Probing the Linear-to-Plastic Transition in Polymer Nanocomposites via Atomistic Simulations: The Role of Interphases.

Polymer nanocomposites have found ubiquitous use across diverse industries, attributable to their distinctive properties and enhanced mechanical performance compared to conventional materials. Elucidating the elastic-to-plastic transition in polymer nanocomposites under diverse mechanical loads is paramount for the bespoke design of materials with desired mechanical attributes. In the current work, the elastic-to-plastic transition is probed in model systems of polyethylene oxide (PEO) and silica, SiO2, nanoparticles, through detailed atomistic molecular dynamics simulations. This comprehensive, multi-scale analysis unveils pivotal markers of the elastic-to-plastic transition, highlighting the quintessential role of microstructural and regional heterogeneities in density, strain, and stress fields, featuring the polymer-nanoparticle interphase region. At the atomic level, the behavior of polymer chains interacting with nanoparticle surfaces is traced, differentiating between free and adsorbed chains, and identifying the microscopic origins of the linear-to-plastic transition. The mechanical behavior of subregions are characterized within the PEO/SiO2 nanocomposites, focusing on the interphase and bulk-like polymer areas, probing stress heterogeneities and their decomposition into various force contributions. At the inception of plasticity, a disruption is discerned in isotropy of the polymeric density field, the emergence of low-density regions, and microscopic voids/cavities within the polymer matrix concomitant with a transition of adsorbed chains to free. The yield strain also emerges as an inflection point in the local versus global strain diagram, demarcating the elastic limit, and the plastic regime shows pronounced strain heterogeneities. The decomposition of the atomic Virial stress into bonded and non-bonded interactions indicates that the rigidity of the material is primarily governed by non-bonded interactions, significantly influenced by the volume fraction of the nanoparticle. These findings emphasize the importance of the microstructural and micromechanical environment at the polymer-nanoparticle interface on the linear-to-plastic transition, which is of great importance in the design of nanocomposite materials with advanced mechanical properties.

Unraveling the Effect of Strain Rate and Temperature on the Heterogeneous Mechanical Behavior of Polymer Nanocomposites via Atomistic Simulations and Continuum Models.

Polymer nanocomposites are characterized by heterogeneous mechanical behavior and performance, which is mainly controlled by the interaction between the nanofiller and the polymer matrix. Optimizing their material performance in engineering applications requires understanding how both the temperature and strain rate of the applied deformation affect mechanical properties. This work investigates the effect of strain rate and temperature on the mechanical properties of poly(ethylene oxide)/silica (PEO/SiO2) nanocomposites, revealing their behavior in both the melt and glassy states, via atomistic molecular dynamics simulations and continuum models. In the glassy state, the results indicate that Young's modulus increases by up to 99.7% as the strain rate rises from 1.0 × 10-7 fs-1 to 1.0 × 10-4 fs-1, while Poisson's ratio decreases by up to 39.8% over the same range. These effects become even more pronounced in the melt state. Conversely, higher temperatures lead to an opposing trend. A local, per-atom analysis of stress and strain fields reveals broader variability in the local strain of the PEO/SiO2 nanocomposites as temperature increases and/or the deformation rate decreases. Both interphase and matrix regions lose rigidity at higher temperatures and lower strain rates, blurring their distinctiveness. The results of the atomistic simulations concerning the elastic modulus and Poisson's ratio are in good agreement with the predictions of the Richeton-Ji model. Additionally, these findings can be leveraged to design advanced polymer composites with tailored mechanical properties and could optimize structural components by enhancing their performance under diverse engineering conditions.

Distribution of Mechanical Properties in Poly(ethylene oxide)/silica Nanocomposites via Atomistic Simulations: From the Glassy to the Liquid State.

