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We have quantified the structure of the colloidal gas-liquid interface using synchrotron X-ray reflectivity measurements on a model colloid-polymer mixture. The interfacial width shows mean-field scaling with the colloid density difference, and the density profiles appear to be monotonic. Furthermore, our measurements allow us to distinguish between different theoretical polymer descriptions commonly used to model colloid-polymer mixtures. Our results highlight the importance of capturing the correct polymer physics in obtaining a quantitative theoretical description of the colloidal gas-liquid interface.

Herein, sequence-controlled polymerization and sequential Ugi-4CR/thiol–yne click reactions inspired a novel synthetic strategy for preparing a well-defined multigraft polymer in which the sequence-controlled amino-functionalized backbones were converted to mono- or di-modular alkynyl-functionalized main chains via an Ugi-4CR and clicked with well-defined thiol end-functionalized polystyrene branches through the “graft-onto” method. The Ugi-4CR showed high conversions (above 91%), while the efficiencies for the thiol–yne click reaction were above 97%. Meanwhile, an innovative concept of “polymeric topological isomers” that had similar molecular weights but different grafted structures was proposed for the first time. These four well-defined multigraft isomeric polymers (mono-brush polymer, double-brush polymer, mono-comb polymer and double-comb polymer) provide a high-level platform for polymer physics studies. Through preliminary measurements, the dilute solution properties were found to be significantly different and to change regularly with variations in the grafted structures.

Lignin solubilization is key to a viable biorefinery because its removal leads to facile deconstruction of biomass and because the isolated lignin can serve to derive precursors of novel high-value materials. The mixing of organic solvents with water has been shown to improve biomass fractionation and lignin conversion reactions. However, generally-applicable solubilization strategies are lacking because of the remarkable variability of lignin across plant feedstocks. Here, to obtain a predictive understanding of lignin solvation, we perform molecular dynamics simulations of model lignin polymers in two mixtures of water with polar aprotic solvents: tetrahydrofuran (THF) : water and γ-valerolactone (GVL) : water. The model lignins include H-, G- and S-only homopolymers and lignins with an S : G 1 : 1 ratio. We find that a well-established theory of self-avoiding polymers in a "good"solvent describes accurately the physical conformations of all types of lignin in both solvents. As the degree of methoxy substitution increases in the homopolymers, the distributions of the lignin radius of gyration and the Flory exponent ν, which describes the lignin-solvent interactions, do not change in THF : water, while ν shifts to slightly higher values in GVL : water. We attribute this increase to the interaction between the methyl group of GVL with the lignin methoxy groups. We also find that the reduction in the lignin radius of gyration due to branching is accurately described by the Zimm-Stockmayer theory for both THF : water and GVL : water. The above findings validate the applicability of polymer physics concepts to lignin and suggest that GVL : water may have the most favorable interaction with S-lignin, whereas the interactions of THF : water with lignin are independent of lignin monomeric content. This research was supported by the Genomic Science Program, Office of Biological and Environmental Research, U.S. Department of Energy (DOE), under Contract FWP ERKP752. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U. S. Department of Energy under Contract No. DE-AC02-05CH11231. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for DOE under Contract DE-AC05-00OR22725.

Tailoring interfaces with polymer brushes is a commonly used strategy to create functional materials for numerous applications. Existing methods are limited in brush thickness, the ability to generate high-density brushes of biopolymers, and the potential for regeneration. Here we introduce a scheme to synthesize ultra-thick regenerating hyaluronan polymer brushes using hyaluronan synthase. The platform provides a dynamic interface with tunable brush heights that extend up to 20 microns – two orders of magnitude thicker than standard brushes. The brushes are easily sculpted into micropatterned landscapes by photo-deactivation of the enzyme. Further, they provide a continuous source of megadalton hyaluronan or they can be covalently-stabilized to the surface. Stabilized brushes exhibit superb resistance to biofilms, yet are locally digested by fibroblasts. This brush technology provides opportunities in a range of arenas including regenerating tailorable biointerfaces for implants, wound healing or lubrication as well as fundamental studies of the glycocalyx and polymer physics., Polymer brushes are often used to functionalise surfaces. Here, the authors report on the creation of high-density, regenerating hyaluronan brushes using hyaluronan synthase enzymes which can be patterned by photo-deactivation and demonstrate biocompatibility and resistance to biofilm formation.

