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Low-cost, high-throughput methods for the determination of high-yield protein expression conditions are developed and verified, to enable the rapid development of new protein materials, such as biosensors and biomaterials.

The linear rheological properties of supramolecular polymer networks formed by mixtures of two different bis-Pd(II) cross-linkers with poly(4-vinylpyridine) in dimethyl sulfoxide are examined. The changes in storage and loss moduli of the networks with mixed cross-linkers are compared to those of samples with a single type of cross-linkers. While the plateau moduli, and presumably network topology, of the networks remain equal regardless of the cross-link distribution, the relaxation time contributed by the faster cross-linkers is increased (by a factor of about 1.5 for the specific samples used in this work) by the presence of the slower cross-linkers, while the reverse influences are not significant. This effect can be explained by the fact that a certain fraction of the elastically effective strands cross-linked with fast cross-linkers is pinned on one end by slow cross-linkers, reducing by half the rate of fast chain relaxation. This effect is anticipated to be general for gels with two well-separated relaxation times.

There are no drugs or treatment methods known to prevent the development of post-traumatic osteoarthritis (PTOA), a type of osteoarthritis (OA) that is triggered by traumatic joint injuries and accounts for ∼12% of the nearly 600 million OA cases worldwide. Lack of effective drug delivery techniques remains a major challenge in developing clinically effective treatments, but cationic delivery carriers can help overcome this challenge. Scaling up treatments that are effective in in vitro models to achieve success in preclinical in vivo models and clinical trials is also a challenging problem in the field. Here we use a cationic green fluorescent protein (GFP) as a carrier to deliver Insulin-Like Growth Factor 1 (IGF-1), a drug considered as a potential therapeutic for PTOA. GFP-IGF-1 conjugates were first synthesized as fusion proteins with different polypeptide linkers, and their transport properties were characterized in human cartilage explants. In vitro experimental data were used to develop a predictive mathematical transport model that was validated using an independent in vitro experimental data set. The model was used to predict the transport of these fusion proteins upon intra-articular injection into human knee joints. The predictions included results for the rate and extent of fusion protein penetration into cartilage, and the maximum levels of fusion proteins that would escape into systemic circulation through the joint capsule. Together, our transport measurements and model set the stage for translation of such explant culture studies to in vivo preclinical studies and potentially clinical application. STATEMENT OF SIGNIFICANCE: The lack of blood supply in cartilage and rapid clearance of drugs injected into human knees presents a major challenge in developing clinically effective treatments for osteoarthritis. Cationic delivery carriers can target negatively charged cartilage and help overcome this problem. Scaling up treatments that are effective in vitro to achieve success in vivo is also challenging. Here, we use a cationic green fluorescent protein (GFP) to deliver Insulin-Like Growth Factor-1 (IGF-1) into cartilage. Experiments measuring transport of GFP-IGF-1 fusion proteins in human cartilage explants were used to develop and validate a mathematical model to predict fusion protein transport upon injection into human knee joints. This work translates such explant culture studies to in vivo preclinical studies and potentially clinical application.

BigSMILES, a line notation for encapsulating the molecular structure of stochastic molecules such as polymers, was recently proposed as a compact and readable solution for writing macromolecules. While BigSMILES strings serve as useful identifiers for reconstructing the molecular connectivity for polymers, in general, BigSMILES allows the same polymer to be codified into multiple equally valid representations. Having a canonicalization scheme that eliminates the multiplicity would be very useful in reducing time-intensive tasks like structural comparison and molecular search into simple string-matching tasks. Motivated by this, in this work, two strategies for deriving canonical representations for linear polymers are proposed. In the first approach, a canonicalization scheme is proposed to standardize the expression of BigSMILES stochastic objects, thereby standardizing the expression of overall BigSMILES strings. In the second approach, an analogy between formal language theory and the molecular ensemble of polymer molecules is drawn. Linear polymers can be converted into regular languages, and the minimal deterministic finite automaton uniquely associated with each prescribed language is used as the basis for constructing the unique text identifier associated with each distinct polymer. Overall, this work presents algorithms to convert linear polymers into unique structure-based text identifiers. The derived identifiers can be readily applied in chemical information systems for polymers and other polymer informatics applications.

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 β-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 β-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.

