A Molecular Explanation for Anomalous Diffusion in Supramolecular Polymer Networks

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.

Decoupling between Translational Diffusion and Viscoelasticity in Transient Networks with Controlled Network Connectivity

The mobility of sustained molecules is influenced by viscoelasticity, which is strongly correlated with the diffusional property in polymeric liquid. However, the study of transient networks formed by a reversible crosslink, which is the viscoelastic liquid, was insufficient due to the absence of a model system. We compare the viscoelastic and diffusional properties of the transient networks, using the model system with controlled network connectivity (Tetra-PEG slime). According to independent measurements of viscoelasticity and diffusion, the root-mean-square distance the polymer diffuses during the viscoelastic relaxation time shows a large deviation from the self-size of the polymer, which is contrary to the conventional understanding. This decoupling between viscoelasticity and diffusion is unique for transient networks, suggesting that the viscoelastic relaxation is not induced by the diffusion of one prepolymer, particularly in the network with low connectivity. These findings will provide a definite basis for discussion to understand the viscoelasticity in transient networks.

A Micro-Scale Non-Linear Finite Element Model to Optimize the Mechanical Behavior of Bioprinted Constructs

Extrusion-based bioprinting is an enabling biofabrication technique that is used to create heterogeneous tissue constructs according to patient-specific geometries and compositions. The optimization of bioinks as per requirements for specific tissue applications is an essential exercise in ensuring clinical translation of the bioprinting technologies. Most notably, optimum hydrogel polymer concentrations are required to ensure adequate mechanical properties of bioprinted constructs without causing significant shear stresses on cells. However, experimental iterations are often tedious for optimizing the bioink properties. In this work, a nonlinear finite element modeling approach has been undertaken to determine the effect of different bioink parameters such as composition, concentration on the range of stresses being experienced by the cells in the bioprinted construct. The stress distribution of the cells at different parts of the constructs has also been modeled. It is found that both bioink chemical compositions and concentrations can substantially alter the stress effects experienced by the cells. Concentrated regions of softer cells near pore regions were found to increase stress concentrations by almost three times compared with stress generated in cells away from the pores. The study provides a method for rapid optimization of bioinks, design of bioprinted constructs, as well as toolpath plans for fabricating constructs with homogenous properties.

Experimental investigation of anomalous molecular probe diffusion in entangled polymer melts

Investigations on the diffusion of small molecules or particles in polymeric materials are important to numerous technologies and can also be used to gain insight on polymer chain dynamics. Systems where the probe size is comparable to (or smaller than) a characteristic length of the polymer chain, the tube diameter for example, are of particular interest because the diffusion coefficient of the probe can be orders of magnitude larger than the value predicted by the Stokes-Einstein relation. In the present study, we employ the optical technique known as forced Rayleigh scattering to study the diffusion of a molecular probe (dye) in several entangled polymer melts over a wide range of length and time scales. The probe size is much smaller than the tube diameter for the systems studied. We find the diffusion coefficient is larger by four to five orders of magnitude than the Stokes-Einstein prediction. More interestingly, we observe anomalous, non-Fickian, diffusion where the value of the measured diffusion coefficient can abruptly change by as much as 50%. We suggest that this unexpected behavior occurs when the time scale for diffusion is larger than the relaxation time associated with the constraint release mechanism for polymer chain dynamics.

CENTAUR-The small- and wide-angle neutron scattering diffractometer/spectrometer for the Second Target Station of the Spallation Neutron Source

CENTAUR has been selected as one of the eight initial instruments to be built at the Second Target Station (STS) of the Spallation Neutron Source at Oak Ridge National Laboratory. It is a small-angle neutron scattering (SANS) and wide-angle neutron scattering (WANS) instrument with diffraction and spectroscopic capabilities. This instrument will maximally leverage the high brightness of the STS source, the state-of-the-art neutron optics, and a suite of detectors to deliver unprecedented capabilities that enable measurements over a wide range of length scales with excellent resolution, measurements on smaller samples, and time-resolved investigations of evolving structures. Notably, the simultaneous WANS and diffraction capability will be unique among neutron scattering instruments in the United States. This instrument will provide much needed capabilities for soft matter and polymer sciences, geology, biology, quantum condensed matter, and other materials sciences that need in situ and operando experiments for kinetic and/or out-of-equilibrium studies. Beam polarization and a high-resolution chopper will enable detailed structural and dynamical investigations of magnetic and quantum materials. CENTAUR's excellent resolution makes it ideal for low-angle diffraction studies of highly ordered large-scale structures, such as skyrmions, shear-induced ordering in colloids, and biomembranes. Additionally, the spectroscopic mode of this instrument extends to lower momentum transfers than are currently possible with existing spectrometers, thereby providing a unique capability for inelastic SANS studies.