This study aims to use molecular dynamics (MD) simulations of Kremer–Grest (KG) chains to inform future developments of models of entangled polymer dynamics. We perform nonequilibrium MD simulations, under shear flow, for well‐entangled KG chains. We study chains of 512 and 1000 KG beads, corresponding to 8 and 15 entanglements, respectively. We compute the linear rheological properties from equilibrium simulations of the stress autocorrelation and obtain from these data the tube model parameters. Under nonlinear shear flow, we compute the shear viscosity, the first and second normal stress differences, and chain contour length. For chains of 512 monomers, we obtain agreement with the results of Cao and Likhtman (ACS Macro. Lett. 2015, 4, 1376). We also compare our nonlinear results with the Graham, Likhtman and Milner‐McLeish (GLaMM) model. We identify some systematic disagreement that becomes larger for the longer chains. We made a comparison of the transient shear stress maximum from our simulations, two nonlinear models and experiments on a wide range of melts and solutions, including polystyrene (PS), polybutadiene, and styrene–butadiene rubber. This comparison establishes that the PS melt data show markedly different behavior to all other melts and solutions and KG simulations reproduce the PS data more closely than either the GLaMM or Xie and Schweizer models. We discuss the performance of these models against the data and simulations. Finally, by imposing a rapid reversing flow, we produce a method to extract the recoverable strain from MD simulations, valid for sufficiently entangled monodisperse polymers. We explore how the resulting data can probe the melt state just before the reversing flow. © 2019 The Authors. Journal of Polymer Science Part B: Polymer Physics published by Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019, 57, 1692–1704

The next materials challenge in organic stretchable electronics is the development of a fully degradable semiconductor that maintains stable electrical performance under strain. Herein, we decouple the design of stretchability and transience by harmonizing polymer physics principles and molecular design in order to demonstrate for the first time a material that simultaneously possesses three disparate attributes: semiconductivity, intrinsic stretchability, and full degradability. We show that we can design acid-labile semiconducting polymers to appropriately phase segregate within a biodegradable elastomer, yielding semiconducting nanofibers that concurrently enable controlled transience and strain-independent transistor mobilities. Along with the future development of suitable conductors and device integration advances, we anticipate that these materials could be used to build fully biodegradable diagnostic or therapeutic devices that reside inside the body temporarily, or environmental monitors that are placed in the field and break down when they are no longer needed. This fully degradable semiconductor represents a promising advance toward developing multifunctional materials for skin-inspired electronic devices that can address previously inaccessible challenges and in turn create new technologies., A concurrently stretchable and degradable semiconducting polymeric system with strain-independent electrical performance is achieved by harnessing both polymer chemistry and polymer physics.