Suppressing the influence of humidity in protein-based materials is central to their use in a variety of applications. It is believed that protein charge plays a key role in water uptake. Therefore, in this work, whey protein was neutralized, supercharged, and superneutralized to examine the effects of protein modification on moisture absorption in protein copolymers. The charge-modified proteins were formulated into thermoset elastomers through a three-step process: methacrylation, complexation with various surfactants, and co-polymerization with n-butyl acrylate. Compatibility of the protein and hydrophobic acrylate monomer can be tuned through changes in surfactant type, ratio between surfactant and protein, and protein charge modification. Using benzalkonium chloride as the surfactant compatibilizer, elastomers with the various modified proteins were prepared using a melt polymerization approach. Acetylation and esterification of whey protein, which neutralize charged functional groups, resulted in the reduction of the proteins' water uptake relative to unmodified whey. Once incoporated into elastomers, all copolymers regardless of protein modifications have similar moisture contents. However, elastomers with superneutralized proteins demonstrated a lowered mechanical dependence on humidity, presented as a smaller change in elongation at break and tensile strength compared to a copolymer based on non-charge modified whey. This journal is

As a machine-recognizable representation of polymer connectivity, BigSMILES line notation extends SMILES from deterministic to stochastic structures. The same framework that allows BigSMILES to accommodate stochastic covalent connectivity can be extended to non-covalent bonds, enhancing its value for polymers, supramolecular materials, and colloidal chemistry. Non-covalent bonds are captured through the inclusion of annotations to pseudo atoms serving as complementary binding pairs, minimal key/value pairs to elaborate other relevant attributes, and indexes to specify the pairing among potential donors and acceptors or bond delocalization. Incorporating these annotations into BigSMILES line notation enables the representation of four common classes of non-covalent bonds in polymer science: electrostatic interactions, hydrogen bonding, metal-ligand complexation, and π-π stacking. The principal advantage of non-covalent BigSMILES is the ability to accommodate a broad variety of non-covalent chemistry with a simple user-orientated, semi-flexible annotation formalism. This goal is achieved by encoding a universal but non-exhaustive representation of non-covalent or stochastic bonding patterns through syntax for (de)protonated and delocalized state of bonding as well as nested bonds for correlated bonding and multi-component mixture. By allowing user-defined descriptors in the annotation expression, further applications in data-driven research can be envisioned to represent chemical structures in many other fields, including polymer nanocomposite and surface chemistry.

Longer and stronger; stiff but not brittle Hydrogels are highly water-swollen, cross-linked polymers. Although they can be highly deformed, they tend to be weak, and methods to strengthen or toughen them tend to reduce stretchability. Two papers now report strategies to create tough but deformable hydrogels (see the Perspective by Bosnjak and Silberstein). Wang et al . introduced a toughening mechanism by storing releasable extra chain length in the stiff part of a double-network hydrogel. A high applied force triggered the opening of cycling strands that were only activated at high chain extension. Kim et al . synthesized acrylamide gels in which dense entanglements could be achieved by using unusually low amounts of water, cross-linker, and initiator during the synthesis. This approach improves the mechanical strength in solid form while also improving the wear resistance once swollen as a hydrogel. —MSL

Recent experiments on self-diffusion in associative networks have shown superdiffusive scaling hypothesized to originate from molecular diffusive mechanisms, which include walking and hopping of th...

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.

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.

Bioinspired brush polymers containing α-2,6-linked sialic acids at the side chain termini were synthesized by protection-group-free, ring-opening metathesis polymerization. Polymers showed strain-selective antiviral activity through multivalent presentation of the sialosides. The multivalent effect was further controlled by independently varying the degree of polymerization, the number density of sialic acids, and the length of side chains in the brush polymers. Optimizing the three-dimensional sialoside spacing for better binding to hemagglutinin trimers was of critical importance to enhance the multivalent effect and the antiviral activity determined by hemagglutination inhibition assays and in vitro infection assays. By taking advantage of their structural similarities with native mucins, these brush polymers can be used as model systems to dissect the intricate design principles in natural mucins.