Polymer nanocomposites exhibit a heterogeneous mechanical behavior that is strongly dependent on the interaction between the polymer matrix and the nanofiller. Here, we provide a detailed investigation of the mechanical response of model polymer nanocomposites under deformation, across a range of temperatures, from the glassy regime to the liquid one, via atomistic molecular dynamics simulations. We study the poly(ethylene oxide) matrix with silica nanoparticles (PEO/SiO2) as a model polymer nanocomposite system with attractive polymer/nanofiller interactions. Probing the properties of polymer chains at the molecular level reveals that the effective mass density of the matrix and interphase regions changes during deformation. This decrease in density is much more pronounced in the glassy state. We focus on factors that govern the mechanical response of PEO/SiO2 systems by investigating the distribution of the (local) mechanical properties, focusing on the polymer/nanofiller interphase and matrix regions. As expected when heating the system, a decrease in Young's modulus is observed, accompanied by an increase in Poisson's ratio. The observed differences regarding the rigidity between the interphase and the matrix region decrease as the temperature rises; at temperatures well above the glass-transition temperature, the rigidity of the interphase approaches the matrix one. To describe the nonlinear viscoelastic behavior of polymer chains, the elastic modulus of the PEO/SiO2 systems is further calculated as a function of the strain for the entire nanocomposite, as well as the interphase and matrix regions. The elastic modulus drops dramatically with increasing strain for both the matrix and the interphase, especially in the small-deformation regime. We also shed light on characteristic structural and dynamic attributes during deformation. Specifically, we examine the rearrangement behavior as well as the segmental and center-of-mass dynamics of polymer chains during deformation by probing the mobility of polymer chains in both axial and radial motions under deformation. The behavior of the polymer motion in the axial direction is dominated by the deformation, particularly at the interphase, whereas a more pronounced effect of the temperature is observed in the radial directions for both the interphase and matrix regions.

Temperature dependence of the dynamics and interfacial width in nanoconfined polymers via atomistic simulations.

We present a detailed computational study on the temperature effect of the dynamics and the interfacial width of unentangled cis-1,4 polybutadiene linear chains confined between strongly attractive alumina layers via long, several µs, atomistic molecular dynamics simulations for a wide range of temperatures (143-473 K). We examine the spatial gradient of the translational segmental dynamics and of an effective local glass temperature (TgL). The latter is found to be much higher than the bulk Tg for the adsorbed layer. It gradually reduces to the bulk Tg at about 2 nm away from the substrate. For distant regions (more than ≈1.2nm), a bulk-like behavior is observed; relaxation times follow a typical Vogel-Fulcher-Tammann dependence for temperatures higher than Tg and an Arrhenius dependence for temperatures below the bulk Tg. On the contrary, the polymer chains at the vicinity of the substrate follow piecewise Arrhenius processes. For temperatures below about the adsorbed layer's TgL, the translational dynamics follows a bulk-like (same activation energy) Arrhenius process. At higher temperatures, there is a low activation energy Arrhenius process, caused by high interfacial friction forces. Finally, we compute the interfacial width, based on both structural and dynamical definitions, as a function of temperature. The absolute value of the interfacial width depends on the actual definition, but, regardless, the qualitative behavior is consistent. The interfacial width peaks around the bulk Tg and contracts for lower and higher temperatures. At bulk Tg, the estimated length of the interfacial width, computed via the various definitions, ranges between 1.0 and 2.7 nm.

Physics-Informed Deep Learning Approach for Reintroducing Atomic Detail in Coarse-Grained Configurations of Multiple Poly(lactic acid) Stereoisomers.