Since the discovery of conductive poly(acetylene), the study of conjugated polymers has remained an active and interdisciplinary frontier between polymer chemistry, polymer physics, computation, and device engineering. One of the ultimate goals of polymer science is to reliably synthesize structures, similar to small molecule synthesis. Kumada catalyst-transfer polymerization (KCTP) is a powerful tool for synthesizing conjugated polymers with predictable molecular weights, narrow dispersities, specific end groups, and complex backbone architectures. However, expanding the monomer scope beyond the well-studied 3-alkylthiophenes to include electron-deficient and complex heterocycles has been difficult. Revisiting the successful applications of KCTP can help us gain new insight into the CTP mechanisms and thus inspire breakthroughs in the controlled polymerization of challenging π-conjugated monomers.In this Account, we highlight our efforts over the past decade to achieve controlled synthesis of homopolymers (p-type and n-type), copolymers (diblock and statistical), and monodisperse high oligomers. We first give a brief introduction of the mechanism and state-of-the-art of KCTP. Since the extent of polymerization control is determined by steric and electronic effects of both the catalyst and monomer, the polymerization can be optimized by modifying monomer and catalyst structures, as well as finding a well-matched monomer-catalyst system. We discuss the effects of side-chain steric hindrance and halogens in the context of heavy atom substituted monomers. By moving the side-chain branch point one carbon atom away from the heterocycle to alleviate steric crowding and stabilize the catalyst resting state, we were able to successfully control the polymerization of new tellurophene monomers. Inspired by innocent role of the sterically encumbered 2-transmetalated 3-alkylthiophene monomer, we introduce the treatment of hygroscopic monomers with a bulky Grignard compound as a water-scavenger for the improved synthesis of water-soluble conjugated polymers. For challenging electron-deficient monomers, we discuss the design of new Ni(II)diimine catalysts with electron-donating character which enhance the stability of the association complex between the catalyst and the growing polymer chain, resulting in the quasi-living synthesis of n-type polymers. Beyond n-type homopolymers, the Ni(II)diimine catalysts are also capable of producing electron-rich and electron-deficient diblock and statistical copolymers. We discuss how density functional theory (DFT) calculations elucidate the role of catalyst steric and electronic effects in controlling the synthesis of π-conjugated polymers. Moreover, we demonstrate the synthesis of monodisperse high oligomers by temperature cycling, which takes full advantage of the unique character of KCTP in that it proceeds through distinct intermediates that are not reactive. The insight we gained thus far leads to the first example of isolated living conjugated polymer chains prepared by a standard KCTP procedure, with general applicability to different monomers and catalytic systems. In summarizing a decade of innovation in KCTP, we hope this Account will inspire future development in the field to overcome key challenges including the controlled synthesis of electron-deficient heterocycles, complex and high-performance systems, and degradable and recyclable materials as well as cutting-edge catalyst design.

The three-dimensional (3D) structure of chromatin is intrinsically associated with gene regulation and cell function1–3. Methods based on chromatin conformation capture have mapped chromatin structures in neuronal systems such as in vitro differentiated neurons, neurons isolated through fluorescence-activated cell sorting from cortical tissues pooled from different animals and from dissociated whole hippocampi4–6. However, changes in chromatin organization captured by imaging, such as the relocation of Bdnf away from the nuclear periphery after activation7, are invisible with such approaches8. Here we developed immunoGAM, an extension of genome architecture mapping (GAM)2,9, to map 3D chromatin topology genome-wide in specific brain cell types, without tissue disruption, from single animals. GAM is a ligation-free technology that maps genome topology by sequencing the DNA content from thin (about 220 nm) nuclear cryosections. Chromatin interactions are identified from the increased probability of co-segregation of contacting loci across a collection of nuclear slices. ImmunoGAM expands the scope of GAM to enable the selection of specific cell types using low cell numbers (approximately 1,000 cells) within a complex tissue and avoids tissue dissociation2,10. We report cell-type specialized 3D chromatin structures at multiple genomic scales that relate to patterns of gene expression. We discover extensive ‘melting’ of long genes when they are highly expressed and/or have high chromatin accessibility. The contacts most specific of neuron subtypes contain genes associated with specialized processes, such as addiction and synaptic plasticity, which harbour putative binding sites for neuronal transcription factors within accessible chromatin regions. Moreover, sensory receptor genes are preferentially found in heterochromatic compartments in brain cells, which establish strong contacts across tens of megabases. Our results demonstrate that highly specific chromatin conformations in brain cells are tightly related to gene regulation mechanisms and specialized functions., A new technique called immunoGAM, which combines genome architecture mapping (GAM) with immunoselection, enabled the discovery of specialized chromatin conformations linked to gene expression in specific cell populations from mouse brain tissues.

International audience; Mechanistic modeling in biology allows to investigate, based on first principles, if putative hypotheses are compatible with observations and to drive further experimental works. Along this line, polymer modeling has been instrumental in 3D genomics to better understand the impact of key mechanisms on the spatial genome organization. Here, I describe how polymer-based models can be practically used to study the role of epigenome in chromosome folding. I illustrate this methodology in the context of Drosophila epigenome folding.

