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Assemblies of peptides and proteins through specific intermolecular interactions set the basis for macroscopic materials found in nature. Peptides provide easily tunable hydrogen-bonding interactions, which can lead to the formation of ordered structures such as highly stable β-sheets that can form amyloid-like supramolecular peptide nanofibrils (PNFs). PNFs are of special interest, as they could be considered as mimics of various fibrillar structures found in nature. In their ability to serve as supramolecular scaffolds, they could mimic certain features of the extracellular matrix to provide stability, interact with pathogens such as virions, and transduce signals between the outside and inside of cells. Many PNFs have been reported that reveal rich bioactivities. PNFs supporting neuronal cell growth or lentiviral gene transduction have been studied systematically, and their material properties were correlated to bioactivities. However, the impact of the structure of PNFs, their dynamics, and stabilities on their unique functions is still elusive. Herein, we provide a microscopic view of the self-assembled PNFs to unravel how the amino acid sequence of self-assembling peptides affects their secondary structure and dynamic properties of the peptides within supramolecular fibrils. Based on sequence truncation, amino acid substitution, and sequence reordering, we demonstrate that peptide–peptide aggregation propensity is critical to form bioactive β-sheet-rich structures. In contrast to previous studies, a very high peptide aggregation propensity reduces bioactivity due to intermolecular misalignment and instabilities that emerge when fibrils are in close proximity to other fibrils in solution. Our multiscale simulation approach correlates changes in biological activity back to single amino acid modifications. Understanding these relationships could lead to future material discoveries where the molecular sequence predictably determines the macroscopic properties and biological activity. In addition, our studies may provide new insights into naturally occurring amyloid fibrils in neurodegenerative diseases.

Acrylic polymers, commonly used in paints, can degrade over time by several different chemical and physical mechanisms, depending on structure and exposure conditions. While exposure to UV light and temperature results in irreversible chemical damage, acrylic paint surfaces in museums can also accumulate pollutants, such as volatile organic compounds (VOCs) and moisture, that affect their material properties and stability. In this work, we studied the effects of different degradation mechanisms and agents on properties of acrylic polymers found in artists’ acrylic paints for the first time using atomistic molecular dynamics simulations. Through the use of enhanced sampling methods, we investigated how pollutants are absorbed into thin acrylic polymer films from the environment around the glass transition temperature. Our simulations suggest that the absorption of VOCs is favorable (−4 to −7 kJ/mol depending on VOCs), and the pollutants can easily diffuse and be emitted back into the environment slightly above glass transition temperature when the polymer is soft. However, typical environmental fluctuations in temperature (<16 °C) can lead for these acrylic polymers to transition to glassy state, in which case the trapped pollutants act as plasticizers and cause a loss of mechanical stability in the material. This type of degradation results in disruption of polymer morphology, which we investigate through calculation of structural and mechanical properties. In addition, we also investigate the effects of chemical damage, such as backbone bond scission and side-chain cross-linking reactions on polymer properties.

The prosperity and lifestyle of our society are very much governed by achievements in condensed matter physics, chemistry and materials science, because new products for sectors such as energy, the environment, health, mobility and information technology (IT) rely largely on improved or even new materials. Examples include solid-state lighting, touchscreens, batteries, implants, drug delivery and many more. The enormous amount of research data produced every day in these fields represents a gold mine of the twenty-first century. This gold mine is, however, of little value if these data are not comprehensively characterized and made available. How can we refine this feedstock; that is, turn data into knowledge and value? For this, a FAIR (findable, accessible, interoperable and reusable) data infrastructure is a must. Only then can data be readily shared and explored using data analytics and artificial intelligence (AI) methods. Making data 'findable and AI ready' (a forward-looking interpretation of the acronym) will change the way in which science is carried out today. In this Perspective, we discuss how we can prepare to make this happen for the field of materials science.

Board-shaped polymers form sanidic mesophases: assemblies of parallel lamellae of stacked polymer backbones separated by disordered side chains. Sanidics vary significantly with respect to polymer order inside their lamellae, making them “stepping stones” toward the crystalline state. Therefore, they are potentially interesting for studying crystallization and technological applications. Building on earlier mesoscopic models of the most disordered sanidics Σd, we focus on the other extreme, near-crystalline order, and develop a generic model that captures a highly ordered Σrmesophase. Polymers are described by generic hindered-rotation chains. Anisotropic nonbonded potentials, with strengths comparable to the thermal energy, mimic board-like monomer shapes. Lamellae equilibrated with Monte Carlo simulations, for a broad range of model parameters, have intralamellar order typical for Σrmesophases: periodically stacked polymers that are mutually registered along their backbones. Our mesophase shows registration on both monomer and chain levels. We calculate scattering patterns and compare with data published for highly ordered sanidic mesophases of two different polymers: polyesters and polypeptoids. Most of the generic structural features that were identified in these experiments are present in our model. However, our mesophase has correlations between chains located in different lamellae and is therefore closer to the crystalline state than the experimental samples.