Multiscale modeling of complex molecular systems, such as macromolecules, encompasses methods that combine information from fine and coarse representations of molecules to capture material properties over a wide range of spatiotemporal scales. Being able to exchange information between different levels of resolution is essential for the effective transfer of this information. The inverse problem of reintroducing atomistic degrees of freedom in coarse-grained (CG) molecular configurations is particularly challenging as, from a mathematical point of view, it is an ill-posed problem; the forward mapping from the atomistic to the CG description is typically defined via a deterministic operator ("one-to-one" problem), whereas the reversed mapping from the CG to the atomistic model refers to creating one representative configuration out of many possible ones ("one-to-many" problem). Most of the backmapping methods proposed so far balance accuracy, efficiency, and general applicability. This is particularly important for macromolecular systems with different types of isomers, i.e., molecules that have the same molecular formula and sequence of bonded atoms (constitution) but differ in the three-dimensional configurations of their atoms in space. Here, we introduce a versatile deep learning approach for backmapping multicomponent CG macromolecules with chiral centers, trained to learn structural correlations between polymer configurations at the atomistic level and their corresponding CG descriptions. This method is intended to be simple and flexible while presenting a generic solution for resolution transformation. In addition, the method is aimed to respect the structural features of the molecule, such as local packing, capturing therefore the physical properties of the material. As an illustrative example, we apply the model on linear poly(lactic acid) (PLA) in melt, which is one of the most popular biodegradable polymers. The framework is tested on a number of model systems starting from homopolymer stereoisomers of PLA to copolymers with randomly placed chiral centers. The results demonstrate the efficiency and efficacy of the new approach.

Revealing the Role of Chain Conformations on the Origin of the Mechanical Reinforcement in Glassy Polymer Nanocomposites.

Understanding the mechanism of mechanical reinforcement in glassy polymer nanocomposites is of paramount importance for their tailored design. Here, we present a detailed investigation, via atomistic simulation, of the coupling between density, structure, and conformations of polymer chains with respect to their role in mechanical reinforcement. Probing the properties at the molecular level reveals that the effective mass density as well as the rigidity of the matrix region changes with filler volume fraction, while that of the interphase remains constant. The origin of the mechanical reinforcement is attributed to the heterogeneous chain conformations in the vicinity of the nanoparticles, involving a 2-fold mechanism. In the low-loading regime, the reinforcement comes mainly from a thin, single-molecule, 2D-like layer of adsorbed polymer segments on the nanoparticle, whereas in the high-loading regime, the reinforcement is dominated by the coupling between train and bridge conformations; the latter involves segments connecting neighboring nanoparticles.

Investigating the complexation propensity of self-assembling dipeptides with the anticancer peptide-drug Bortezomib: a computational study.

The investigation of potential self-assembled peptides as carriers for the delivery of anticancer drug Bortezomib is the topic of the present study. The self-assembly of Bortezomib in water is examined using all-atom molecular dynamics simulations and corresponding experimental results from FESEM experiments. In addition, a series of dipeptides with a similar chemical formula to Bortezomib with hydrogel-forming ability are being investigated for their propensity to bind to the drug molecule. Dipeptides are divided into two classes, the protected FF (Fmoc-FF and Z-FF) and the LF-based (Cyclo-LF and LF) ones. The thermodynamic stability of the complexes formed in an aqueous environment, as well as key morphological features of the nanoassemblies are investigated at the molecular level. Binding enthalpy between Bortezomib and dipeptides follows the increasing order: LF < Cyclo-LF < Fmoc-FF < Z-FF under both van der Waals and electrostatic contributions. Protected FF dipeptides have a higher affinity for the drug molecule, which will favor its entrapment, giving them an edge over the LF based dipeptides. By evaluating the various measures, regarding both the binding between the two components and the eventual ability of controlled drug release, we conclude that the protected FF class is a more suitable candidate for drug release of Bortezomib, whereas among its two members, Fmoc-FF appears to be more promising. The selection of the optimal candidates based on the present computational study will be a stepping stone for future detailed experimental studies involving the encapsulation and controlled release of Bortezomib both in vitro and in vivo.

Structure of amino acid sequence-reversed wtRop protein: insights from atomistic molecular dynamics simulations.