We present computer simulations of a dynamic Monte Carlo algorithm for polymer chains on the FCC lattice which takes explicitly into account the possibility to overcome topological constraints by controlling the rate at which nearby polymer strands may cross through each other. By applying the method to systems of interacting ring polymers at melt conditions, we characterize their structure and dynamics by measuring, in particular, the amounts of knots and links which are formed during the relaxation process. In comparison to standard melts of unknotted and unconcatenated rings, our simulations demonstrate that the mechanism of strand crossing is responsible for fluidizing the melt provided the time scale of the process is faster than the internal relaxation of the chain, in agreement with recent experiments employing solutions of DNA rings in the presence of the type II topoisomerase enzyme. In the opposite case of slow rates the melt is shown to become slower, and this prediction may be easily validated experimentally., 12 pages, 9 figures in the main text, 8 supplementary figures. Submitted for publication

Chain molecules play a key role in the polymer field and in living cells. Our focus is on a new homopolymer model of a linear chain molecule subject to an attractive self-interaction promoting compactness. We analyze the model using simple analytic arguments complemented by extensive computer simulations. We find several striking results: there is a first order transition from a high temperature random coil phase to a highly unusual low temperature phase; the modular ground states exhibit significant degeneracy; the ground state structures exhibit spontaneous dimensional reduction and have a two-layer structure; and the ground states are assembled from secondary motifs of helices and strands connected by tight loops. We discuss the similarities and notable differences between the ground state structures (we call these PoSSuM -- Planar Structures with Secondary Motifs) in the novel phase and protein native state structures., 14 pages, 5 figures

Polymers with precisely defined monomeric sequences present an exquisite tool for controlling material properties by harnessing both the robustness of synthetic polymers and the ability to tailor the inter- and intramolecular interactions so crucial to many biological materials. While polymer scientists traditionally synthesized and studied the physics of long molecules best described by their statistical nature, many biological polymers derive their highly tailored functions from precisely controlled sequences. Therefore, significant effort has been applied toward developing new methods of synthesizing, characterizing, and understanding the physics of non-natural sequence-defined polymers. This perspective considers the synergistic advantages that can be achieved via tailoring both precise sequence control and attributes of traditional polymers in a single system. Here, we focus on the potential of sequence-defined polymers in highly associating systems, with a focus on the unique properties, such as enhanced proton conductivity, that can be attained by incorporating sequence. In particular, we examine these materials as key model systems for studying previously unresolvable questions in polymer physics including the role of chain shape near interfaces and how to tailor compatibilization between dissimilar polymer blocks. Finally, we discuss the critical challenges-in particular, truly scalable synthetic approaches, characterization and modeling tools, and robust control and understanding of assembly pathways-that must be overcome for sequence-defined polymers to attain their potential and achieve ubiquity.

A fundamental paradigm in polymer physics is that macromolecular conformations in equilibrium can be described by universal scaling laws, being key for structure, dynamics, and function of soft (biological) matter and in the materials sciences. Here, we reveal that during diffusion-influenced, nonequilibrium chain-growth polymerization, scaling laws change qualitatively, in particular, the growing polymers exhibit a surprising self-avoiding walk (SAW) behavior in poor and theta-solvents. Our analysis, based on monomer-resolved reaction-diffusion computer simulations, demonstrates that this phenomenon is a result of i) nonequilibrium monomer density depletion correlations around the active polymerization site, leading to a locally directed and self-avoiding growth, in conjunction with ii) chain (Rouse) relaxation times larger than the competing polymerization reaction time. These intrinsic nonequilibrium mechanisms are facilitated by fast and persistent reaction-driven diffusion (sprints) of the active site, with analogies to pseudo-chemotactic active Brownian particles. Our findings have implications for time-controlled structure formation in polymer processing, as in, e.g., reactive self-assembly, photo-crosslinking, and 3D printing., 15 pages, 8 figures

Polyelectrolyte complex micelles (PCMs) are a unique class of self-assembled nanoparticles that form with a core of associated polycations and polyanions, microphase-separated from neutral, hydrophilic coronas in aqueous solution. The hydrated nature and structural and chemical versatility make PCMs an attractive system for delivery and for fundamental polymer physics research. By leveraging block copolymer design with controlled self-assembly, fundamental structure-property relationships can be established to tune the size, morphology, and stability of PCMs precisely in pursuit of tailored nanocarriers, ultimately offering storage, protection, transport, and delivery of active ingredients. This perspective highlights recent advances in predictive PCM design, focusing on (i) structure-property relationships to target specific nanoscale dimensions and shapes and (ii) characterization of PCM dynamics primarily using time-resolved scattering techniques. We present several vignettes from these two emerging areas of PCM research and discuss key opportunities for PCM design to advance precision medicine.