We study active topological glass under spherical confinement, allowing us to exceed the chain lengths simulated previously and determine the critical exponents of the arrested conformations. We find a previously unresolved “tank-treading” dynamic mode of active segments along the ring contour. This mode can enhance active–passive phase separation in the state of active topological glass when both diffusional and conformational relaxation of the rings are significantly suppressed. Within the observational time, we see no systematic trends in the positioning of the separated active domains within the confining sphere. The arrested state exhibits coherent stochastic rotations. We discuss possible connections of the conformational and dynamic features of the system to chromosomes enclosed in the nucleus of a living cell.

Responsiveness of polypeptides and polymers in aqueous solution plays an important role in biomedical applications and in designing advanced functional materials. Elastin-like polypeptides (ELPs) are a well-known class of synthetic intrinsically disordered proteins (IDPs), which exhibit a lower critical solution temperature (LCST) in pure water and in aqueous solutions. Here, we compare the influence of cis/transproline isomerization on the phase behavior of single ELPs in pure water. Our results reveal that proline isomerization tunes the conformational behavior of ELPs while keeping the transition temperature unchanged. We find that the presence of the cisisomers facilitates compact structures by preventing peptide–water hydrogen bonding while promoting intramolecular interactions. In other words, the LCST transition of ELPs with all proline residues in the cisstate occurs with almost no noticeable conformational change.

Retroviral gene delivery is the key technique for in vitro and ex vivo gene therapy. However, inefficient virion‐cell attachment resulting in low gene transduction efficacy remains a major challenge in clinical applications. Adjuvants for ex vivo therapy settings need to increase transduction efficiency while being easily removed or degraded post‐transduction to prevent the risk of venous embolism after infusing the transduced cells back to the bloodstream of patients, yet no such peptide system have been reported thus far. In this study, peptide amphiphiles (PAs) with a hydrophobic fatty acid and a hydrophilic peptide moiety that reveal enhanced viral transduction efficiency are introduced. The PAs form β‐sheet‐rich fibrils that assemble into positively charged aggregates, promoting virus adhesion to the cell membrane. The block‐type amphiphilic sequence arrangement in the PAs ensures efficient cell‐virus interaction and biodegradability. Good biodegradability is observed for fibrils forming small aggregates and it is shown that via molecular dynamics simulations, the fibril‐fibril interactions of PAs are governed by fibril surface hydrophobicity. These findings establish PAs as additives in retroviral gene transfer, rivalling commercially available transduction enhancers in efficiency and degradability with promising translational options in clinical gene therapy applications. Peptide amphiphiles as enhancers of retroviral gene delivery through improved cell‐virus interaction and biodegradability are reported. The peptide amphiphiles exhibit comparable efficacy to existing transduction enhancers and hold promise for potential use in ex vivo gene therapy.

Steady-state shear viscosity η(γ̇) of unconcatenated ring polymer melts as a function of the shear rate γ̇ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z≈ 5 and Z≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ∼ γ̇–0.56 ± 0.02, independent of chain length, for Weissenberg numbers up to about 102. Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ∼ γ̇–0.57 ± 0.08for 4 ≤ Z≤ 57. Viscosity decreases with chain length for high γ̇. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi∼ 104, the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ∼ γ̇–0.57, we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large γ̇. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/γ̇. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

We study the effect of entanglements on the glass transition of high molecular weight polymers, by the comparison of single-chain nanoparticles (SCNPs) and equilibrated melts of high-molecular weight polystyrene of identical molecular weight. SCNPs were prepared by electrospraying technique and characterized using scanning electron microscopy and atomic force microscopy techniques. Differential scanning calorimetry, Brillouin light spectroscopy, and rheological experiments around the glass transition were compared. In parallel, entangled and disentangled polymer melts were also compared under cooling from molecular dynamics simulations based on a bead-spring polymer model. While experiments suggest a small decrease in the glass transition temperature of films of nanoparticles in comparison to entangled melts, simulations do not observe any significant difference, despite rather different chain conformations.

Intrinsically disordered proteins (IDPs) play an important role in an array of biological processes but present a number of fundamental challenges for computational modeling. Recently, simple polymer models have regained popularity for interpreting the experimental characterization of IDPs. Homopolymer theory provides a strong foundation for understanding generic features of phenomena ranging from single-chain conformational dynamics to the properties of entangled polymer melts, but is difficult to extend to the copolymer context. This challenge is magnified for proteins due to the variety of competing interactions and large deviations in side-chain properties. In this work, we apply a simple physics-based coarse-grained model for describing largely disordered conformational ensembles of peptides, based on the premise that sampling sterically forbidden conformations can compromise the faithful description of both static and dynamical properties. The Hamiltonian of the employed model can be easily adjusted to investigate the impact of distinct interactions and sequence specificity on the randomness of the resulting conformational ensemble. In particular, starting with a bead–spring-like model and then adding more detailed interactions one by one, we construct a hierarchical set of models and perform a detailed comparison of their properties. Our analysis clarifies the role of generic attractions, electrostatics, and side-chain sterics, while providing a foundation for developing efficient models for IDPs that retain an accurate description of the hierarchy of conformational dynamics, which is nontrivially influenced by interactions with surrounding proteins and solvent molecules.

