High-throughput experimentation for discovery of biodegradable polyesters.

The consistent rise of plastic pollution has stimulated interest in the development of biodegradable plastics. However, the study of polymer biodegradation has historically been limited to a small number of polymers due to costly and slow standard methods for measuring degradation, slowing new material innovation. High-throughput polymer synthesis and a high-throughput polymer biodegradation method are developed and applied to generate a biodegradation dataset for 642 chemically distinct polyesters and polycarbonates. The biodegradation assay was based on the clear-zone technique, using automation to optically observe the degradation of suspended polymer particles under the action of a single Pseudomonas lemoignei bacterial colony. Biodegradability was found to depend strongly on aliphatic repeat unit length, with chains less than 15 carbons and short side chains improving biodegradability. Aromatic backbone groups were generally detrimental to biodegradability; however, ortho- and para-substituted benzene rings in the backbone were more likely to be degradable than metasubstituted rings. Additionally, backbone ether groups improved biodegradability. While other heteroatoms did not show a clear improvement in biodegradability, they did demonstrate increases in biodegradation rates. Machine learning (ML) models were leveraged to predict biodegradability on this large dataset with accuracies over 82% using only chemical structure descriptors.

The Block Copolymer Phase Behavior Database.

The Block Copolymer Database (BCDB) is a platform that allows users to search, submit, visualize, benchmark, and download experimental phase measurements and their associated characterization information for di- and multiblock copolymers. To the best of our knowledge, there is no widely accepted data model for publishing experimental and simulation data on block copolymer self-assembly. This proposed data schema with traceable information can accommodate any number of blocks and at the time of publication contains over 5400 block copolymer total melt phase measurements mined from the literature and manually curated and simulation data points of the phase diagram generated from self-consistent field theory that can rapidly be augmented. This database can be accessed via the Community Resource for Innovation in Polymer Technology (CRIPT) web application and the Materials Data Facility. The chemical structure of the polymer is encoded in BigSMILES, an extension of the Simplified Molecular-Input Line-Entry System (SMILES) into the macromolecular domain, and the user can search repeat units and functional groups using the SMARTS search syntax (SMILES Arbitrary Target Specification). The user can also query characterization and phase information using Structured Query Language (SQL) and download custom sets of block copolymer data to train machine learning models. Finally, a protocol is presented in which GPT-4, an AI-powered large language model, can be used to rapidly screen and identify block copolymer papers from the literature using only the abstract text and determine whether they have BCDB data, allowing the database to grow as the number of published papers on the World Wide Web increases. The F1 score for this model is 0.74. This platform is an important step in making polymer data more accessible to the broader community.

Cradle-to-gate life cycle assessment of Spirulina bioplastic produced via plasticization with glycerol.

Bioplastics have been used as alternatives to conventional petroleum-based plastics to lessen the burdens on marine and terrestrial environments due to their non-biodegradability and toxicity. However, recent studies have shown that not all bioplastics may be environmentally friendly. Microalgae, such as Spirulina that do not require arable land, have been identified as a potential bioplastic source. In this study, cradle-to-gate life cycle assessment (LCA) was carried out in openLCA program using the Agribalyse database, to evaluate the environmental impacts of Spirulina bioplastic, formed from plasticization of Spirulina powder with glycerol. Two processes were created for the inventories of (i) Spirulina powder and (ii) Spirulina bioplastic, where the output of the former served as an input for the latter. The extruded bioplastic sheets were food-grade and could be used as edible packaging materials. The bioplastic was also compared to conventional plastics and it was found that the energy consumption was 3.83 ± 0.26 MJ/kg-bioplastic, which was 12% and 22% higher than that of LDPE and PVC plastic films, respectively. The impacts on the environment showed that the chemical growth medium (Zarrouk medium) and electricity were the main contributors in most of the categories. Compared to the PVC and LDPE films, the Spirulina bioplastic's impacts on the aquatic ecosystems were 2-3 times higher. The global warming potential of the Spirulina bioplastic was 1.99 ± 0.014 kg CO2 eq, which was 23% and 47% lower than that of LDPE and PVC films, respectively. Sensitivity analysis was carried out by changing the electricity source and using alternative growth media. Except for the case of switching to solar energy, the results for other cases did not differ significantly from the base case scenario. Future studies were suggested to identify different greener alternatives to the growth medium as well as different energy mixes for more environmentally benign solutions.

