High-throughput experimentation for discovery of biodegradable polyesters

Multifunctional piezoelectric hydrogels under ultrasound stimulation boost chondrogenesis by recruiting autologous stem cells and activating the Ca2+/CaM/CaN signaling pathway

Articular cartilage, owing to the lack of undifferentiated stem cells after injury, faces significant challenges in reconstruction and repair, making it a major clinical challenge. Therefore, there is an urgent need to design a multifunctional hydrogels capable of recruiting autologous stem cells to achieve in situ cartilage regeneration. Here, our study investigated the potential of a piezoelectric hydrogel (Hyd6) for enhancing cartilage regeneration through ultrasound (US) stimulation. Hyd6 has multiple properties including injectability, self-healing capabilities, and piezoelectric characteristics. These properties synergistically promote stem cell chondrogenesis. The fabrication and characterization of Hyd6 revealed its excellent biocompatibility, biodegradability, and electromechanical conversion capabilities. In vitro and in vivo experiments revealed that Hyd6, when combined with US stimulation, significantly promotes the recruitment of autologous stem cells and enhances chondrogenesis by generating electrical signals that promote the influx of Ca2+, activating downstream CaM/CaN signaling pathways and accelerating cartilage formation. An in vivo study in a rabbit model of chondral defects revealed that Hyd6 combined with US treatment significantly improved cartilage regeneration, as evidenced by better integration of the regenerated tissue with the surrounding cartilage, greater collagen type II expression, and improved mechanical properties. The results highlight the potential of Hyd6 as a novel therapeutic approach for treating cartilage injuries, offering a self-powered, noninvasive, and effective strategy for tissue engineering and regenerative medicine.

Machine Learning for Developing Sustainable Polymers

Sustainable polymers from renewable resources have been gaining importance due to their recyclability and reduced environmental impact. However, their development through conventional trial-and-error methods remains inefficient and resource-intensive. Machine learning (ML) has emerged as a powerful tool in polymer science, enabling rapid prediction, and discovery of new chemicals and materials. In this review, we examine emerging trends in ML applications for sustainable polymer development, focusing on catalyst discovery, property optimization, and new polymer design. We analyze unique challenges in applying ML to sustainable polymers and evaluate proposed solutions, providing insights for future development in this rapidly evolving field.

Designing for degradation: the importance of considering biotic and abiotic polymer degradation

Considering the increasing global plastic demand, there is a critical need to gain insight into environmental processes that govern plastic degradation in order to inform novel design of sustainable polymers. Current biological degradation testing standards focus on formation of CO2 (i.e., mineralization) alone as a diagnostic, ultimately limiting identification of structure-degradation relationships in a timely fashion. This work developed a sequential abiotic (i.e., photodegradation and hydrolysis) and biotic degradation test and applied it to a suite of 18 polymers, including ten lab produced, novel polyhydroxyalkanoate polyesters, and eight commercially available, bio-based (i.e., polylactic acid and poly-3-hydroxybutyrate) and fossil-derived (i.e., polystyrene, polypropylene, low density polyethylene, poly(ethylene terephthalate) and tire rubber) polymers. Biomineralization alone following standard methods (i.e., ASTM 6691-17, ISO 23977-1 2020) underestimated polymer degradation up to two-fold over 28 days. Simulated sunlight enhanced the overall polymer degradation by mobilizing dissolved organic carbon (DOC). After photoirradiation, up to 100% of released dissolved organic carbon was bioavailable for marine microbes over 14 days. Photodegradation and hydrolysis could be explained by structural drivers in the commodity polymers, and the lab-synthesized polymers illustrated a limit to total degradation beyond which no enhancements in degradation were achieved. Taken together, this workflow allows for relatively fast experimental determination of environmentally relevant stimuli to help support eventual elucidation of structure-property relationships for enhanced a priori design of degradable polymers.

