogen bonding, metal–ligand complexation, and π–π stacking. The principal advantage of non-covalent BigSMILES is the ability to accommodate a broad variety of non-covalent chemistry with a simple user-orientated, semi-flexible annotation formalism. This goal is achieved by encoding a universal but non-exhaustive representation of non-covalent or stochastic bonding patterns through syntax for (de)protonated and delocalized state of bonding as well as nested bonds for correlated bonding and multi-component mixture. By allowing user-defined descriptors in the annotation expression, further applications in data-driven research can be envisioned to represent chemical structures in many other fields, including polymer nanocomposite and surface chemistry.