High-Throughput Screening of Streptavidin-Binding Proteins in Self-Assembled Solid Films for Directed Evolution of Materials.

Evolution has shaped the development of proteins with an incredible diversity of properties. Incorporating proteins into materials is desirable for applications including biosensing; however, high-throughput selection techniques for screening protein libraries in materials contexts is lacking. In this work, a high-throughput platform to assess the binding affinity for ordered sensing proteins was established. A library of fusion proteins, consisting of an elastin-like polypeptide block, one of 22 variants of rcSso7d, and a coiled-coil order-directing sequence, was generated. All selected variants had high binding in films, likely due to the similarity of the assay to magnetic bead sorting used for initial selection, while solution binding was more variable. From these results, both the assembly of the fusion proteins in their operating state and the functionality of the binding protein are key factors in the biosensing performance. Thus, the integration of directed evolution with assembled systems is necessary to the design of better materials.

Automated, High-Throughput Screening of Hybrid Elastin-like Polypeptide/Polysaccharide Multilayer Film Deposition.

The self-assembled layer-by-layer technique has attracted a great deal of attention as a method for engineering bio-functional surfaces under mild chemical conditions. The production of multilayer films, starting from newly designed building blocks, may be laborious, considering the inherent limitations for anticipating how minimal changes in the macromolecular composition may impact both film deposition and performance. This paper presents an automated, high-throughput approach to depositing polyelectrolyte multilayers (PEMs) in multiwell plates, enabling the screening of nearly 100 film formulations in the same process. This high-throughput layer-by-layer (HT-LbL) method runs in an affordable, fully commercial platform using Python-coded routines that can be easily adapted for the materials science lab settings. The HT-LbL system was validated by investigating the deposition of polysaccharide-based films in multiwell plates, probing the absorbance signal of ionically stained polyelectrolyte multilayers (PEMs) prepared in one single batch. The HT-LbL method was also used to investigate the deposition of PEMs with a small library of genetically engineered elastin-like polypeptides (ELPs) with different levels of ionizable and hydrophobic amino acid residues. The deposition of ELP/chitosan films was assessed based on the signal of fluorescently labeled species (chitosan or ELP-mCherry), demonstrating that both electrostatic and hydrophobic residues are essential for film buildup. The growth and surface properties of ELP-mCherry/chitosan films also seemed susceptible to the assembly pH, forming a higher film growth and a rougher and more hydrophobic surface for both polyelectrolytes deposited under a low ionization degree. Overall, this study illustrates the challenge of predicting the growth and properties of multilayer films and how the HT-LbL can accelerate the development of multilayer films that demand high levels of testing and optimization.

Structural and dynamic heterogeneity in associative networks formed by artificially engineered protein polymers.