α1-Antitrypsin is a protease inhibitor belonging to the serpin family. Serpin polymerisation is at the core of a class of genetic conformational diseases called serpinopathies. These polymers are known to be unbranched, flexible, and heterogeneous in size with a beads-on-a-string appearance viewed by negative stain electron microscopy. Here, we use atomic force microscopy and time-lapse dynamic light scattering to measure polymer size and shape for wild-type (M) and Glu342→Lys (Z) α1-antitrypsin, the most common variant that leads to severe pathological deficiency. Our data for small polymers deposited onto mica and in solution reveal a power law relation between the polymer size, namely the end-to-end distance or the hydrodynamic radius, and the polymer mass, proportional to the contour length. We use the scaling concepts of polymer physics to assess that α1-antitrypsin polymers are random linear chains with a low persistence length.

The dynamics of polymer-nanoparticle (NP) mixtures, which involves multiple scales and system-specific variables, has posed a long-standing challenge on its theoretical description. In this paper, we construct a microscopic theory for polymer diffusion in the mixtures based on a combination of generalized Langevin equation, mode-coupling approach, and polymer physics ideas. The parameter-free theory has an explicit expression and remains tractable on pair correlation level with system-specific equilibrium structures as input. Taking a minimal polymer-NP mixture as an example, our theory correctly captures the dependence of polymer diffusion on NP concentration and average interparticle distance. Importantly, the polymer diffusion exhibits a power law decay as the polymer length increases at dense NPs and/or long chain, which marks the emergence of entanglement-like motion. The work provides a first-principle theoretical foundation to investigate dynamic problems in diverse polymer nanocomposites., 10 pages, 6 figures

Novel technologies are revealing that chromosomes have a complex three-dimensional organization within the cell nucleus that serves functional purposes. Models from polymer physics have been developed to quantitively understand the molecular principles controlling their structure and folding mechanisms. Here, by using massive molecular-dynamics simulations we show that classical scaling laws combined with finite-size effects of a simple polymer model can effectively explain the scaling behavior that chromatin exhibits at the topologically associating domains level, as revealed by experimental observations. Model results are then validated against recently published high-resolution in situ Hi-C data.

Sampling equilibrium ensembles of dense polymer mixtures is a paradigmatically hard problem in computational physics, even in lattice-based models. Here, we develop a formalism based on interacting binary tensors that allows for tackling this problem using quantum annealing machines. Our approach is general in that properties such as self-avoidance, branching, and looping can all be specified in terms of quadratic interactions of the tensors. Microstates realizations of different lattice polymer ensembles are then seamlessly generated by solving suitable discrete energy-minimization problems. This approach enables us to capitalize on the strengths of quantum annealing machines, as we demonstrate by sampling polymer mixtures from low to high densities, using the D-Wave quantum computer. Our systematic approach offers a promising avenue to harness the rapid development of quantum computers for sampling discrete models of filamentous soft-matter systems., Supplementary Material Included

Polyelectrolyte brushes are important stimuli-responsive materials in a variety of technological applications as well as in biological systems. Their small size, however, introduces characterization challenges, particularly in studying 3D structure and time-dependent behavior. In this Letter, we report on the polyelectrolyte brush behavior of extra-large hyaluronan brushes (∼15 μm) recently developed using an enzyme-mediated growth process. In response to increasing ionic strength, the brush displays the osmotic brush regime and the salted brush regime. We also show a collapse of 96% when the brush is placed in a poor solvent. This collapse is rapid when changing from a good to poor solvent, but re-expansion is slow when changing back to a good solvent. The observed brush behavior described in this Letter is similar to that seen for smaller polyelectrolyte brushes, indicating that these larger brushes may serve as model systems to study more complex phenomena through confocal microscopy.