This study aims to the investigation of the advantages of designing new proteins presume upon a 'bias' sequence of amino acids, based on the reversed sequence of parent proteins, such as the retro ones. The structural simplicity of wtRop offers a very attractive model system to study these aspects. The current work is based on all-atom Molecular Dynamics (MD) simulations and corresponding experimental evidence on two different types of reversed wtRop protein, one with a fully reversed sequence of amino acids (rRop) and another with a partially reversed sequence (prRop), where only the five residues of the loop region (30ASP-34GLN) were not reversed. The exploration of the structure of the two retro proteins is performed highlighting the similarities and the differences with their parent protein, by employing various measures. Two models have been studied for both reversed proteins, a dimeric and a monomeric with the former one found to be more stable than the latter. Preferable equilibrium structures that the protein molecule can attain are explored, indicating the equilibration pathway. Simulation findings indicate a disruption of the α-helical structure and the appearance of additional secondary structures for both retro proteins. Reduced structural stability compared to their parent protein (wtRop) is also found. A corruption of the hydrophobic core is observed in the dimeric models. Furthermore, the simulations findings are consistent with the experimental characterization of prRop by circular dichroism spectroscopy (CD) which highlights an unstable, highly α-helical protein.Communicated by Ramaswamy H. Sarma.

The effect of chemical constitution on polyisoprene dynamics.

Polyisoprene (PI) melts have been studied, with most reports focusing on systems with high 1,4-cis content. In contrast, 1,4-trans PI homopolymers or random copolymers have seldom been examined, despite a handful of investigations suggesting a distinct dynamic behavior. Herein, we employ all-atom simulations to investigate the effect of chemical architecture on the dynamics of cis and trans-PI homopolymers, as well as copolymers. We examine the thermodynamic, conformational, and structural properties of the polymers and validate the performance of the models. We probe chain dynamics, revealing that cis-PI presents accelerated translation and reorientation modes relative to trans as recorded by the mean square displacement of the chain center-of-mass as well as by the characteristic times of the lower modes in a Rouse analysis. Interestingly, progressing to higher modes, we observe a reversal with trans units exhibiting faster dynamics. This was further confirmed by calculations of local carbon-hydrogen vector reorientation dynamics, which offer a microscopic view of segmental mobility. To obtain insight into the simulation trajectories, we evaluate the intermediate incoherent scattering function that supports a temperature-dependent crossover in relative mobility that extends over separations beyond the Kuhn-length level. Finally, we analyzed the role of non-Gaussian displacements, which demonstrate that cis-PI exhibits increased heterogeneity in dynamics over short-timescales in contrast to trans-PI, where deviations persist over times extending to terminal dynamics. Our all-atom simulations provide a fundamental understanding of PI dynamics and the impact of microstructure while providing important data for the design and optimization of PI-based materials.

Adsorption of air pollutants onto silver and gold atomic clusters: DFT and PNO-LCCSD-F12 calculations.

We provide a comprehensive investigation of intermolecular interactions between atmospheric gaseous pollutants, including CH4, CO, CO2, NO, NO2, SO2, as well as H2O and Agn (n = 1-22) or Aun (n = 1-20) atomic clusters. The optimized geometries of all the systems investigated in our study were determined using density functional theory (DFT) with M06-2X functional and SDD basis set. The PNO-LCCSD-F12/SDD method was used for more accurate single-point energy calculations. Compared to their isolated states, the structures of the Agn and Aun clusters undergo severe deformations upon adsorption of the gaseous species, which become more significant as the size of the clusters decreases. Considering that, in addition to adsorption energy, we have determined the interaction and deformation energy of all the systems. All our calculations consistently show that among the gaseous species examined, SO2 and NO2 exhibit a higher preference for adsorption on both types of clusters, with a slightly higher preference for the Ag clusters compared to the Au clusters, with the SO2/Ag16 system exhibiting the lowest adsorption energy. The type of intermolecular interactions was investigated through wave function analyses, including natural bond orbital (NBO) and quantum theory of atoms in molecules (QTAIM), showing that NO2 and SO2 are chemisorbed on the Agn and Aun atomic clusters, whereas the other gas molecules exhibit a much weaker interaction with them. The reported data can be used as input parameters for molecular dynamics simulations to study the selectivity of atomic clusters towards specific gases under ambient conditions, as well as to design materials that take advantage of the studied intermolecular interactions.