Experimental Comparison of Bond Lifetime and Viscoelastic Relaxation in Transient Networks with Well-Controlled Structures

We demonstrate an experimental comparison of the bond lifetime, estimated using surface plasmon resonance (SPR), and the viscoelastic relaxation time of transient networks with well-controlled structures (dynamically cross-linked Tetra-PEG gel). SPR and viscoelastic measurements revealed that the temperature dependences of the two characteristic times are in agreement, while the viscoelastic response is delayed with respect to the lifetime by a factor of 2-3, dependent on the network strand length. Polymers cross-linked by temporary interactions form transient networks, which show fascinating viscoelasticity with a single relaxation mode. However, the molecular understanding of such simple viscoelasticity has remained incomplete because of the difficulty of experimentally evaluating bond lifetimes and heterogeneous structures in conventional transient networks. Our results suggest that bond dissociation and recombination both contribute to the macromechanical response. This report on direct bond-lifetime-viscoelastic-relaxation time comparison provides important information for the molecular design of transient network materials.

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.

A General DNA-Gated Hydrogel Strategy for Selective Transport of Chemical and Biological Cargos

The selective transport of molecular cargo is critical in many biological and chemical/materials processes and applications. Although nature has evolved highly efficient in vivo biological transport systems, synthetic transport systems are often limited by the challenges associated with fine-tuning interactions between cargo and synthetic or natural transport barriers. Herein, deliberately designed DNA-DNA interactions are explored as a new modality for selective DNA-modified cargo transport through DNA-grafted hydrogel supports. The chemical and physical characteristics of the cargo and hydrogel barrier, including the number of nucleic acid strands on the cargo (i.e., the cargo valency) and DNA-DNA binding strength, can be used to regulate the efficiency of cargo transport. Regimes exist where a cargo-barrier interaction is attractive enough to yield high selectivity yet high mobility, while there are others where the attractive interactions are too strong to allow mobility. These observations led to the design of a DNA-dendron transport tag, which can be used to universally modify macromolecular cargo so that the barrier can differentiate specific species to be transported. These novel transport systems that leverage DNA-DNA interactions provide new chemical insights into the factors that control selective cargo mobility in hydrogels and open the door to designing a wide variety of drug/probe-delivery systems.

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.

Mechanics of 3D Cell-Hydrogel Interactions: Experiments, Models, and Mechanisms

Hydrogels are highly water-swollen molecular networks that are ideal platforms to create tissue mimetics owing to their vast and tunable properties. As such, hydrogels are promising cell-delivery vehicles for applications in tissue engineering and have also emerged as an important base for ex vivo models to study healthy and pathophysiological events in a carefully controlled three-dimensional environment. Cells are readily encapsulated in hydrogels resulting in a plethora of biochemical and mechanical communication mechanisms, which recapitulates the natural cell and extracellular matrix interaction in tissues. These interactions are complex, with multiple events that are invariably coupled and spanning multiple length and time scales. To study and identify the underlying mechanisms involved, an integrated experimental and computational approach is ideally needed. This review discusses the state of our knowledge on cell-hydrogel interactions, with a focus on mechanics and transport, and in this context, highlights recent advancements in experiments, mathematical and computational modeling. The review begins with a background on the thermodynamics and physics fundamentals that govern hydrogel mechanics and transport. The review focuses on two main classes of hydrogels, described as semiflexible polymer networks that represent physically cross-linked fibrous hydrogels and flexible polymer networks representing the chemically cross-linked synthetic and natural hydrogels. In this review, we highlight five main cell-hydrogel interactions that involve key cellular functions related to communication, mechanosensing, migration, growth, and tissue deposition and elaboration. For each of these cellular functions, recent experiments and the most up to date modeling strategies are discussed and then followed by a summary of how to tune hydrogel properties to achieve a desired functional cellular outcome. We conclude with a summary linking these advancements and make the case for the need to integrate experiments and modeling to advance our fundamental understanding of cell-matrix interactions that will ultimately help identify new therapeutic approaches and enable successful tissue engineering.

Physics of the Nuclear Pore Complex: Theory, Modeling and Experiment

The hallmark of eukaryotic cells is the nucleus that contains the genome, enclosed by a physical barrier known as the nuclear envelope (NE). On the one hand, this compartmentalization endows the eukaryotic cells with high regulatory complexity and flexibility. On the other hand, it poses a tremendous logistic and energetic problem of transporting millions of molecules per second across the nuclear envelope, to facilitate their biological function in all compartments of the cell. Therefore, eukaryotes have evolved a molecular "nanomachine" known as the Nuclear Pore Complex (NPC). Embedded in the nuclear envelope, NPCs control and regulate all the bi-directional transport between the cell nucleus and the cytoplasm. NPCs combine high molecular specificity of transport with high throughput and speed, and are highly robust with respect to molecular noise and structural perturbations. Remarkably, the functional mechanisms of NPC transport are highly conserved among eukaryotes, from yeast to humans, despite significant differences in the molecular components among various species. The NPC is the largest macromolecular complex in the cell. Yet, despite its significant complexity, it has become clear that its principles of operation can be largely understood based on fundamental physical concepts, as have emerged from a combination of experimental methods of molecular cell biology, biophysics, nanoscience and theoretical and computational modeling. Indeed, many aspects of NPC function can be recapitulated in artificial mimics with a drastically reduced complexity compared to biological pores. We review the current physical understanding of the NPC architecture and function, with the focus on the critical analysis of experimental studies in cells and artificial NPC mimics through the lens of theoretical and computational models. We also discuss the connections between the emerging concepts of NPC operation and other areas of biophysics and bionanotechnology.