The solvent quality determines the collapsed or the expanded state of a polymer. For example, a polymer dissolved in a poor solvent collapses, whereas in a good solvent it opens up. While this standard understanding is generally valid, there are examples when a polymer collapses even in a mixture of two good solvents. This phenomenon, commonly known as co-non-solvency, is usually associated with a wide range of synthetic (smart) polymers. Moreover, recent experiments have shown that some biopolymers, such as elastin-like polypeptides (ELPs) that exhibit lower critical solution behavior Tlin pure water, show co-non-solvency behavior in aqueous ethanol mixtures. In this study, we investigate the phase behavior of elastin-like polypeptides (ELPs) in aqueous binary mixtures using molecular dynamics simulations of all-atom and complementary explicit solvent generic models. The model is parameterized by mapping the solvation free energy obtained from the all-atom simulations onto the generic interaction parameters. For this purpose, we derive segment-based (monomer level) generic parameters for four different peptides, namely proline (P), valine (V), glycine (G), and alanine (A), where the first three constitute the basic building blocks of ELPs. Here, we compare the conformational behavior of two ELP sequences, namely -(VPGGG)- and -(VPGVG)-, in aqueous ethanol and -urea mixtures. Consistent with recent experiments, we find that ELPs show co-non-solvency in aqueous ethanol mixtures. Ethanol molecules have preferential binding with all ELP residues, with an interaction contrast of 6–8 kBT, and thus driving the coil-to-globule transition. On the contrary, ELP conformations show a weak variation in aqueous urea mixtures. Our simulations suggest that the glycine residues dictate the overall behavior of ELPs in aqueous urea, where urea molecules have a rather weak preferential binding with glycine as observed from the all atom simulations, i.e., less than kBT. This weak interaction dilutes the overall effect of other neighboring residues and thus ELPs exhibit a different conformational behavior in aqueous urea in comparison to aqueous ethanol mixtures. While the validation of the latter findings will require a more detailed experimental investigation, the results presented here may provide a new twist to the present understanding of cosolvent interactions with peptides and proteins.

Recently, disordered blends of semiconducting and insulating polymers have been used to prepare light-emitting diodes with increased luminous efficiency. Because the thermodynamic stability of the disordered phase in blends is limited, equivalent diblock copolymers (BCPs) could be an alternative. However, the choice between disordered blends and BCPs requires understanding structural differences and their effect on charge carrier transport. Using a hybrid mesoscopic model, we simulate blends and equivalent BCPs of two representative semiconducting and insulating polymers: poly(p-phenylene vinylene) (PPV) and polyacrylate. The immiscibility is varied to mimic annealing at different temperatures. We find stable or metastable disordered morphologies until we reach the mean-field (MF) spinodal. Disordered morphologies are heterogeneous because of thermal fluctuations and local segregation. Near the MF spinodal, segregation is stronger in BCPs than in the blends, even though the immiscibility, normalized by the MF spinodal, is the same. We link the spatial distribution of PPV with electric conductance. We predict that the immiscibility (temperature at which the layer is annealed) affects electrical percolation much stronger in BCPs than in blends. Differences in the local structure and percolation between blends and BCPs are enhanced at a high insulator content.

The programming of nanomaterials at molecular length-scales to control architecture and function represents a pinnacle in soft materials synthesis. Although elusive in synthetic materials, Nature has evolutionarily refined macromolecular synthesis with perfect atomic resolution across three-dimensional space that serves specific functions. We show that biomolecules, specifically proteins, provide an intrinsic macromolecular backbone for the construction of anisotropic brush polymers with monodisperse lengths via grafting-from strategy. Using human serum albumin as a model, its sequence was exploited to chemically transform a single cysteine, such that the expression of said functionality is asymmetrically placed along the backbone of the eventual brush polymer. This positional monofunctionalization strategy was connected with biotin–streptavidin interactions to demonstrate the capabilities for site-specific self-assembly to create higher ordered architectures. Supported by systematic experimental and computational studies, we envisioned that this macromolecular platform provides unique avenues and perspectives in macromolecular design for both nanoscience and biomedicine.