Circularity in polydiketoenamine thermoplastics via control over reactive chain conformation

Controlling the reactivity of bonds along polymer chains enables both functionalization and deconstruction with relevance to chemical recycling and circularity. Because the substrate is a macromolecule, however, understanding the effects of chain conformation on the reactivity of polymer bonds emerges as important yet underexplored. Here, we show how oxy-functionalization of chemically recyclable condensation polymers affects acidolysis to monomers through control over distortion and interaction energies in the rate-limiting transition states. Oxy-functionalization of polydiketoenamines at specific sites on either the amine or triketone monomer segments increased acidolysis rates by more than three orders of magnitude, opening the door to efficient deconstruction of linear chain architectures. These insights substantially broaden the scope of applications for polydiketoenamines in a circular manufacturing economy, including chemically recyclable adhesives for a diverse range of surfaces.

Polymer Biodegradation in Aquatic Environments: A Machine Learning Model Informed by Meta-Analysis of Structure-Biodegradation Relationships

Polymers are widely produced and contribute significantly to environmental pollution due to their low recycling rates and persistence in natural environments. Biodegradable polymers, while promising for reducing environmental impact, account for less than 2% of total polymer production. To expand the availability of biodegradable polymers, research has explored structure-biodegradability relationships, yet most studies focus on specific polymers, necessitating further exploration across diverse polymers. This study addresses this gap by curating an extensive aerobic biodegradation data set of 74 polymers and 1779 data points drawn from both published literature and 28 sets of original experiments. We then conducted a meta-analysis to evaluate the effects of experimental conditions, polymer structure, and the combined impact of polymer structure and properties on biodegradation. Next, we developed a machine learning model to predict polymer biodegradation in aquatic environments. The model achieved an Rtest2 score of 0.66 using Morgan fingerprints, detailed experimental conditions, and thermal decomposition temperature (Td) as the input descriptors. The model's robustness was supported by a feature importance analysis, revealing that substructure R-O-R in polyethers and polysaccharides positively influenced biodegradation, while molecular weight, Td, substructure -OC(═O)- in polyesters and polyalkylene carbonates, side chains, and aromatic rings negatively impacted it. Additionally, validation against the meta-analysis findings confirmed that predictions for unseen test sets aligned with established empirical biodegradation knowledge. This study not only expands our understanding across diverse polymers but also offers a valuable tool for designing environmentally friendly polymers.

Property Prediction of Bio-Derived Block Copolymer Thermoplastic Elastomers Using Graph Kernel Methods

Increasing the diversity of bio-based polymers is needed to address the combined problems of plastic pollution and greenhouse gas emissions. The magnitude of the problems necessitates rapid discovery of new materials; however, identification of appropriate chemistries maybe slow using current iterative methods. Machine learning (ML) methods could significantly expedite new material discovery and property identification. Here, PolyAGM, a ML algorithm using graph kernel methods, is introduced and used to predict the properties of block copolymers and identify the responsible structural 'motifs'. It applies a "fingerprinting" method to convert Graph representations of polymers into numerical vectors. The Graphs explicitly encode the entire copolymer of atoms and bonds such that the sequencing of chemical features and polymer chain length are included, alongside relevant stereochemical information. PolyAGM gives predictions for both thermal and mechanical properties that are in good agreement with experimental measurements. This work focuses on predicting the properties of bio-derived ABA-block polymer thermoplastic elastomers, but the general fingerprinting technique of PolyAGM should be relevant to other application fields.

Degradable poly(β-amino ester) microparticles for cleansing products and food fortification

Microplastic pollution is a pressing global crisis caused by the extensive use of nondegradable microplastic materials in daily activities. One effective approach to mitigate this issue is to replace nondegradable plastics with degradable materials that have properties amendable for targeted applications. Here we present the development of a degradable microparticle (MP) platform based on a poly(β-amino ester) (PAE) that degrades into sugar and amino acid derivatives. This PAE MP platform showed functional replacement of nondegradable microplastics used in cleansing products and food fortification. In cleansing products, PAE MPs effectively enhanced the cleansing efficiency of a representative rinse-off product and showed effective removal of potentially toxic elements, as an alternative of traditional nondegradable microbeads. In food fortification, PAE MPs provided robust protection for multiple essential vitamins and minerals against extensive cooking and storage conditions with rapid nutrient release in a simulated human digestion system. Collectively, these PAE MPs present a potential platform to replace microplastic usage on a global scale in many applications.