The nonlinear rheology of multilayer stacks of alternating isotactic polypropylene (PP) and polyethylene (PE) films with N layers was measured in shear and uniaxial extension. We show that the force to extend N − 1 interfaces can lead to strain hardening. We studied three PE/PP pairs: a Ziegler–Natta catalyzed pair and two metallocene pairs, one with high density PE and one with linear low density PE. Interfacial tension was measured on matrix/droplet blends of each pair using small amplitude oscillatory shear measurements fitted with the Palierne model. Multilayer coextrusion was used to fabricate bilayers and sheets with hundreds of layers for each polyolefin pair. Under shear deformation, disentangling of chains in the N − 1 interfaces led to a decrease in the overall shear viscosity, which is interpreted as an interfacial slip velocity and is in agreement with previous studies on multilayer films. Under extensional flows, the multilayers exhibited an increased transient extensional viscosity (tensile stress growth coefficient, η E , M +) and pronounced strain hardening, even when the constituent homopolymers exhibited no strain hardening behavior. A model based on a force summation was developed to predict this behavior with interfacial tension as a fitting parameter; the extracted interfacial tensions agreed reasonably well with those from the Palierne model. The “slip in shear” and “hardening in extension” behaviors highlight the role of interfacial polymer physics during rheological measurements and polymer processing.

The accurate prediction of RNA secondary structure from primary sequence has had enormous impact on research from the past 40 years. Although many algorithms are available to make these predictions, the inclusion of non-nested loops, termed pseudoknots, still poses challenges arising from two main factors: 1) no physical model exists to estimate the loop entropies of complex intramolecular pseudoknots, and 2) their NP-complete enumeration has impeded their study. Here, we address both challenges. First, we develop a polymer physics model that can address arbitrarily complex pseudoknots using only two parameters corresponding to concrete physical quantities—over an order of magnitude fewer than the sparsest state-of-the-art phenomenological methods. Second, by coupling this model to exhaustive enumeration of the set of possible structures, we compute the entire free energy landscape of secondary structures resulting from a primary RNA sequence. We demonstrate that for RNA structures of ∼80 nucleotides, with minimal heuristics, the complete enumeration of possible secondary structures can be accomplished quickly despite the NP-complete nature of the problem. We further show that despite our loop entropy model’s parametric sparsity, it performs better than or on par with previously published methods in predicting both pseudoknotted and non-pseudoknotted structures on a benchmark data set of RNA structures of ≤80 nucleotides. We suggest ways in which the accuracy of the model can be further improved.

Internal dynamics of flexible polymer chains is one of the most important fundamental problems in polymer physics. Although numerous efforts have been devoted to the understanding of internal dynamics for linear polymers, little attention was paid to branched systems. This work aims to elucidate how the branching effect quantitatively influences the internal motions of long-subchain hyperbranched polymers in dilute solution. By light scattering study of four hyperbranched polystyrene samples with controlled branching patterns and low polydispersities (Mw/Mn < 1.40 and Mw ∼ 107 g/mol), we quantified and analyzed the asymptotic behavior of the reduced first cumulant [Γ* = Γ(q)/(q3kBT/η0)], the value of Γ* at high q-regime [the approximate values of Γ*(∞)], the scattering vector (q) dependence of linewidth [Γ(q)], the number of relaxation modes in Γ(q)-distribution curves, the characteristic relaxation time (τ1) of the first internal mode, and the q-dependent relative strength of internal motions. Our result...