Polymer melts undergoing large deformation by elongation are studied by molecular dynamics simulations of bead–spring chains in melts. By applying a primitive path analysis to strongly deformed polymer melts, the role of topological constraints in highly entangled polymer melts is investigated and quantified. We show that the overall, large scale conformations of the primitive paths (PPs) of stretched chains follow affine deformation while the number and the distribution of entanglement points along the PPs do not. Right after deformation, PPs of chains retract in both directions parallel and perpendicular to the elongation. Upon further relaxation we observe a long-lived clustering of entanglement points. Together with the delayed relaxation time this leads to a metastable inhomogeneous distribution of topological constraints in the melts.

We present a new simulation-guided process to create nanoporous materials, which does not require specific chemical treatment and solely relies on mechanical deformation of pure highly entangled homopolymer films. Starting from fully equilibrated freestanding thick polymer melt films, we apply a simple “biaxial expansion” deformation. Upon expansion holes form, which are prevented from growing and coalescing beyond a characteristic size due to the entanglement structure of the melt. We investigate the local morphology, the void formation upon expansion, and their stabilization. The dependence of the average void (pore) size and void fraction (porosity) on the total strain and subsequent relaxation is investigated. Furthermore, the stabilization of the porous structure of the thin expanded films through cooling below the glass transition temperature Tgis discussed.

Conformational transitions of (bio)macromolecules in aqueous mixtures are intimately linked to local concentration fluctuations of different solvent components. Though computer simulations are ideally suited to investigate such phenomena, in conventional setups the excess of one cosolvent close to the solute leads to depletion elsewhere, requiring very large simulation domains to avoid system size effects. We, here, propose an approach to overcome this depletion effect, which combines the adaptive resolution scheme (AdResS) with a Metropolis particle exchange criterion. In AdResS, a small all-atom region, containing the solute, is coupled to a coarse-grained reservoir, where the particle exchange is performed. The particle exchange would be almost impossible had they been performed in an all-atom setup of a dense molecular liquid. As a first application of the method, we study the concentration driven reentrant collapse and swelling transition of poly(N-isopropylacrylamide) (PNIPAm) in aqueous methanol and demonstrate the role of the delicate interplay of the different intermolecular interactions.

Despite a vast body of the literature devoted to the use of phenylene polymers in the fabrication of graphene nanoribbons, the study of the physical properties of these precursors still poses open questions whose answers will certainly contribute to the design of more efficient/precise synthesis protocols. Particularly, persistence length measurements combined with size exclusion chromatography techniques assign both semiflexible to semirigid structures depending on the molecular weight of the precursor (NaritaNat. Chem.2014, 6, 126−132). Peculiarly, these results suggest an apparent structural change upon increasing the length of the polymers. To address this puzzle, we use single-chain models to study the stiffness of polyphenylene precursors in a theta-like solvent as a function of chain composition and monomer sequence. Steric effects are isolated by considering random walk chains with segment length distributions and the position of monomers determined by the nature of the arene substitution along the backbone. Moreover, two homopolymer limiting cases are defined, that is, meta and para sequences, by associating two types of monomers to each possible substitution pattern. We consider, within these two limiting cases, chains with different compositions and monomer sequences. We compute persistence lengths, mean square end-to-end distances, and gyration and hydrodynamic radii. We find that distinct values of the persistence length for apparently the same chain chemistry are the result of different mixing ratios and the arrangement along the chain of the two positional isomers of the same monomer. Finally, we discuss the relation between two-dimensional density of the number of crossings and the length of polyphenylene segments as they would occur upon strong chain adsorption onto a substrate.

A true challenge in designing multiresponsive complex macromolecular architectures is to tune their conformation at will by changing the gradients of external stimuli. However, the lack of a clear molecular-level understanding, establishing a delicate interplay between segment-based interaction details and large-scale macromolecular properties, has hindered the implementation of design principles for a long time. Combining molecular simulations, together with complementary polymer synthesis and characterization, we propose a molecular-level design principle of multiresponsive copolymer architectures. For this purpose, we use the co-nonsolvency concept that is associated with polymer collapse in miscible good solvents. We show how the responsiveness of different polymer blocks can provide fully flexible conformational tuning and, therefore, may serve as a guiding principle for smart material design.

We develop a generic coarse-grained model of soluble conjugated polymers, capable of describing their self-assembly into a lamellar mesophase. Polymer chains are described by a hindered-rotation model, where interaction centers represent entire repeat units, including side chains. We introduce soft anisotropic nonbonded interactions to mimic the potential of mean force between atomistic repeat units. The functional form of this potential reflects the symmetry of the molecular order in a lamellar mesophase. The model can generate both nematic and lamellar (sanidic smectic) molecular arrangements. We parametrize this model for a soluble conjugated polymer poly(3-hexylthiophene) (P3HT) and demonstrate that the simulated lamellar mesophase matches morphologies of low molecular weight P3HT, experimentally observed at elevated temperatures. A qualitative charge-transport model allows us to link local chain conformations and mesoscale order to charge transport. In particular, it shows how coarsening of lamellar domains and chain extension increase the charge carrier mobility. By modeling large systems and long chains, we can capture transport between lamellar layers, which is due to rare, but thermodynamically allowed, backbone bridges between neighboring layers.