This work investigates static gel structure and cooperative multi-chain motion in associative networks using a well-defined model system composed of artificial coiled-coil proteins. The combination of small-angle and ultra-small-angle neutron scattering provides evidence for three static length scales irrespective of protein gel design which are attributed to correlations arising from the blob length, inter-junction spacing, and multi-chain density fluctuations. Self-diffusion measurements using forced Rayleigh scattering demonstrate an apparent superdiffusive regime in all gels studied, reflecting a transition between distinct "slow" and "fast" diffusive species. The interconversion between the two diffusive modes occurs on a length scale on the order of the largest correlation length observed by neutron scattering, suggesting a possible caging effect. Comparison of the self-diffusive behavior with characteristic molecular length scales and the single-sticker dissociation time inferred from tracer diffusion measurements supports the primarily single-chain mechanisms of self-diffusion as previously conceptualized. The step size of the slow mode is comparable to the root-mean-square length of the midblock strands, consistent with a single-chain walking mode rather than collective motion of multi-chain aggregates. The transition to the fast mode occurs on a timescale 10-1000 times the single-sticker dissociation time, which is consistent with the onset of single-molecule hopping. Finally, the terminal diffusivity depends exponentially on the number of stickers per chain, further suggesting that long-range diffusion occurs by molecular hopping rather than sticky Rouse motion of larger assemblies. Collectively, the results suggest that diffusion of multi-chain clusters is dominated by the single-chain pictures proposed in previous coarse-grained modeling.

BigSMARTS: A Topologically Aware Query Language and Substructure Search Algorithm for Polymer Chemical Structures.

Molecular search is important in chemistry, biology, and informatics for identifying molecular structures within large data sets, improving knowledge discovery and innovation, and making chemical data FAIR (findable, accessible, interoperable, reusable). Search algorithms for polymers are significantly less developed than those for small molecules because polymer search relies on searching by polymer name, which can be challenging because polymer naming is overly broad (i.e., polyethylene), complicated for complex chemical structures, and often does not correspond to official IUPAC conventions. Chemical structure search in polymers is limited to substructures, such as monomers, without awareness of connectivity or topology. This work introduces a novel query language and graph traversal search algorithm for polymers that provides the first search method able to fully capture all of the chemical structures present in polymers. The BigSMARTS query language, an extension of the small-molecule SMARTS language, allows users to write queries that localize monomer and functional group searches to different parts of the polymer, like the middle block of a triblock, the side chain of a graft, and the backbone of a repeat unit. The substructure search algorithm is based on the traversal of graph representations of the generating functions for the stochastic graphs of polymers. Operationally, the algorithm first identifies cycles representing the monomers and then the end groups and finally performs a depth-first search to match entire subgraphs. To validate the algorithm, hundreds of queries were searched against hundreds of target chemistries and topologies from the literature, with approximately 440,000 query-target pairs. This tool provides a detailed algorithm that can be implemented in search engines to provide search results with full matching of the monomer connectivity and polymer topology.

Molecular Characterization of Polymer Networks.

Polymer networks are complex systems consisting of molecular components. Whereas the properties of the individual components are typically well understood by most chemists, translating that chemical insight into polymer networks themselves is limited by the statistical and poorly defined nature of network structures. As a result, it is challenging, if not currently impossible, to extrapolate from the molecular behavior of components to the full range of performance and properties of the entire polymer network. Polymer networks therefore present an unrealized, important, and interdisciplinary opportunity to exert molecular-level, chemical control on material macroscopic properties. A barrier to sophisticated molecular approaches to polymer networks is that the techniques for characterizing the molecular structure of networks are often unfamiliar to many scientists. Here, we present a critical overview of the current characterization techniques available to understand the relation between the molecular properties and the resulting performance and behavior of polymer networks, in the absence of added fillers. We highlight the methods available to characterize the chemistry and molecular-level properties of individual polymer strands and junctions, the gelation process by which strands form networks, the structure of the resulting network, and the dynamics and mechanics of the final material. The purpose is not to serve as a detailed manual for conducting these measurements but rather to unify the underlying principles, point out remaining challenges, and provide a concise overview by which chemists can plan characterization strategies that suit their research objectives. Because polymer networks cannot often be sufficiently characterized with a single method, strategic combinations of multiple techniques are typically required for their molecular characterization.

Strengthening and Toughening of Protein-Based Thermosets via Intermolecular Self-Assembly.