This two-dimensional computational study investigates the effect of external magnetic fields on thin film nanocomposites comprised of superparamagnetic nanoparticles dispersed within block copolymer melts, which display a variety of morphological transitions based on the field orientation, nanoparticle loading, and selectivity of the nanoparticles for the blocks. In-plane magnetic fields lead to chaining of the nanoparticles; when selective for the minority block in a hexagonal block copolymer nanostructure, this chaining results in the formation of stripe phases oriented parallel to the magnetic field. When selective for the majority block of the hexagonal structure, nanoparticle chains of sufficient persistence length drive the orientation of the hexagonal morphology with the ⟨100⟩ direction oriented parallel to the magnetic field. Out-of-plane magnetic fields induce repulsive dipolar interactions between the nanoparticles that annihilate the defects in the hexagonal morphology of the block copolymer when the nanoparticle is selective for the minority block. When the nanoparticles are selective for the majority block and the field is oriented out of plane, repulsive dipolar interactions lead to the formation of honeycomb lattices. In all cases, the nanoparticle size and volume fraction must be chosen to maximize the commensurability with the block copolymer structure to optimize the ordering of the final composite.

The diffusion of entangled rod–coil block copolymers is investigated by molecular dynamics (MD) simulations, and theories are introduced that describe the observed features and underlying physics. The reptation of rod–coil block copolymers is dominated by the mismatch between the curvature of the rod and coil entanglement tubes, which results in dramatically slower diffusion of rod–coils compared to the rod and coil homopolymers. For small rods, a local curvature-dependent free energy penalty results in a rough energy surface inside the entanglement tube, causing diffusivity to decrease with rod length. For large rods, rotational hindrances on the rod dominate, causing the coil block to relax by an arm retraction mechanism and diffusivity to decrease exponentially with coil size.

This work presents scattering functions of conjugates consisting of a colloid particle and a self-avoiding polymer chain as a model for protein–polymer conjugates and nanoparticle–polymer conjugates in solution. The model is directly derived from the two-point correlation function with the inclusion of excluded volume effects. The dependence of the calculated scattering function on the geometric shape of the colloid and polymer stiffness is investigated. The model is able to describe the experimental scattering signature of the solutions of suspending hard particle–polymer conjugates and provide additional conformational information. This model explicitly elucidates the link between the global conformation of a conjugate and the microstructure of its constituent components.

The Flory-Rehner and Bray-Merrill swelling theories are venerable theories for calculating the swelling of polymer networks and are widely applied across polymer materials. Here, these theories are revised to include cyclic topological defects present in polymer networks by using a modified phantom network model. These closed-form equations assume defect contributions to the swelling elasticity to be linear and additive and allow different assumptions regarding prestrain of larger loops to be incorporated. To compare to the theories, swelling experiments are performed on end-linked poly(ethylene glycol) gels in which the topological defects (primary and secondary loops) have been previously measured. Gels with higher loop densities exhibit higher swelling ratios. An equation is derived to compare swelling models independent of knowledge of the Flory-Huggins χ parameter, showing that the revised swelling models for loop defects are more accurate than both the phantom network model that neglects loops and the Bray-Merrill equation.

Physics-based models are the primary approach for modeling the phase behavior of block copolymers. However, the successful use of self-consistent field theory (SCFT) for designing new materials relies on the correct chemistry- and temperature-dependent Flory-Huggins interaction parameter

Although surface-based biosensors have been widely used in diagnostic applications, these sensors experience reduced sensitivity in the most common detection fluids because of nonspecific binding e...

The failure properties of a polymer network, including toughness, ultimate strain, and ultimate stress, are some of the most critical properties for network performance. The polymer networks often ...

While protein self-assembly has been used to improve the performance of biosensors and biocatalysts, few general techniques have been demonstrated to achieve well-ordered protein arrays under the h...

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.

Protein–polymer bioconjugates represent a class of materials that integrate protein functionality with polymer material properties and block copolymer self-assembly. To investigate the effect of polymer block secondary structure and chirality on self-assembly of globular protein–helix diblock copolymers, four types of bioconjugates consisting of a poly(amino acid) and enhanced green fluorescent protein (eGFP) were synthesized and compared: two homochiral, α-helix-forming bioconjugates incorporating either L- or D-type poly(amino acids), a 1 : 1 blend of the L- and D-type bioconjugates, and a bioconjugate incorporating structureless, achiral poly(amino acids). Poly(amino acids) (PAAs) were synthesized via N-carboxy anhydride (NCA) polymerization, and PAAs were conjugated to eGFP via native chemical ligation. All bioconjugates with a helical block self-assembled into lamellae at all concentrations measured (20 to 60 wt%). In contrast, the random copolymer of L- and D-type monomers did not self-assemble at any concentration or temperature. This was shown to be an effect of a non-repulsive interaction between the flexible PAA and the eGFP blocks, which is strong enough to affect the protonation state of the eGFP chromophore in water. Therefore, secondary structure of the polymer block can modulate the effective segregation strength between blocks and drive self-assembly even in systems with non-repulsive blocks.