Many popular methods for the calculation of chemical potentials rely on the insertion of test particles into the target system. In the case of liquids and liquid mixtures, this procedure increases in difficulty upon increasing density or concentration, and the use of sophisticated enhanced sampling techniques becomes inevitable. In this work, we propose an alternative strategy, spatially resolved thermodynamic integration, or SPARTIAN for short. Here, molecules are described with atomistic resolution in a simulation subregion and as ideal gas particles in a larger reservoir. All molecules are free to diffuse between subdomains adapting their resolution on the fly. To enforce a uniform density profile across the simulation box, a single-molecule external potential is computed, applied, and identified with the difference in chemical potential between the two resolutions. Since the reservoir is represented as an ideal gas bath, this difference exactly amounts to the excess chemical potential of the target system. The present approach surpasses the high density/concentration limitation of particle insertion methods because the ideal gas molecules entering the target system region spontaneously adapt to the local environment. The ideal gas representation contributes negligibly to the computational cost of the simulation, thus allowing one to make use of large reservoirs at minimal expenses. The method has been validated by computing excess chemical potentials for pure Lennard-Jones liquids and mixtures, SPC and SPC/E liquid water, and aqueous solutions of sodium chloride. The reported results well reproduce literature data for these systems.

In adaptive resolution simulations, different regions of a simulation box are modeled with different levels of detail. Particles change their resolution on-the-fly when traveling from one subregion to the other. This method is particularly useful for studying multiscale systems in which effects on a broad range of length and time scales play a role. Until now, the geometry of the high-resolution region has been limited to simple geometries of spherical, cuboid, or cylindrical form, whose shape does not change during the simulation. However, many phenomena involve changes in size and shape of system components, for example, protein folding, polymer collapse, nucleation, and crystallization. In this work, we develop a scheme that uses a series of overlapping spheres to allow for an arbitrary division of space into domains of different levels of resolution. Furthermore, the geometry is automatically adjusted on-the-fly during the simulation according to changes in size and shape of, for example, a solvated macromolecule within the high-resolution region. The proposed approach is validated on liquid water. We then simulate the folding of an atomistically detailed polypeptide solvated in a shell of atomistic water that changes shape as the peptide conformation changes. We demonstrate that the peptide folding process is unperturbed by the use of our methodology.

Quantum delocalization of atomic nuclei affects the physical properties of many hydrogen-rich liquids and biological systems even at room temperature. In computer simulations, quantum nuclei can be modeled via the path-integral formulation of quantum statistical mechanics, which implies a substantial increase in computational overhead. By restricting the quantum description to a small spatial region, this cost can be significantly reduced. Herein, we derive a bottom-up, rigorous, Hamiltonian-based scheme that allows molecules to change from quantum to classical and vice versa on the fly as they diffuse through the system, both reducing overhead and making quantum grand-canonical simulations possible. The method is validated via simulations of low-temperature parahydrogen. Our adaptive resolution approach paves the way to efficient quantum simulations of biomolecules, membranes, and interfaces.

The systematic exploration of chemical compound space holds many promises toward structure–function relationships and material design. In the context of computer simulations, progress is hampered by both the sheer number of compounds and the efforts associated with parametrizing a force field for every new molecule. A coarse-grained (CG) representation provides not only a reduced phase space but also a smaller number of compounds, due to the redundancy of CG representations mapping to the same structure. Though many CG models require the explicit force-field parametrization of a molecule with all others, others assume transferability by means of mixing rules, such as the Martini force field. To alleviate the burden associated with tedious parametrizations for each new compound, the present work aims at automating the mapping and parametrization of common small organic molecules for Martini. We test the method by analyzing the water/octanol partitioning of more than 650 neutral molecules, the hydration free energy of 354 others, and the free energies of hydration and solvation in octanol of another 69 compounds. Last, we compare with all-atom simulations the thermodynamics of insertion of four individual solute molecules in a phospholipid membrane. The protocol demonstrates the feasibility of an automated parametrization scheme for Martini and provides prospects for high-throughput simulation methodologies.

We examine the effects of the common Debye-Hückel approximation used in theories of polyelectrolytes. Molecular dynamics simulations using the Debye-Hückel pair potential of salt-free polyelectrolytes have been performed. The results of these simulations are compared to earlier “Coulomb" simulations which explicitly treated the counterions. We report here the comparisons of the osmotic pressure, the end-to-end distance and the single chain structure factor. In the dilute regime the Debye-Hückel chains are more elongated than the Coulomb chains implying that the counterion screening is stronger than the Debye-Hückel prediction. Like the Coulomb chains the Debye-Hückel chains contract significantly below the overlap density in contradiction to all theories. Entropy thus plays an important and sorely neglected role in theory.