As proteins are abundant polymers in biomass sources such as agricultural feedstocks and byproducts, leveraging them to develop alternatives to synthetic polymers is of great interest. However, the mechanical performance of protein materials is not suitable for most target applications. Constructing copolymers with proteins as hard domains and rubbery polymers as soft domains has been shown to be a promising strategy for improving mechanical properties. Herein, it is demonstrated that toughening and strengthening of protein copolymers can be advanced further by thermal treatment, leading to mechanical enhancements that generalize across a variety of different protein feedstocks, including whey, serum, soy, and pea proteins. The thermal treatment induces a rearrangement of protein structure, leading to the formation of intermolecular ß-sheets. The ordered intermolecular structures in the hard domains of thermosets greatly improve their mechanical properties, providing simultaneous increases in strength, toughness, and modulus, with little sacrifice in fracture strain. Analogous to crystalline structures, the formation of intermolecular ß-sheet structures also leads to reduced hygroscopicity. This is a valuable contribution, as practical applications of natural polymer-based plastics are frequently hindered by the materials' humidity sensitivity. Therefore, this work demonstrates a simple yet versatile strategy to improve the materials' performance from a wide range of protein feedstocks, as well as signifies the implications of protein structural assembly in materials design.

Hierarchy of relaxation times in supramolecular polymer model networks.

Supramolecular polymer gels are an evolving class of soft materials with a vast number of properties that can be tuned to desired applications. Despite continuous advances concerning polymer synthesis, sustainability or adaptability, a consistent understanding of the interplay between structure, dynamics, and diffusion processes within transient networks is lacking. In this study, the hierarchy of several relaxation processes is investigated, starting from a microscopic perspective of a single sticker dissociation event up to the center-of-mass diffusion of a star-shaped polymer building block on different length scales, as well as the resulting macroscopic mechanical response to applied external stress. In addition to that, a second focus is placed on the gel micro-structure that is analyzed by light scattering. Conversion of the dynamic light scattering (DLS) inverse length scale into real space allows for a combination of relaxation times with those obtained by forced Rayleigh scattering (FRS). For these investigations, a model-type metallo-supramolecular network consisting of narrowly dispersed tetra-arm poly(ethylene glycol)-terpyridine macromolecules that are interconnected via complexation with zinc ions is chosen. Assembling the obtained activation energies reveals that all complex dissociation-governed relaxation processes exhibit similar activation energies.

Single-Event Spectroscopy and Unravelling Kinetics of Covalent Domains Based on Cyclobutane Mechanophores.

Mechanochemical reactions that lead to an increase in polymer contour length have the potential to serve as covalent synthetic mimics of the mechanical unfolding of noncovalent "stored length" domains in structural proteins. Here we report the force-dependent kinetics of stored length release in a family of covalent domain polymers based on cis-1,2-substituted cyclobutane mechanophores. The stored length is determined by the size (n) of a fused ring in an [n.2.0] bicyclic architecture, and it can be made sufficiently large (>3 nm per event) that individual unravelling events are resolved in both constant-velocity and constant-force single-molecule force spectroscopy (SMFS) experiments. Replacing a methylene in the pulling attachment with a phenyl group drops the force necessary to achieve rate constants of 1 s-1 from ca. 1970 pN (dialkyl handles) to 630 pN (diaryl handles), and the substituent effect is attributed to a combination of electronic stabilization and mechanical leverage effects. In contrast, the kinetics are negligibly perturbed by changes in the amount of stored length. The independent control of unravelling force and extension holds promise as a probe of molecular behavior in polymer networks and for optimizing the behaviors of materials made from covalent domain polymers.

Mechanism Dictates Mechanics: A Molecular Substituent Effect in the Macroscopic Fracture of a Covalent Polymer Network.

