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  1. Abstract

    Polyethylene (PE) is the most widely produced synthetic polymer. By installing chemically cleavable bonds into the backbone of PE, it is possible to produce chemically deconstructable PE derivatives; to date, however, such designs have primarily relied on carbonyl‐ and olefin‐related functional groups. Bifunctional silyl ethers (BSEs; SiR2(OR′2)) could expand the functional scope of PE mimics as they possess strong Si−O bonds and facile chemical tunability. Here, we report BSE‐containing high‐density polyethylene (HDPE)‐like materials synthesized through a one‐pot catalytic ring‐opening metathesis polymerization (ROMP) and hydrogenation sequence. The crystallinity of these materials can be adjusted by varying the BSE concentration or the steric bulk of the Si‐substituents, providing handles to control thermomechanical properties. Two methods for chemical recycling of HDPE mimics are introduced, including a circular approach that leverages acid‐catalyzed Si−O bond exchange with 1‐propanol. Additionally, despite the fact that the starting HDPE mimics were synthesized by chain‐growth polymerization (ROMP), we show that it is possible to recover the molar mass and dispersity of recycled HDPE products using step‐growth Si−O bond formation or exchange, generating high molecular weight recycled HDPE products with mechanical properties similar to commercial HDPE.

     
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  2. Abstract

    High energy photons (λ < 400 nm) are frequently used to initiate free radical polymerizations to form polymer networks, but are only effective for transparent objects. This phenomenon poses a major challenge to additive manufacturing of particle‐reinforced composite networks since deep light penetration of short‐wavelength photons limits the homogeneous modification of physicochemical and mechanical properties. Herein, the unconventional, yet versatile, multiexciton process of triplet–triplet annihilation upconversion (TTA‐UC) is employed for curing opaque hydrogel composites created by direct‐ink‐write (DIW) 3D printing. TTA‐UC converts low energy red light (λmax = 660 nm) for deep penetration into higher‐energy blue light to initiate free radical polymerizations within opaque objects. As proof‐of‐principle, hydrogels containing up to 15 wt.% TiO2filler particles and doped with TTA‐UC chromophores are readily cured with red light, while composites without the chromophores and TiO2loadings as little as 1–2 wt.% remain uncured. Importantly, this method has wide potential to modify the chemical and mechanical properties of complex DIW 3D‐printed composite polymer networks.

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

     
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    Free, publicly-accessible full text available January 1, 2025
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  8. Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts. 
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    Free, publicly-accessible full text available December 12, 2024
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