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Vitrimer is an emerging class of sustainable polymers with self-healing capabilities enabled by dynamic covalent adaptive networks. However, their limited molecular diversity constrains their property space and potential applications.…
Vitrimers are a relatively new class of polymer materials with unique properties offered by cross-links that can undergo associative exchange dynamics. We here present a new class of vitrimers based on poly(methyl acrylate) with cross-links…
The design/discovery of new materials is highly non-trivial owing to the near-infinite possibilities of material candidates, and multiple required property/performance objectives. Thus, machine learning tools are now commonly employed to…
The demand for innovative synthetic polymers with improved properties is high, but their structural complexity and vast design space hinder rapid discovery. Machine learning-guided molecular design is a promising approach to accelerate…
Artificial intelligence (AI) promotes the polymer design paradigm from a traditional trial-and-error approach to a data-driven style. Achieving high thermal conductivity (TC) for intrinsic polymers is urgent because of their importance in…
Vitrimers are polymer networks that, thanks to covalent bond exchange, combine desirable properties of thermoplastic and thermosets, such as flowability and insolubility. For this reason, vitrimers are considered to be good candidates for a…
Poly(ethylene terephthalate) (PET), a widely used thermoplastic in packaging, textiles, and engineering applications, is valued for its strength, clarity, and chemical resistance. Increasing environmental impact concerns and regulatory…
The generation of molecules with Artificial Intelligence (AI) is poised to revolutionize materials discovery. Potential applications range from development of potent drugs to efficient carbon capture and separation technologies. However,…
Polymers underpin applications across energy, healthcare, and materials science, yet their vast chemical space makes systematic discovery challenging. Most machine learning approaches represent polymers as molecular graphs of a single…
The success of the Materials Genome Initiative has led to opportunities for data-driven approaches for materials discovery. The recent development of Polymer Genome (PG), which is a machine learning (ML) based data-driven informatics…
Vitrimers are a special class of polymers that undergo dynamic cross-linking under thermal stimuli. Their ability to exchange covalent bonds can be harnessed to mitigate damage in a composite or to achieve recyclable aerospace composites.…
Traditional plastics demand a choice between durability (thermosets) and reprocessability (thermoplastics). Vitrimers are a recent class of polymer network combining both these qualities. Their increased cost of production can be offset by…
We investigate the construction of generative models capable of encoding physical constraints that can be hard to express explicitly. For the problem of inverse material design, where one seeks to design a material with a prescribed set of…
Vitrimers offer a promising sustainable alternative to conventional epoxies due to their recyclability. Vitrimers are covalent adaptive networks where some bonds can break and reform above the vitrimer transition temperature. While this can…
Vitrimers are a class of crosslinked polymer that are capable of undergoing bond exchange reactions, allowing structural reorganization while maintaining overall network integrity. Two key features that are particularly relevant when this…
Designing novel materials that possess desired properties is a central need across many manufacturing industries. Driven by that industrial need, a variety of algorithms and tools have been developed that combine AI (machine learning and…
Polymer packaging plays a crucial role in food preservation but poses major challenges in recycling and environmental persistence. To address the need for sustainable, high-performance alternatives, we employed a polymer informatics…
Vitrimers are polymer networks that can undergo bond exchange reactions. They dynamically rearrange their structures while maintaining their overall integrity, thus resulting in unique properties such as self-healing, reprocessability,…
We present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compressed into a three-dimensional latent space using a…
Glass transition temperature ($T_{\text{g}}$) plays an important role in controlling the mechanical and thermal properties of a polymer. Polyimides are an important category of polymers with wide applications because of their superior heat…