Self-Assembly of Phenylalanine-Leucine, Leucine-Phenylalanine, and Cyclo(-leucine-phenylalanine) Dipeptides through Simulations and Experiments.

For over two decades, peptide self-assembly has been the focus of attention and a great source of inspiration for biomedical and nanotechnological applications. The resulting peptide nanostructures and their properties are closely related to the information encoded within each peptide building block, their sequence, and their modes of self-organization. In this work. we assess the behavior and differences between the self-association of the aromatic-aliphatic Phe-Leu dipeptide compared to its retro-sequence Leu-Phe and cyclic Cyclo(-Leu-Phe) counterparts, using a combination of simulation and experimental methods. Detailed all-atom molecular dynamics (MD) simulations offer a quantitative prediction at the molecular level of the conformational, dynamical and structural properties of the peptides' self-assembly, while field emission scanning electron microscopy (FESEM) experiments allow microscopic observation of the self-assembled end-structures. The complementarity and qualitative agreement between the two methods not only highlights the differences between the self-assembly propensity of cyclic and linear retro-sequence peptides but also sheds light on underlying mechanisms of self-organization. The self-assembling propensity was found to follow the order: Cyclo(-Leu-Phe) > Leu-Phe > Phe-Leu.

Soft Character of Star-Like Polymer Melts: From Linear-Like Chains to Impenetrable Nanoparticles.

The importance of microscopic details in the description of the behavior of polymeric nanostructured systems, such as hairy nanoparticles, has been lately discussed via experimental and theoretical approaches. Here we focus on star polymers, which represent well-defined soft nano-objects. By means of atomistic molecular dynamics simulations, we provide a quantitative study about the effect of chemistry on the penetrability of star polymers in a melt, which cannot be considered by generic coarse-grained models. The "effective softness" estimated for two dissimilar polymers is confronted with available literature data. A consistent picture about the star penetrability can be drawn when the star internal packing is taken into consideration besides the number and the length of the star arms. These findings, together with the recently introduced two-layer model, represent a step forward in providing a fundamental understanding of the soft character of stars and guiding their design toward advanced applications, such as in all-polymer nanocomposites.

Synthesis and Modeling of Poly(L-lactic acid) via Polycondensation of L-Lactic Acid.

We present synthetic experiments of lactic acid (LA) polycondensation to produce poly(lactic acid) (PLA) as well as kinetic modeling calculations that capture the polymer molecular weight increase with time, given the initial concentrations. Tin-octoate-catalyzed polycondensation of (D,L)- or L-lactic acid was carried out in pre-dried toluene after azeotropic dehydration for 48-120 h at 130-137 °C. The polymerization was optimized by varying lactic acid and catalyst concentrations as well as the temperature. Gel permeation chromatography was used to experimentally follow the evolution of molecular weights and the products were characterized by NMR, TGA, DSC and IR. Under optimal conditions, PLLA with weight-average molecular weight (Mw) of 161 kDa could be obtained. The rate equations that describe polycondensation kinetics were recast in a condensed form that allowed very fast numerical solution and calculation of the number-average molecular weight with time. Deviations with respect to the experiment were minimized in a least-squares fashion to determine rate constants. The optimized kinetics parameters are shown to reproduce the experimental data accurately.

A methodology for determining the local mechanical properties of model atomistic glassy polymeric nanostructured materials.

We propose a methodology for calculating the distribution of the mechanical properties in model atomistic polymer-based nanostructured systems. The use of atomistic simulations is key in unravelling the fundamental mechanical behavior of composite materials. Most simulations involving the mechanical properties of polymer nanocomposites (PNCs) concern their global (average) properties, which are typically extracted by applying macroscopic strain on the boundaries of the simulation box and calculating the total (global) stress by invoking the Virial formalism over all atoms within the simulation box; thus, extracting the pertinent mechanical properties from the corresponding stress-strain relation. However, in order to probe the distribution of mechanical properties within heterogeneous multi-component polymer-based systems, a detailed computation of stress and strain fields within specific sub-domains is necessary. For example, it is well known for multi-component nanostructured systems, such as PNCs, that the mechanical behavior of the polymer/nanofiller interphases, or interfaces, is crucial for determining the global mechanical properties of the composite materials. Here we propose a new methodology to probe the distribution of mechanical properties by directly computing the (local) stress and strain at the atomic level, and averaging over user-defined subdomains. The workflow of our computational method possesses the following features:•Calculating the stress and strain per atom (or per particle) for nanostructured microscopic (here atomistic) model configurations, under an imposed applied deformation.•Averaging the local, per-atom defined, stress and strain on user-defined subdomains within the nanostructured model system.•Predicting the mechanical properties within the specific subdomains, focusing on polymer/solid interphases.

Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models.

Despite the modern advances in the available computational resources, the length and time scales of the physical systems that can be studied in full atomic detail, via molecular simulations, are still limited. To overcome such limitations, coarse-grained (CG) models have been developed to reduce the dimensionality of the physical system under study. However, to study such systems at the atomic level, it is necessary to re-introduce the atomistic details into the CG description. Such an ill-posed mathematical problem is typically treated via numerical algorithms, which need to balance accuracy, efficiency, and general applicability. Here, we introduce an efficient and versatile method for backmapping multi-component CG macromolecules of arbitrary microstructures. By utilizing deep learning algorithms, we train a convolutional neural network to learn structural correlations between polymer configurations at the atomistic and their corresponding CG descriptions, obtained from atomistic simulations. The trained model is then utilized to get predictions of atomistic structures from input CG configurations. As an illustrative example, we apply the convolutional neural network to polybutadiene copolymers of various microstructures, in which each monomer microstructure (i.e., cis-1,4, trans-1,4, and vinyl-1,2) is represented as a different CG particle type. The proposed methodology is transferable over molecular weight and various microstructures. Moreover, starting from a specific single CG configuration with a given microstructure, we show that by modifying its chemistry (i.e., CG particle types), we are able to obtain a set of well equilibrated polymer configurations of different microstructures (chemistry) than the one of the original CG configuration.

Dynamics of Polymer Chains in Poly(ethylene oxide)/Silica Nanocomposites via a Combined Computational and Experimental Approach.

The dynamics of polymer chains in poly(ethylene oxide)/silica (PEO/SiO2) nanoparticle nanohybrids have been investigated via a combined computational and experimental approach involving atomistic molecular dynamics simulations and dielectric relaxation spectroscopy (DRS) measurements. The complementarity of the approaches allows us to study systems with different polymer molecular weights, nanoparticle radii, and compositions across a broad range of temperatures. We study the effects of spatial confinement, which is induced by the nanoparticles, and chain adsorption on the polymer's structure and dynamics. The investigation of the static properties of the nanocomposites via detailed atomistic simulations revealed a heterogeneous polymer density layer at the vicinity of the PEO/SiO2 interface that exhibited an intense maximum close to the inorganic surface, whereas the bulk density was reached for distances ∼1-1.2 nm away from the nanoparticle. For small volume fractions of nanoparticles, the polymer dynamics, probed by the atomistic simulations of low-molecular-weight chains at high temperatures, are consistent with the presence of a thin adsorbed layer that exhibits slow dynamics, with the dynamics far away from the nanoparticle being similar to those in the bulk. However, for high volume fractions of nanoparticles (strong confinement), the dynamics of all polymer chains were predicted slower than that in the bulk. On the other hand, similar dynamics were found experimentally for both the local ß-process and the segmental dynamics for high-molecular-weight systems measured at temperatures below the melting temperature of the polymer, which were probed by DRS. These differences can be attributed to various parameters, including systems of different molecular weights and nanoparticle states of dispersion, the different temperature range studied by the different methods, the potential presence of a reduced-mobility PEO/SiO2 interfacial layer that does not contribute to the dielectric spectrum, and the presence of amorphous-crystalline interfaces in the experimental samples that may lead to a different dynamical behaviors of the PEO chains.

Mechanical Behavior of Polymer Nanocomposites via Atomistic Simulations: Conformational Heterogeneity and the Role of Strain Rate.