Development of poly(butylene oxalate-co-furanoate) copolymers with enhanced sustainability and hydrolytic degradability

Polyoxalate, a novel intrinsically hydrolysable polyester, garners significant interest for its high cost-effectiveness and versatility. However, concerns persist regarding its durability in practical applications. This study integrates bio-based poly(butylene furanoate) (PBF), which possesses remarkable barrier performance, into the poly(butylene oxalate) (PBOx) framework to synthesize poly(butylene oxalate‑co‑furanoate) (PBOF) with tunable degradation rates. The influence of incorporating BF units on thermal, crystalline, mechanical, and barrier properties was systematically analyzed. Results demonstrated the addition of BF units dramatically improved the balance between degradation and physical properties. Laboratory degradation experiments indicated that PBOF possessed significant degradation effects. Among them, PBOF-41 (with 41 % molar furanoate) decreased in weight by 20 % in freshwater, 70 % in an enzyme solution, and 8 % in artificial seawater within 30 days. After 28 days of degradation in soil, the residual weight was reduced to 80 % of its initial weight. Theoretical calculations and experiments have clarified the enhancement of the Gibbs free energy and energy barrier of the hydrolysis reaction by the BF unit. In summary, PBOF copolyesters have excellent gas barrier performance, adjustable thermal properties, well-balanced mechanical properties, and degradability, making them highly promising for sustainable plastic products.

Toward a Circular Bioeconomy: Designing Microbes and Polymers for Biodegradation

Polymer production is rapidly increasing, but there are no large-scale technologies available to effectively mitigate the massive accumulation of these recalcitrant materials. One potential solution is the development of a carbon-neutral polymer life cycle, where microorganisms convert plant biomass to chemicals, which are used to synthesize biodegradable materials that ultimately contribute to the growth of new plants. Realizing a circular carbon life cycle requires the integration of knowledge across microbiology, bioengineering, materials science, and organic chemistry, which itself has hindered large-scale industrial advances. This review addresses the biodegradation status of common synthetic polymers, identifying novel microbes and enzymes capable of metabolizing these recalcitrant materials and engineering approaches to enhance their biodegradation pathways. Design considerations for the next generation of biodegradable polymers are also reviewed, and finally, opportunities to apply findings from lignocellulosic biodegradation to the design and biodegradation of similarly recalcitrant synthetic polymers are discussed.

Application of MicroResp™ for quick and easy detection of plastic degradation by marine bacterial isolates

Microplastic debris in the marine environment is a global problem. Biodegradable polymers are being developed as alternatives to petroleum-based plastics, and quick and easy methods for screening for bacterial strains that can degrade such polymers are needed. As a screening method, the clear zone method has been widely used but has technical difficulties such as plate preparation and interpretation of results. In this study, we adapted the MicroResp™ system to easily detect biodegradation activity of marine bacteria in a 3-day assay. Among the 6 bacterial strains tested, 3, 2 and 1 strain degraded poly (butylene succinate-co-adipate) (PBSA), poly (ε-caprolactone) (PCL) and poly (3-hydroxybutyrate-co-3-hydroxyhexanoate), respectively. Only one strain that showed degradation activity of PBSA and PCL in the MicroResp™ system was also positive in the clear zone assay on the respective emulsion plates. Our results show that the adapted MicroResp™ system can screen for bacterial strains that degrade plastic.

Rapid marine degradable poly(butylene oxalate) by introducing promotion building blocks

The design and development of high-performance marine-degradable plastics have long been considered a superior strategy to address marine plastic pollution. To achieve a balance between rapid marine degradability and high performance of polyester plastics, this work designed two series of poly(butylene oxalate) (PBOx) copolymers with intrinsic hydrolysis ability using poly(ethylene oxalate) (PEOx) and poly(glycolic acid) (PGA) as promotion building blocks. The synthesis process, crystallization properties, barrier performance, and mechanical properties of copolymers were comparatively investigated. Additionally, the marine degradability of copolymers received specific focus. The theoretical calculation demonstrated that the introduction of promotion blocks reduced the hydrolysis energy barrier of the copolymers. In general, the results revealed the advantages of PBEOx copolymer in satisfying practicality and better regulating marine degradability. The high gas barrier performance, suitable thermal properties, tunable mechanical properties, and rapid marine degradability endow the copolymer as a promising candidate toward sustainable and marine-degradable plastics.