The cells and tissues that make up our body manage contradictory mechanical demands. It is crucial for their survival to be able to withstand large mechanical loads, but it is equally crucial for them to produce forces and actively change shape during biological processes such as tissue growth and repair. The mechanics of cells and tissues is determined by scaffolds of protein polymers known as the cytoskeleton and the extracellular matrix, respectively. Experiments on model systems reconstituted from purified components combined with polymer physics concepts have already uncovered some of the mechanisms that underlie the paradoxical mechanics of living matter. Initial work focused on explaining universal features, such as the nonlinear elasticity of cells and tissues, in terms of polymer network models. However, there is a growing recognition that living matter exhibits many advanced mechanical functionalities that are not captured by these coarse-grained theories. Here, we review recent experimental and theoretical insights that reveal how the porous structure, structural hierarchy, transient crosslinking and mechanochemical activity of biopolymers confer resilience combined with the ability to adapt and self-heal. These physical concepts increase our understanding of cell and tissue biology and provide inspiration for advanced synthetic materials. Biopolymer networks provide mechanical integrity and enable active deformation of cells and tissues. Here, we review recent experimental and theoretical studies of the mechanical behaviour of biopolymer networks with a focus on reductionist approaches.

Significant parallels exist between the phase separation behavior of polymers in solution and the types of biomolecular condensates, or ‘membraneless organelles,’ that are of increasing interest in living systems. Liquid–liquid phase separation allows for compartmentalization and the sequestration of materials and can be harnessed as a sensitive strategy for responding to small changes in the environment. Here, I review many of the parallels and synergies between ongoing efforts to study and take advantage of phase separation in living versus synthetic materials.

Theoretical models of the conformational behavior of flexible polymer chains in mixed solvents enunciated in the world literature during the last decade are critically reviewed. Models describing different mechanisms of coil-to-globule transitions in a good solvent induced by cosolvent addition are highlighted. Special attention is given to the analysis of theoretical approaches to describing the collapse of polymer chains in binary mixtures of good solvents. The review addresses researchers engaged in polymer physics and chemistry and materials scientists involved in the design of smart polymers.

2D nanoslit devices, where two crystals with atomically flat surfaces are separated by only a few nanometers, have attracted considerable attention because their tunable control over the confinement allows for the discovery of unusual transport behavior of gas, water, and ions. Here, the passage of double-stranded DNA molecules is studied through nanoslits fabricated from exfoliated 2D materials, such as graphene or hexagonal boron nitride, and the DNA polymer behavior is examined in this tight confinement. Two types of events are observed in the ionic current: long current blockades that signal DNA translocation and short spikes where DNA enters the slits but withdraws. DNA translocation events exhibit three distinct phases in their current-blockade traces—loading, translation, and exit. Coarse-grained molecular dynamics simulation allows the different polymer configurations of these phases to be identified. DNA molecules, including folds and knots in their polymer structure, are observed to slide through the slits with near-uniform velocity without noticeable frictional interactions of DNA with the confining graphene surfaces. It is anticipated that this new class of 2D-nanoslit devices will provide unique ways to study polymer physics and enable lab-on-a-chip biotechnology.

Knots in long DNA molecules are prevalent in biological systems and serve as a model system for investigating static and dynamic properties of biopolymers. We explore the dynamics of knots in double-stranded DNA in a new regime of nanometer-scale confinement, large forces, and short time scales, using solid-state nanopores. We show that DNA knots undergo isomorphic translocation through a nanopore, retaining their equilibrium morphology by swiftly compressing in a lateral direction to fit the constriction. We observe no evidence of knot tightening or jamming, even for single-digit nanopores. We explain the observations as the malleability of DNA, characterized by sharp buckling of the DNA in nanopores, driven by the transient disruption of base pairing. Our molecular dynamics simulations support the model. These results are relevant not only for the understanding of DNA packing and manipulation in living cells but also for the polymer physics of DNA and the development of nanopore-based sequencing technologies.

The flow-induced self-assembly of entangled Bombyx mori silk proteins is hypothesised to be aided by the ‘registration’ of aligned protein chains using intermolecularly interacting ‘sticky’ patches. This suggests that upon chain alignment, a hierarchical network forms that collectively stretches and induces nucleation in a precisely controlled way. Through the lens of polymer physics, we argue that if all chains would stretch to a similar extent, a clear correlation length of the stickers in the direction of the flow emerges, which may indeed favour such a registration effect. Through simulations in both extensional flow and shear, we show that there is, on the other hand, a very broad distribution of protein–chain stretch, which suggests the registration of proteins is not directly coupled to the applied strain, but may be a slow statistical process. This qualitative prediction seems to be consistent with the large strains (i.e., at long time scales) required to induce gelation in our rheological measurements under constant shear. We discuss our perspective of how the flow-induced self-assembly of silk may be addressed by new experiments and model development.