Polymer nanohybrids with a high fraction of nanofillers have been found to exhibit improved mechanical properties compared to the neat polymer homogeneous systems. Since polymer-based materials are characterized by a broad range of relaxation times, it is expected that their response under external load would depend on the actual rate of the applied deformation. In this work, we investigate the heterogeneous mechanical behavior in glassy poly(ethylene oxide)/silica nanoparticles (PEO/SiO2) nanocomposites via detailed atomistic molecular dynamics simulations. Our goal is to unravel the effect of strain rate on the mechanism of polymer nanocomposite reinforcement, within the glassy state, by directly probing the mechanical properties at the molecular level. By applying tensile deformations with various strain rates we clearly demonstrate that the value of the applied strain rate strongly affects the mechanical properties of the PEO/SiO2 model systems, inducing a transition from a rubber-like behavior, at low strain rate, to a more brittle one, at high strain rates. Then, we further investigate the mechanical heterogeneity in glassy PEO/SiO2 systems by probing directly the stress and strain fields for various conformations of adsorbed (trains, tails, loops, and bridges), and free polymer chains. Our data emphasize the importance of both train and bridge conformations on the mechanical reinforcement of the polymer nanocomposites. Last, we also probe the mobility of various chain conformations, under different applied strain rates, and their contribution to the overall mechanical behavior of the nanocomposite, during the deformation process.

Coupling between Polymer Conformations and Dynamics Near Amorphous Silica Surfaces: A Direct Insight from Atomistic Simulations.

The dynamics of polymer chains in the polymer/solid interphase region have been a point of debate in recent years. Its understanding is the first step towards the description and the prediction of the properties of a wide family of commercially used polymeric-based nanostructured materials. Here, we present a detailed investigation of the conformational and dynamical features of unentangled and mildly entangled cis-1,4-polybutadiene melts in the vicinity of amorphous silica surface via atomistic simulations. Accounting for the roughness of the surface, we analyze the properties of the polymer chains as a function of their distance from the silica slab, their conformations and the chain molecular weight. Unlike the case of perfectly flat and homogeneous surfaces, the monomeric translational motion parallel to the surface was affected by the presence of the silica slab up to distances comparable with the extension of the density fluctuations. In addition, the intramolecular dynamical heterogeneities in adsorbed chains were revealed by linking the conformations and the structure of the adsorbed chains with their dynamical properties. Strong dynamical heterogeneities within the adsorbed layer are found, with the chains possessing longer sequences of adsorbed segments ("trains") exhibiting slower dynamics than the adsorbed chains with short ones. Our results suggest that, apart from the density-dynamics correlation, the configurational entropy plays an important role in the dynamical response of the polymers confined between the silica slabs.

Structure and Thermal Stability of wtRop and RM6 Proteins through All-Atom Molecular Dynamics Simulations and Experiments.

In the current work we study, via molecular simulations and experiments, the folding and stability of proteins from the tertiary motif of 4-α-helical bundles, a recurrent motif consisting of four amphipathic α-helices packed in a parallel or antiparallel fashion. The focus is on the role of the loop region in the structure and the properties of the wild-type Rop (wtRop) and RM6 proteins, exploring the key factors which can affect them, through all-atom molecular dynamics (MD) simulations and supporting by experimental findings. A detailed investigation of structural and conformational properties of wtRop and its RM6 loopless mutation is presented, which display different physical characteristics even in their native states. Then, the thermal stability of both proteins is explored showing RM6 as more thermostable than wtRop through all studied measures. Deviations from native structures are detected mostly in tails and loop regions and most flexible residues are indicated. Decrease of hydrogen bonds with the increase of temperature is observed, as well as reduction of hydrophobic contacts in both proteins. Experimental data from circular dichroism spectroscopy (CD), are also presented, highlighting the effect of temperature on the structural integrity of wtRop and RM6. The central goal of this study is to explore on the atomic level how a protein mutation can cause major changes in its physical properties, like its structural stability.