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.

Characterization of MIPS in a suspension of repulsive active Brownian particles through dynamical features

We study a two-dimensional system composed by Active Brownian Particles (ABPs), focusing on the onset of Motility Induced Phase Separation (MIPS), by means of molecular dynamics simulations. For a pure hard-disk system with no translational diffusion, the phase diagram would be completely determined by their density and Péclet number. In our model, two additional effects are present: translational noise and the overlap of particles; we study the effects of both in the phase space. As we show, the second effect can be mitigated if we use, instead of the standard Weeks-Chandler-Andersen potential, a stiffer potential: the pseudo-hard sphere potential. Moreover, in determining the boundary of our phase space, we explore different approaches to detect MIPS and conclude that observing dynamical features, via the non-Gaussian parameter, is more efficient than observing structural ones, such as through the local density distribution function. We also demonstrate that the Vogel-Fulcher equation successfully reproduces the decay of the diffusion as a function of density, with the exception of very high densities. Thus, in this regard, the ABP system behaves similar to a fragile glass.

Dynamics and healing behavior of metallosupramolecular polymers

Self-healing or healable polymers can recuperate their function after physical damage. This process involves diffusion of macromolecules across severed interfaces until the structure of the interphase matches that of the pristine material. However, monitoring this nanoscale process and relating it to the mechanical recovery remain elusive. We report that studying diffusion across healed interfaces and a correlation of contact time, diffusion depth, and mechanical properties is possible when two metallosupramolecular polymers assembled with different lanthanoid salts are mended. The materials used display similar properties, while the metal ions can be tracked with high spatial resolution by energy-dispersive x-ray spectrum imaging. We find that healing actual defects requires an interphase thickness in excess of 100 nm, 10 times more than previously established for self-adhesion of smooth films of glassy polymers.

Future trends in synchrotron science at NSLS-II

In this paper, we summarize briefly some of the future trends in synchrotron science as seen at the National Synchrotron Light Source II, a new, low emittance source recently commissioned at Brookhaven National Laboratory. We touch upon imaging techniques, the study of dynamics, the increasing use of multimodal approaches, the vital importance of data science, and other enabling technologies. Each are presently undergoing a time of rapid change, driving the field of synchrotron science forward at an ever increasing pace. It is truly an exciting time and one in which Roger Cowley, to whom this journal issue is dedicated, would surely be both invigorated by, and at the heart of.

From Microscale to Macroscale: Nine Orders of Magnitude for a Comprehensive Modeling of Hydrogels for Controlled Drug Delivery

Because of their inherent biocompatibility and tailorable network design, hydrogels meet an increasing interest as biomaterials for the fabrication of controlled drug delivery devices. In this regard, mathematical modeling can highlight release mechanisms and governing phenomena, thus gaining a key role as complementary tool for experimental activity. Starting from the seminal contribution given by Flory-Rehner equation back in 1943 for the determination of matrix structural properties, over more than 70 years, hydrogel modeling has not only taken advantage of new theories and the increasing computational power, but also of the methods offered by computational chemistry, which provide details at the fundamental molecular level. Simulation techniques such as molecular dynamics act as a "computational microscope" and allow for obtaining a new and deeper understanding of the specific interactions between the solute and the polymer, opening new exciting possibilities for an in silico network design at the molecular scale. Moreover, system modeling constitutes an essential step within the "safety by design" paradigm that is becoming one of the new regulatory standard requirements also in the field-controlled release devices. This review aims at providing a summary of the most frequently used modeling approaches (molecular dynamics, coarse-grained models, Brownian dynamics, dissipative particle dynamics, Monte Carlo simulations, and mass conservation equations), which are here classified according to the characteristic length scale. The outcomes and the opportunities of each approach are compared and discussed with selected examples from literature.

Mechanisms of Diffusion in Associative Polymer Networks: Evidence for Chain Hopping

Networks assembled by reversible association of telechelic polymers constitute a common class of soft materials. Various mechanisms of chain migration in associative networks have been proposed; yet there remains little quantitative experimental data to discriminate among them. Proposed mechanisms for chain migration include multichain aggregate diffusion as well as single-chain mechanisms such as "walking" and "hopping", wherein diffusion is achieved by either partial ("walking") or complete ("hopping") disengagement of the associated chain segments. Here, we provide evidence that hopping can dominate the effective diffusion of chains in associative networks due to a strong entropic penalty for bridge formation imposed by local network structure; chains become conformationally restricted upon association with two or more spatially separated binding sites. This restriction decreases the effective binding strength of chains with multiple associative domains, thereby increasing the probability that a chain will hop. For telechelic chains this manifests as binding asymmetry, wherein the first association is effectively stronger than the second. We derive a simple thermodynamic model that predicts the fraction of chains that are free to hop as a function of tunable molecular and network properties. A large set of self-diffusivity measurements on a series of model associative polymers finds good agreement with this model.