Extensive Monte Carlo simulations are presented for the bond-fluctuation model on three-dimensional simple cubic lattices. High statistics data are obtained for polymer volume fractions Φ in the range 0.025 ≤Φ≤0.500 and chain lengths N in the range 20 ≤N ≤200, making use of a parallel computer containing 80 transputers. The simulation technique takes into account both excluded volume interactions and entanglement restrictions, while otherwise the chains are non-interacting and athermal. The simulation data are analysed in terms of the de Gennes scaling concepts, describing the crossover from swollen coils in the dilute limit to gaussian coils in semidilute and concentrated solution. The crossover scaling functions for the chain linear dimensions and for the decay of the structure factor are estimated and compared to corresponding theoretical and experimental results in the literature. Also the dynamics of the chains is studied in detail, and evidence for a gradual crossover from the Rouse model to a D ∼N-2law for the diffusion constant is presented. This crossover is consistent with scaling only if a concentration-dependent segmental “friction coefficient" is introduced. Within this framework general agreement between these data, other simulations and experiment is found.

We outline a method to investigate the role of nuclear quantum effects in liquid water making use of a force field derived from ab initio simulations. Starting from a first-principles molecular dynamics simulation, we obtain an effective force field for bulk liquid water using the force-matching technique. After validating that our effective model reproduces the key structural and dynamic properties of the reference system, we use it to perform path integral simulations to investigate the role played by nuclear quantum effects on bulk water, probing radial distribution functions, vibrational spectra, and hydrogen bond fluctuations. Our approach offers a practical route to derive ab initio quality molecular models to study quantum effects at a low computational cost.

We establish a link between the microscopic ordering and the charge-transport parameters for a highly crystalline polymeric organic semiconductor, poly(2,5-bis(3-tetradecylthiophen-2-yl)thieno[3,2-b]thiophene) (PBTTT). We find that the nematic and dynamic order parameters of the conjugated backbones, as well as their separation, evolve linearly with temperature, while the side-chain dynamic order parameter and backbone paracrystallinity change abruptly upon the (also experimentally observed) melting of the side chains around 400 K. The distribution of site energies follows the behavior of the backbone paracrystallinity and can be treated as static on the time scale of a single-charge transfer reaction. On the contrary, the electronic couplings between adjacent backbones are insensitive to side-chain melting and vary on a much faster time scale. The hole mobility, calculated after time-averaging of the electronic couplings, reproduces well the value measured in a short-channel thin-film transistor. The results underline that to secure efficient charge transport in lamellar arrangements of conjugated polymers: (i) the electronic couplings should present high average values and fast dynamics, and (ii) the energetic disorder (paracrystallinity) should be small.

Solvation free energies of peptides in water decrease with increasing urea concentration and therefore lead to increased solubility. In this work, we study the solvation thermodynamics of a triglycine in aqueous urea solutions at room temperature T= 300 K. We perform our analysis within the framework of the Kirkwood–Buff theory of liquid mixtures, developed for open systems. For this purpose, we use a recently proposed approach to study liquid mixtures within an “effective” open boundary simulation scheme (AdResS). We couple a small open boundary all-atom (explicit) region to a much larger coarse-grained particle reservoir. This coupling allows the free exchange of particles in thermodynamic equilibrium. Our approach preserves correct particle fluctuations that are important for studying the concentration driven conformational transition of (bio)molecules.

Using the adaptive resolution (AdResS) molecular dynamics scheme, we present a new approach to calculate the thermodynamic properties of liquid mixtures in an open boundary simulation. As a test case, we simulate methanol–water mixtures. We show that Kirkwood–Buff integrals (KBI), which directly connect global thermodynamic properties to microscopic molecular distributions, can be efficiently calculated over a wide range of methanol mole fractions by choosing only a very small (∼3% of total simulation domain) open boundary explicit (all atom) region and a surrounding coarse-grained reservoir that takes care of correct particle fluctuations.

For the example of C60 solutes in toluene, we present the implementation of the adaptive resolutions scheme (AdResS) for molecular simulations into GROMACS. In AdResS a local, typically all-atom cavity is coupled to a surrounding of coarse-grained, simplified molecules. This methodology can not only be used to reduce the CPU time demand of atomistic simulations but also to systematically investigate the relative influence of different interactions on structure formation. For this, we vary the thickness of the all atom layer of toluene around the C60 and analyze the first toluene layers in comparison to a full bulk simulation.