Cataloged from PDF version of article. Thesis (M.S.): Bilkent University, Department of Physics, İhsan Doğramacı Bilkent University, 2021. Includes bibliographical references (leaves 46-48). The transport of polymers across membranes in electrolyte solutions happens in most biological systems and is necessary for cells to function. Moreover, the poly-mer translocation process has proven to be very important in experiments and applications as well, providing a rich source of information about the polymer’s size and composition [1], [2], making the polymer translocation procedure a po-tential sequencing method that is efficient, cheap, and quick [3], [4]. However, no consensus on the theoretical understanding of the translocation mechanism has been reached yet [3], leaving it a major challenge for theoretical modelling due to its steric, hydrodynamic, and electrostatic interactions [2], [5]. Here, we calculate the electrostatic energy cost of the translocating polymer in both the approach and translocation phases and investigate the dependence of the poly-mer’s grand potential on different model tunable parameters. In the case of neu-tral membranes, low permittivity carbon-based membranes repel the approaching polymer with energy magnitude between ∼ 11 kBT and ∼ 27 kBT , while high permittivity engineered membranes attract the approaching polymer with almost the same energy magnitude. This behavior can be attributed to polymer image-charge interactions, which become amplified with low permittivity membranes. In strong salt solutions, the membrane exhibits a repulsive barrier that turns to a metastable well in dilute solutions. In pure solvents, the metastable well becomes a deep, stable well that traps the polymer in the pore for some time, where the translocation phase is mainly governed by the attractive trans-cis side interac-tion. For weakly charged membranes, the membrane charge attraction wins over the image-charge repulsion, leading to an attractive minimum at zt ≈ −1 nm followed by a repulsive barrier at lt = L/2 while for stronger membrane charges, the attractive well turns to a metastable point followed by an attractive, stable well. These results suggest that, in translocation experiments, DNA motion can be controlled by tuning the system parameters, such as the solution concentration or the membrane charge. by Ghada Mahmoud Abdullah Mohamed M.S.

The random motion of a flexible molecular chain floating in a solvent or a melt can itself be quite complex. The discussion in this chapter starts with some basic concepts of an ideal polymer chain. It is then followed by classical models describing the dynamics and diffusion of polymer chains applicable to polymer melts. This chapter’s main objective is to contrast the differences between the mobility of polymer chains in melts (or solvents) and the kinetically trapped glassy state.

Understanding the mechanisms driving the folding of chromosomes in nuclei is a major goal of modern Molecular Biology. Recent technological advances in microscopy (FISH, STORM) and sequencing approaches (Hi-C, GAM, SPRITE) enabled to collect quantitative data about chromatin 3D architecture, revealing a non-random and highly specific organization. To transform such tremendous amount of data into valuable insights on genome folding, heavy computational analyses are required. Here, we study the performances of PRISMR, a computational tool based on Machine Learning strategies and Polymer Physics principles, to explore genome 3D structure from Genome Architecture Mapping (GAM) data. Using such data, we show that PRISMR can successfully reconstruct the 3D structure of real genomic regions at various length scales, from mega-base sized loci to whole chromosomes. Importantly, the inferred structures are validated against independent Hi-C data. Finally, we show how PRISMR can be effectively employed to explore differences between experimental methods.

The static light scattering (SLS) method is introduced with key equations used to extract quantitative information such as weight-average molecular weight, osmotic second virial coefficient, and radius of gyration from the experimental data. The use of Zimm plots to obtain visual cues of the polymer's characteristics is presented. A treatise of the thermodynamic process (modified by structural parameters) sensed by light scattering from a single atom, multiple atoms, fluids, small and large polymers is presented with reliance on a plethora of equations. The design of the SLS instrument as well as a few case studies of SLS applications are summarized to help the user understand the experiment better and to discern compromises in commercial instruments. The opportunity in combining DLS and SLS to obtain a complete picture of polymer characterization and polymer physics closes the loop on these light scattering techniques.