The fracture of rubbery polymer networks involves a series of molecular events, beginning with conformational changes along the polymer backbone and culminating with a chain scission reaction. Here, we report covalent polymer gels in which the macroscopic fracture "reaction" is controlled by mechanophores embedded within mechanically active network strands. We synthesized poly(ethylene glycol) (PEG) gels through the end-linking of azide-terminated tetra-arm PEG (Mn = 5 kDa) with bis-alkyne linkers. Networks were formed under identical conditions, except that the bis-alkyne was varied to include either a cis-diaryl (1) or cis-dialkyl (2) linked cyclobutane mechanophore that acts as a mechanochemical "weak link" through a force-coupled cycloreversion. A control network featuring a bis-alkyne without cyclobutane (3) was also synthesized. The networks show the same linear elasticity (G' = 23-24 kPa, 0.1-100 Hz) and equilibrium mass swelling ratios (Q = 10-11 in tetrahydrofuran), but they exhibit tearing energies that span a factor of 8 (3.4 J, 10.6, and 27.1 J·m-2 for networks with 1, 2, and 3, respectively). The difference in fracture energy is well-aligned with the force-coupled scission kinetics of the mechanophores observed in single-molecule force spectroscopy experiments, implicating local resonance stabilization of a diradical transition state in the cycloreversion of 1 as a key determinant of the relative ease with which its network is torn. The connection between macroscopic fracture and a small-molecule reaction mechanism suggests opportunities for molecular understanding and optimization of polymer network behavior.

Tuning Selective Transport of Biomolecules through Site-Mutated Nucleoporin-like Protein (NLP) Hydrogels.

Natural selective filtering systems (e.g., the extracellular matrix, nuclear pores, and mucus) separate molecules selectively and efficiently, and the detailed understanding of transport mechanisms exploited in these systems provides important bioinspired design principles for selective filters. In particular, nucleoporins consist of consensus repeat sequences that are readily utilized for engineering repeat proteins. Here, the consensus repeat sequence of Nsp1, a yeast nucleoporin, is polymerized to form a nucleoporin-like protein (NLP) and mutated to understand the effect of sequence on selective transport. The hydrophilic spacers of the NLPs were redesigned considering net charge, charge distribution, and polarity. Mutations were made near to and far from the FSFG interacting domain to explore the role of highly conserved residues as a function of spatial proximity. A nuclear transport receptor-cargo complex, nuclear transport factor 2-green fluorescent protein (NTF2-GFP), was used as a model for changes in transport. For mutations of the charged spacer, some mutations of highly conserved charged residues were possible without knocking out selective transport of the NTF2, but the formation of regions of clustered negative charge has an unfavorable effect on nuclear transporter permeation. Thus, positive net charge and alternating positive and negative charge within the hydrophilic spacer are advantageous for recognition and selective transport. In the polarity panel, mutations that increased the interaction between NTF2-GFP and the gel led to decreased permeation of the NTF2-GFP due to blocking of the interface and inability of the NTF2-GFP to transport into the gel. Therefore, these results provide a strategy for tuning selective permeability of biomolecules using the artificially designed consensus repeat-based hydrogels.

SANS quantification of bound water in water-soluble polymers across multiple concentration regimes.

Contrast-variation small-angle neutron scattering (CV-SANS) is a widely used technique for quantifying hydration water in soft matter systems, but it is predominantly applied in the dilute regime or for systems with a well-defined structure factor. Here, CV-SANS was used to quantify the number of hydration water molecules associating with three water-soluble polymers with different critical solution temperatures and types of water-solute interactions in dilute, semidilute, and concentrated solution through the exploration of novel methods of data fitting and analysis. Multiple SANS fitting workflows with varying levels of model assumptions were evaluated and compared to give insight into SANS model selection. These fitting pathways ranged from general, model-free algorithms to more standard form and structure factor fitting. In addition, Monte Carlo bootstrapping was evaluated as a method to estimate parameter uncertainty through simulation of technical replicates. The most robust fitting workflow for dilute solutions was found to be form factor fitting without CV-SANS (i.e. polymer in 100% D2O). For semidilute and concentrated solutions, while the model-free approach can be mathematically defined for CV-SANS data, the addition of a structure factor imposes physical constraints on the optimization problem, suggesting that the optimal fitting pathway should include appropriate form and structure factor models. The measured hydration numbers were consistent with the number of tightly bound water molecules associated with each monomer unit, and the concentration dependence of the hydration number was largely governed by the chemistry-specific interactions between water and polymer. Polymers with weaker water-polymer interactions (i.e. those with fewer hydration water molecules) were found to have more bound water at higher concentrations than those with stronger water-polymer interactions due to the increase in the number of forced water-polymer contacts in the concentrated system. This SANS-based method to count hydration water molecules can be applied to polymers in any concentration regime, which will lead to improved understanding of water-polymer interactions and their impact on materials design.

