Search for: All records

A polymer coating autonomously reports damageviafluorescence from a force-induced retro-Diels–Alder reaction. The optical signal correlates with impact energy, enabling real-time, equipment-free damage detection, even in pigmented coatings. 

Abstract The field of polymer mechanochemistry has been revolutionized by implementing force-responsive functional groups—mechanophores. The rational design of mechanophores enables the controlled use of force to achieve constructive molecular reactivity and material responses. While a variety of mechanophores have been developed, this Mini Review focuses on cyclobutane, which has brought valuable insights into molecular reactivity and dynamics as well as innovations in materials. We discuss its reactivity and mechanism, dynamics and stereoselectivity, as well as impacts on material properties. 

Integrating mechanophores into multiple-network elastomers enables 20-fold toughness enhancement and 37% activation and provides insights into the toughening mechanismviabond scission visualization. 

Abstract Synthetic plastics sourced from petroleum have gained widespread use since the 1950s. Polystyrene (PS) is one of the most extensively used plastics, as it is colorless, has high mechanical strength, and exhibits excellent chemical and thermal stability; however, it is also one of the least recycled plastics because of the high cost and low profit in recycling. Herein, we demonstrate a mechanochemical recycling approach that allows PS to be efficiently degraded into benzene when it is ground in a ball mill with AlCl₃. For example, when 165 kDa PS pellets are milled with AlCl₃, the extent of degradation reaches 90% at 15 min. Isotope labeling experiments indicate that both ambient water and the polymer backbone can be proton sources for the formation of benzene. The benzene generated in the mechanochemical degradation can be used to synthesize styrene, which can be repolymerized to produce polystyrene, allowing for the closed‐loop recycling of PS. In addition, a mechanochemical Friedel–Crafts acylation between the generated benzene and the subsequently added benzoic anhydride produces benzophenone in 40%–50% yield. The mechanochemical degradation process demonstrated here is solvent‐free, cost‐effective, and energy‐efficient, providing a promising route for the chemical recycling and upcycling of PS. 

The consumption of synthetic polymers has ballooned; so has the amount of post-consumer waste generated. The current polymer economy, however, is largely linear with most of the post-consumer waste being either landfilled or incinerated. The lack of recycling, together with the sizable carbon footprint of the polymer industry, has led to major negative environmental impacts. Over the past few years, chemical recycling technologies have gained significant traction as a possible technological route to tackle these challenges. In this regard, olefin metathesis, with its versatility and ease of operation, has emerged as an attractive tool. Here, we discuss the developments in olefin-metathesis-based chemical recycling technologies, including the development of new materials and the application of olefin metathesis to the recycling of commercial materials. We delve into structure–reactivity relationships in the context of polymerization–depolymerization behavior, how experimental conditions influence deconstruction outcomes, and the reaction pathways underlying these approaches. We also look at the current hurdles in adopting these technologies and relevant future directions for the field. 

Graft polymers with various sidechain lengths and grafting densities are prepared usingtrans-cyclobutane-fused cyclooctene macromonomers; the solvent-free depolymerization of these graft polymers in the presence of a ruthenium catalyst is studied. 

Graft polymers are gaining increasing interest because of their unique architectural characteristics. We recently reported a novel type of depolymerizable graft polymer based on poly(trans-cyclobutane fused cyclooctene), in an effort to address the trade-off between depolymerizability and controlled grafting-through polymerization. In this work, we examine the thermal, mechanical, and morphological properties of a graft copolymer thermoplastic material prepared by copolymerizing poly(L-lactide) and margaric acid-based macromonomers. A copolymerization kinetics study reveals that the two macromonomers are incorporated almost randomly and that the domain spacing measured from small-angle X-ray scattering is consistent with the random distribution. An investigation of the crystallization behavior suggests that proper thermal treatment is required to maximize, or to even observe crystallinity. The physical states of the soft and hard domains, whether melt, glassy, or semicrystalline, significantly impact the tensile properties of the resulting copolymer materials. Finally, the rheological properties and morphological features are discussed. 

Word vector embeddings have been shown to contain and amplify biases in the data they are extracted from. Consequently, many techniques have been proposed to identify, mitigate, and attenuate these biases in word representations. In this paper, we utilize interactive visualization to increase the interpretability and accessibility of a collection of state-of-the-art debiasing techniques. To aid this, we present the Visualization of Embedding Representations for deBiasing (“VERB”) system, an open-source web-based visualization tool that helps users gain a technical understanding and visual intuition of the inner workings of debiasing techniques, with a focus on their geometric properties. In particular, VERB offers easy-to-follow examples that explore the effects of these debiasing techniques on the geometry of high-dimensional word vectors. To help understand how various debiasing techniques change the underlying geometry, VERB decomposes each technique into interpretable sequences of primitive transformations and highlights their effect on the word vectors using dimensionality reduction and interactive visual exploration. VERB is designed to target natural language processing (NLP) practitioners who are designing decision-making systems on top of word embeddings, and also researchers working with the fairness and ethics of machine learning systems in NLP. It can also serve as a visual medium for education, which helps an NLP novice understand and mitigate biases in word embeddings.