The equilibrium swelling behavior of a crosslinked polyelectrolyte gel under poor‐solvent conditions is examined. To this end, MD simulations of a coarse‐grained network model with a diamond‐like topology are employed where the counterions are explicitly taken into account. A large range of different parameter combinations in the fraction fof charged monomers of the network, the strength of electrostatic interactions measured via the Bjerrum length $\ell _{{\rm B}} $, and various strand lengths are studied. The results agree with data on single PE chains, in particular the theoretically predicted pearl necklace conformations can be identified as well as a sausage‐like regime in the strong‐coupling region.

A long‐lived metastable “new melt” state of polymers has been recently reported, where monomers exhibit different mobilities due to an unusual distribution of entanglements. We study the relaxation of (fully disentangled) globules to the entangled state by means of computer simulations, and compare our data to the scenario of de Gennes' explosion upon melting. The entanglement length Neis measured using the primitive path analysis method. The results show that in the case of relatively short chains (N≈ 20Ne), the relaxation of the entanglement length is very fast compared to that of the chains' size which slows down as the chain length Nexceeds the equilibrium value of Ne.

Coarse-graining is a systematic way of reducing the number of degrees of freedom representing a system of interest. Several coarse-graining techniques have so far been developed, such as iterative Boltzmann inversion, force-matching, and inverse Monte Carlo. However, there is no unified framework that implements these methods and that allows their direct comparison. We present a versatile object-oriented toolkit for coarse-graining applications (VOTCA) that implements these techniques and that provides a flexible modular platform for the further development of coarse-graining techniques. All methods are illustrated and compared by coarse-graining the SPC/E water model, liquid methanol, liquid propane, and a single molecule of hexane.

A detailed analysis of the efficiency of a Monte‐Carlo (MC) method employing non‐local moves for simple lattice ring polymers is presented. While the introduction of kink‐translocation moves for linear chains results in the expected speedup by a factor of the order of the number of sites, this is significantly reduced for a melt of rings.

We present a detailed study of a new, optimized coarse-grained (CG) model of polystyrene (PS) and compare it with a recently published one (Harmandaris et al., Macromolecules2006, 39, 6708). By implementing a different mapping scheme, the new model, augmented with softer nonbonded interactions, better reproduces the local chain conformations and melt packing observed in atomistic simulations of atactic PS. Both models properly predict the bonded distributions and are capable of simulating different tacticities without needing sidegroups. Both CG models fit dynamic data from long atomistic simulations after determining the scale factor for the simulation time. Together with a rigorous back‐mapping procedure from the mesoscopic to atomistic description, this opens up a very feasible way for generating very long atomistic trajectories.

An atomistic force field has been adapted for use in molecular dynamics simulations of molecular materials that contain azobenzene (AB) functional groups. Force field parameters for bonded interactions and partial charges in the AB unit have been derived from ab initio molecular dynamics reference calculations. First applications of the new force field to liquid trans- and cis-AB are presented, both using a purely classical approach (MM) and a hybrid quantum-classical (QM/MM) simulation scheme. Detailed structural analysis confirms that QM/MM and purely MM simulations yield results that are in good agreement with each other. The force field of the AB core has been extended to include aliphatic chains that are attached via ether bridges to the two AB benzene rings. This allows for studying temperature induced phase transitions in the liquid−crystalline 8AB8 system. Using replica exchange techniques the new force field has successfully reproduced the smectic to isotropic-phase transition.

Summary:We describe recent advances obtained in understanding the microscopic interplay of a charged hydrogel with its confined mobile counterions. Results of extensive computer simulations are compared to simple scaling descriptions for various solvent conditions. We will briefly discuss our simulation package ESPResSo which was used to perform the simulations. We demonstrate why simple scaling theories suffice to adequately describe the swelling behavior of these systems despite their enormous complexity. We will conclude with a presentation of ongoing results for polyelectrolyte networks under poor solvent conditions.

Abstract: Topological constraints, referred to as entanglements in the literature, dominate the viscoelastic behavior of high molecular weight polymeric liquids. To give a microscopic foundation of the phenomenological tube models which successfully describe this behavior, we have recently introduced a method for identifying the so-called primitive path mesh that characterizes the microscopic topological state of (computer generated) conformations of long-chain polymer networks, melts and solutions. Here we give a short account of this approach and discuss some applications. [Copyright &y& Elsevier]

Similar to entangled ropes, polymer chains cannot slide through each other. These topological constraints, the so‐called entanglements, dominate the viscoelastic behavior of high‐molecular‐weight polymeric liquids. Tube models of polymer dynamics and rheology are based on the idea that entanglements confine a chain to small fluctuations around a primitive path which follows the coarse‐grained chain contour. To establish the microscopic foundation for these highly successful phenomenological models, we have recently introduced a method for identifying the primitive path mesh that characterizes the microscopic topological state of computer‐generated conformations of long‐chain polymer melts and solutions. Here we give a more detailed account of the algorithm and discuss several key aspects of the analysis that are pertinent for its successful use in analyzing the topology of the polymer configurations. We also present a slight modification of the algorithm that preserves the previously neglected self‐entanglements and allows us to distinguish between local self‐knots and entanglements between distant sections of the same chain. Our results indicate that the latter make a negligible contribution to the tube and that the contour length between local self‐knots, Nlk is significantly larger than the entanglement length Ne. © 2005 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 43: 917–933, 2005