Effect of sticker clustering on the dynamics of associative networks.

Recent experimental and theoretical work has shown that sticker clustering can be used to enhance properties such as toughness and creep resistance of polymer networks. While it is clear that the changes in properties are related to a change in network topology, the mechanistic relationship is still not well understood. In this work, the effect of sticker clustering was investigated by comparing the dynamics of random copolymers with those where the stickers are clustered at the ends of the chain in the unentangled regime using both linear mechanics and diffusion measurements. Copolymers of N,N-dimethyl acrylamide (DMA) and pendant histidine groups were synthesized using reversible addition-fragmentation chain transfer (RAFT) polymerization. The clustered polymers were synthesized using a bifunctional RAFT agent, such that the midblock consisted of PDMA and the two end blocks were random copolymers of DMA and the histidine-functionalized monomer. Upon addition of Ni ions, transient metal-coordinate crosslinks are formed as histidine-Ni complexes. Combined studies of rheology, neutron scattering and self-diffusion measurements using forced Rayleigh scattering revealed changes to the network topology and stress relaxation modes. The network topology is proposed to consist of aggregates of the histidine-Ni complexes bridged by the non-associative midblock. Therefore, stress relaxation requires the cooperative dissociation of multiple bonds, resulting in increased relaxation times. The increased relaxation times, however, were accompanied by faster diffusion. This is attributed to the presence of defects such as elastically inactive chain loops. This study demonstrates that the effects of cooperative sticker dissociation can be observed even in the presence of a significant fraction of loop defects which are known to alter the nonlinear properties of conventional telechelic polymers.

PolyDAT: A Generic Data Schema for Polymer Characterization.

Polymers are stochastic materials that represent distributions of different molecules. In general, to quantify the distribution, polymer researchers rely on a series of chemical characterizations that each reveal partial information on the distribution. However, in practice, the exact set of characterizations that are carried out, as well as how the characterization data are aggregated and reported, is largely nonstandard across the polymer community. This scenario makes polymer characterization data highly disparate, thereby significantly slowing down the development of polymer informatics. In this work, a proposal on how structural characterization data can be organized is presented. To ensure that the system can apply universally across the entire polymer community, the proposed schema, PolyDAT, is designed to embody a minimal congruent set of vocabulary that is common across different domains. Unlike most chemical schemas, where only data pertinent to the species of interest are included, PolyDAT deploys a multi-species reaction network construct, in which every characterization on relevant species is collected to provide the most comprehensive profile on the polymer species of interest. Instead of maintaining a comprehensive list of available characterization techniques, PolyDAT provides a handful of generic templates, which align closely with experimental conventions and cover most types of common characterization techniques. This allows flexibility for the development and inclusion of new measurement methods. By providing a standard format to digitalize data, PolyDAT serves not only as an extension to BigSMILES that provides the necessary quantitative information but also as a standard channel for researchers to share polymer characterization data.

Glycoprotein Mimics with Tunable Functionalization through Global Amino Acid Substitution and Copper Click Chemistry.