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

Luminescence thermometry has substantially progressed in the last decade, rapidly approaching the performance of concurrent technologies. Performance is usually assessed through the relative thermal sensitivity, Sr, and temperature uncertainty, ����T. Until now, the state-of-the-art values at ambient conditions do not exceed maximum Sr of 12.5% K���1 and minimum ����T of 0.1 K. Although these numbers are satisfactory for most applications, they are insufficient for fields that require lower thermal uncertainties, such as biomedicine. This has motivated the development of materials with an improved thermal response, many of them responding to the temperature through distinct photophysical properties. This paper demonstrates how the performance of multiparametric luminescent thermometers can be further improved by simply applying new analysis routes. The synergy between multiparametric readouts and multiple linear regression makes possible a tenfold improvement in Sr and ����T, reaching a world record of 50% K���1 and 0.05 K, respectively. This is achieved without requiring the development of new materials or upgrading the detection system as illustrated by using the green fluorescent protein and Ag2S nanoparticles. These results open a new era in biomedicine thanks to the development of new diagnosis tools based on the detection of super-small temperature fluctuations in living specimens., This project has received funding from the European Union's Horizon 2020 FET Open programme under grant agreement No 801305 (NanoTBTech). This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 823941.

Proteins films have been developed for use in food packaging materials in order to replace synthetic polymers because of environment pollution. Despite their advantages, the use of protein films in a wide range of food products is still limited due to their hydrophilic behavior. Thus, this study aimed to decrease the sensitivity of fish protein films to water through the application of glow discharge plasma. Plasma parameters (power, pressure and time of exposure) were studied according to a 23 factorial design, and the physicochemical properties of the films including moisture content, water vapor permeability, and solubility in water were evaluated. The microstructure and thermal properties of the films were also characterized. In general, glow discharge plasma caused different effects in films properties, such as cleaning and etching which were responsible for the changes observed in physicochemical properties. Power and time of exposure, as well as their interaction, were the most influent parameters. Decrease in water vapor permeability and solubility were observed in some treatments, which are important characteristics for a material to be used as food packaging. Then, the plasma setting might be changed through the adjustment of parameters of exposure according to the specificity of the application intended.

Protein-polymer bioconjugate self-assembly has attracted a great deal of attention as a method to fabricate protein nanomaterials in solution and the solid state. To identify protein properties that affect phase behavior in protein-polymer block copolymers, a library of 15 unique protein-b-poly(N-isopropylacrylamide) (PNIPAM) copolymers comprising 11 different proteins was compiled and analyzed. Many attributes of phase behavior are found to be similar among all studied bioconjugates regardless of protein properties, such as formation of micellar phases at high temperature and low concentration, lamellar ordering with increasing temperature, and disordering at high concentration, but several key protein-dependent trends are also observed. In particular, hexagonal phases are only observed for proteins within the molar mass range 20-36 kDa, where ordering quality is also significantly enhanced. While ordering is generally found to improve with increasing molecular weight outside of this range, most large bioconjugates exhibited weaker than predicted assembly, which is attributed to chain entanglement with increasing polymer molecular weight. Additionally, order-disorder transition boundaries are found to be largely uncorrelated to protein size and quality of ordering. However, the primary finding is that bioconjugate ordering can be accurately predicted using only protein molecular weight and percentage of residues contained within β sheets. This model provides a basis for designing protein-PNIPAM bioconjugates that exhibit well-defined self-assembly and a modeling framework that can generalize to other bioconjugate chemistries., United States. Department of Energy. Office of Basic Energy Sciences (Award DE-SC0007106)

Proteins have great potential as biomass-derived feedstocks for material synthesis and can form strong materials due to their highly hydrogen-bonded nature. Elastomers comprised of proteins and a synthetic rubbery polymer were prepared by copolymerizing a methacrylated protein and a vinyl monomer, where proteins function as macro-cross-linkers and reinforcing fillers. Selecting a hydrophobic synthetic polymer block partially mitigates the moisture absorption of protein-based materials while maintaining desirable levels of mechanical properties. The use of a hydrophobic monomer is enabled by the use of surfactants that function as compatibilizers, since proteins are generally insoluble in organic solvents and vinyl monomers. Surfactants also lower the softening temperature of proteins, allowing materials to be fabricated solvent free using thermoplastic processing techniques. The preparation of a polyacrylate network toughened through incorporation of protein cross-linking domains is demonstrated using whe...