Summary: Using extensive Molecular Dynamics simulations we study the behavior of very rigid polyelectrolytes with hydrophobic side chains that are known to form cylindrical micelles in aqueous solution. We investigate the stability of such micelles with respect to hydrophobicity, Coulomb interaction, and micellar size. We show that for the parameter range relevant for poly(p-phenylene sulfonate)s (PPP) one finds a stable finite micellar size close to the experimental parameter region. We also point out that our model has some similarities to DNA solutions with added condensing agents, hinting to the possibility that the size of DNA aggregates is under certain circumstances thermodynamically limited.DNA-like morphologies of the polyelectrolytes.

In this article we review the complexation behavior of charged polymers adsorbed onto charged substrates. In the first part we summarize the results obtained on the adsorption properties of a single polyelectrolyte chain with one or several oppositely charged spherical colloids. The results of various simulational studies are compared with theoretical predictions. After that, we show that under strong electrostatic coupling conditions one can also obtain complexations, where chain and colloid carry the same charge (like‐charge complexation). This effect is due to counterion correlation effects. Finally, we investigate the case of polyelectrolyte multilayers structures, which are composed of alternating polycations and polyanions on various substrate geometries. This structure, normally obtained by a so‐called layer‐by‐lay deposition, is very stable experimentally, but only poorly understood in terms of theoretical approaches. Our simulation results suggest that short range attractive interactions (e.g., van der Waals) are important for obtaining a stable sequence of multilayers. © 2004 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 42: 3557–3570, 2004

Using extensive Molecular Dynamics (MD) simulations we study the behavior of polyelectrolytes in poor solvents, where we take explicitely care of the counterions. The resulting pearl‐necklace structures are subject to strong conformational fluctuations, only leading to small signatures in the form factor, which is a severe obstacle for experimental observations. In addition we study how the necklace collapses as a function of Bjerrum length. At last we demonstrate that the position of the first peak in the inter‐chain structure factor varies with the monomer density close to $ρ^{1/3}_{m}$for all densities. This is in strong contrast to polyelectrolyte solutions in good solvent.

In the context of a few characteristic examples, the perspectives of computational materials science for polymeric systems are being discussed. The examples chosen cover the range from atomistic/quantum models to coarse grained bead spring polymer models. Cartoon of the average chain conformations near the surface. Since the chains are relatively short and only the chain ends adsorb, there is no entanglement network, which would otherwise enhance the bulk adhesion to the surface. Black lines represent chains with both chain ends stuck to the surface, red lines represent chains with only one chain end stuck to the surface and the other in the bulk, and light blue lines represent chains in the bulk.29

The paper gives a short overview on recent approaches to link several time and length scales in soft matter simulations. Special attention is given to the fact that in contrast to low molecular weight compounds, intramolecular entropy is as important as the energetic contribution. First applications to industrially relevant problems are mentioned.

In a previous work^[1] we presented a coarse-graining procedure for bonded interactions, while spherical, purely repulsive 6–12 interactions were used to account for the excluded-volume of the beads of the phantom chains. Here we extend this approach towards ellipsoidal beads whose shapes are extracted from the geometry of the underlying atomistic chains. The influence of the bead shapes on the static and dynamical properties of melts are studied in detail for two modifications of polycarbonates, from 2mers up to 20mers. The results obtained in both cases are discussed in the context of corresponding experiments and atomistic simulations.

Many fundamental questions for the understanding of polymer melts and networks are more suitably addressed by current computer simulations than by experiments. The reason is that simulations have simultaneous access to the microscopic structure and the macroscopic behavior of well-defined model systems. The coarse-grained models used often bear little relation to actual chemical species. This is justified by the experimentally established universality of polymer dynamics and no limitation for the test and development of theories which are directed at these universal aspects. The difficulties already encountered on this level will be illustrated for entanglements between polymers which dominate the dynamic in dense systems.

A Monte Carlo study of SAW's on a diluted diamond lattice is presented. We find that the exponentv does not change by dilution,v˜0.59 as in the undiluted case, in contrast to the original conclusion of Chakrabarti and Kertész. This result cannot be understood by the Harris criterion. At the percolation concentrationpc of the lattice we find a higher exponentvpc˜2/3. A scaling form of the crossover between these exponents nearpc is proposed and found to be consistent with the Monte Carlo results.

The elastic and relaxational properties of polymer networks are strongly influenced by quenched disorder, introduced by the crosslinks in the systems. By extensive computer simulations of appropriately tailored model systems these effects are systematically investigated.