Glycoproteins and their mimics are challenging to produce because of their large number of polysaccharide side chains that form a densely grafted protein-polysaccharide brush architecture. Herein a new approach to protein bioconjugate synthesis is demonstrated that can approach the functionalization densities of natural glycoproteins through oligosaccharide grafting. Global amino acid substitution is used to replace the methionine residues in a methionine-enriched elastin-like polypeptide with homopropargylglycine (HPG); the substitution was found to replace 93% of the 41 methionines in the protein sequence as well as broaden and increase the thermoresponsive transition. A series of saccharides were conjugated to the recombinant protein backbones through copper(I)-catalyzed alkyne-azide cycloaddition to determine reactivity trends, with 83-100% glycosylation of HPGs. Only an acetyl-protected sialyllactose moiety showed a lower level of 42% HPG glycosylation that is attributed to steric hindrance. The recombinant glycoproteins reproduced the key biofunctional properties of their natural counterparts such as viral inhibition and lectin binding.

Effect of Protein Surface Charge Distribution on Protein-Polyelectrolyte Complexation.

Charge anisotropy or the presence of charge patches at protein surfaces has long been thought to shift the coacervation curves of proteins and has been used to explain the ability of some proteins to coacervate on the "wrong side" of their isoelectric point. This work makes use of a panel of engineered superfolder green fluorescent protein mutants with varying surface charge distributions but equivalent net charge and a suite of strong and weak polyelectrolytes to explore this concept. A patchiness parameter, which assessed the charge correlation between points on the surface of the protein, was used to quantify the patchiness of the designed mutants. Complexation between the polyelectrolytes and proteins showed that the mutant with the largest patchiness parameter was the most likely to form complexes, while the smallest was the least likely to do so. The patchiness parameter was found to correlate well with the phase behavior of the protein-polymer mixtures, where both macrophase separation and the formation of soluble aggregates were promoted by increasing the patchiness depending on the polyelectrolyte with which the protein was mixed. Increasing total charge and increasing strength of the polyelectrolyte promote interactions for oppositely charged polyelectrolytes, while charge regulation is also key to interactions for similarly charged polyelectrolytes, which must interact selectively with oppositely charged patches.

Semibatch monomer addition as a general method to tune and enhance the mechanics of polymer networks via loop-defect control.

Controlling the molecular structure of amorphous cross-linked polymeric materials is a longstanding challenge. Herein, we disclose a general strategy for precise tuning of loop defects in covalent polymer gel networks. This "loop control" is achieved through a simple semibatch monomer addition protocol that can be applied to a broad range of network-forming reactions. By controlling loop defects, we demonstrate that with the same set of material precursors it is possible to tune and in several cases substantially improve network connectivity and mechanical properties (e.g., ∼600% increase in shear storage modulus). We believe that the concept of loop control via continuous reagent addition could find broad application in the synthesis of academically and industrially important cross-linked polymeric materials, such as resins and gels.

Non-isocyanate urethane linkage formation using l-lysine residues as amine sources.

Bio-based polyurethane materials are broadly applied in medicine as drug delivery systems. Nevertheless, their synthesis comprises the use of petroleum-based toxic amines, isocyanates and polyols, and their biocompatibility or functionalization is limited. Therefore, the use of lysine residues as amine sources to create non-isocyanate urethane (NIU) linkages was investigated. Therefore, a five-membered biscyclic carbonate (BCC) was firstly synthetized and reacted with a protected lysine, a tripeptide and a heptapeptide to confirm the urethane linkage formation with lysine moiety and to optimize reaction conditions. Afterwards, the reactions between BCC and a model protein, elastin-like protein (ELP), and ß-Lactoglobulin (BLG) obtained from whey protein, respectively, were performed. The synthesized protein materials were structural, thermally and morphologically characterized to confirm the urethane linkage formation. The results demonstrate that using both simple and more complex source of amines (lysine), urethane linkages were effectively achieved. This pioneering approach opens the possibility of using proteins to develop non-isocyanate polyurethanes (NIPUs) with tailored properties.