In the classical phantom network theory, the shear modulus of a polymer network is derived assuming the underlying network has a treelike topology made up of identical strands. However, in real networks, defects such as dangling ends, cyclic defects, and polydispersity in strand sizes exist. Moreover, studies have shown that cyclic defects, or loops, are intrinsic to polymer networks. In this study, we illustrate a general framework for calculating the rubber elasticity of phantom networks with arbitrary defects. Closed form solutions for the elastic effectiveness of strands near isolated loops and dangling ends are obtained, and it was found that under classical assumptions of phantom network theory loops with order ≥3 have zero net impact on the overall elasticity. However, when a simple approximation for strand prestrain is considered, the modified network theory agrees well with experimentally measured moduli of PEG gels.

Myofibrillar proteins have good film forming ability, that leads to the formation of polymers with interesting properties for food packaging development. However, as other bio-sourced macromolecules, they have limited performance compared to synthetic materials and cold plasma represents a promising strategy to change polymer properties. Alternating current (AC) glow discharge plasma is a novel and innovative approach for surface modification of agro-based films in order to improve their properties. Then, the effects of exposure to AC glow discharge plasma were studied on the physicochemical, microstructural and thermal properties of myofibrillar protein films from fish. Films treated for 2 min showed increased elongation at break and decreased tensile strength, while the opposite behavior was observed after 5 min of treatment. Solubility in water increased with 5 min and water vapor permeability increased with 2 min of plasma treatment. Color and opacity also increased probably as a result of chemical changes because of plasma application. Slight changes were observed in microstructure of the films. Thermal properties results agreed with the modifications observed in physicochemical performance, which might be attributed to polymer surface functionalization and etching. Thus, the AC glow discharge is a promising alternative to other strategies in order to advance properties of myofibrillar protein films for food packaging because it is a dry process, does not cause damage by heating in the material, and does not pollute the environment.

The vast differences in material properties accessible via crosslinking of sidechain-functionalized polymers are driven by topology., The vast differences in material properties accessible via crosslinking of sidechain-functionalized polymers are driven by topology. For example, vulcanized rubbery networks feature intermolecular connections and loop topologies of various orders while single-chain nanoparticles (SCNPs) are comprised, in principle, entirely of primary loops. Despite this fact, precise quantification of loops in sidechain crosslinked polymers has not been accomplished. Here, it is demonstrated that by introducing cleavable linkers and mass labels onto the pendant functional groups of reactive polymers, the number of primary loops in sidechain crosslinked materials ranging from rubbery networks (gels) to soluble SCNPs can be precisely quantified. This study sheds new light on the topology of sidechain-crosslinked networks, providing design principles for augmenting the properties of this industrially and academically important class of materials through topological control.

Bioconjugates made of the model red fluorescent protein mCherry and synthetic polymer blocks show that topology, i.e. the BA, BA2, ABA and ABC chain structure of the block copolymers, where B represents the protein and A and C represent polymers, has a significant effect on ordering transitions and the type and size of nanostructures formed during microphase separation. ABA and ABC type block copolymers were synthesized by using two site-specific bioconjugation reactions: the thiol–ene reaction with a cysteine on mCherry and maleimide functionalized polymers, and the sortase A ligation reaction with an LPETG sequence at the C-terminus on mCherry and a triglycine functionalized polymer. The phase behaviors of mCherry–poly(N-isopropylacrylamide) (PNIPAM) and mCherry–(PNIPAM)2 show that the shapes of the phase diagrams are similar overall, but mCherry–(PNIPAM)2, i.e. BA2 type, yields a narrower domain spacing than mCherry–PNIPAM, i.e. BA type. PNIPAM–mCherry–PNIPAM (ABA type) shows only lamellar phases in the range of conditions under which ordered structures appear. PDMAPS–mCherry–PNIPAM (ABC type) shows an ordered structure across the widest range of conditions in the four bioconjugates and also the widest range of different nanodomain structures. The phase behavior of the ABC type implies that the repulsive interaction between two water-soluble coil polymers can be a key factor in enhancing the self-assembly of globular protein–polymer block copolymers.

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.

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.

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

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.