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A method for characterizing the topological fluctuations in liquids is proposed. This approach exploits the concept of the weighted gyration tensor of a collection of particles and permits the definition of a local configurational unit (LCU). The first principal axis of the gyration tensor serves as the director of the LCU, which can be tracked and analyzed by molecular dynamics simulations. Analysis of moderately supercooled Kob-Andersen mixtures suggests that orientational relaxation of the LCU closely follows viscoelastic relaxation and exhibits a two-stage behavior. The slow relaxing component of the LCU corresponds to the structural, Maxwellian mechanical relaxation. Additionally, it is found that the mean curvature of the LCUs is approximately zero at the Maxwell relaxation time with the Gaussian curvature being negative. This observation implies that structural relaxation occurs when the configurationally stable and destabilized regions interpenetrate each other in a bicontinuous manner. Finally, the mean and Gaussian curvatures of the LCUs can serve as reduced variables for the shear stress correlation, providing a compelling proof of the close connection between viscoelastic relaxation and topological fluctuations in glass-forming liquids.
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We present results from explicit-solvent coarse-grained molecular dynamics (MD) simulations of fully charged, salt-free, and unentangled polyelectrolytes in semidilute solutions. The inclusion of a polar solvent in the model allows for a more physical representation of these solutions at concentrations, where the assumptions of a continuum dielectric medium and screened hydrodynamics break down. The collective dynamic structure factor of polyelectrolytes, S(q, t), showed that at [Formula: see text], where [Formula: see text] is the polyelectrolyte peak in the structure factor S(q) and [Formula: see text] is the correlation length, the relaxation time obtained from fits to stretched exponential was [Formula: see text], which describes unscreened Zimm-like dynamics. This is in contrast to implicit-solvent simulations using a Langevin thermostat where [Formula: see text]. At [Formula: see text], a crossover region was observed that eventually transitions to another inflection point [Formula: see text] at length scales larger than [Formula: see text] for both implicit- and explicit-solvent simulations. The simulation results were also compared to scaling predictions for correlation length, [Formula: see text], specific viscosity, [Formula: see text], and diffusion coefficient, [Formula: see text], where [Formula: see text] is the polyelectrolyte concentration. The scaling prediction for [Formula: see text] holds; however, deviations from the predictions for [Formula: see text] and D were observed for systems at higher [Formula: see text], which are in qualitative agreements with recent experimental results. This study highlights the importance of explicit-solvent effects in molecular dynamics simulations, particularly in semidilute solutions, for a better understanding of polyelectrolyte solution behavior.
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The collective density-density and hydrostatic pressure-pressure correlations of glass-forming liquids are spatiotemporally mapped out using molecular dynamics simulations. It is shown that the sharp rise of structural relaxation time below the Arrhenius temperature coincides with the emergence of slow, nonhydrodynamic collective dynamics on mesoscopic scales. The observed long-range, nonhydrodynamic mode is independent of wave numbers and closely coupled to the local structural dynamics. Below the Arrhenius temperature, it dominates the slow collective dynamics on length scales immediately beyond the first structural peak in contrast to the well-known behavior at high temperatures. These results highlight a key connection between the qualitative change in mesoscopic two-point collective dynamics and the dynamic crossover phenomenon.
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Supported amines are a promising class of CO2 sorbents offering large uptake capacities and fast uptake rates. Among supported amines, poly(ethyleneimine) (PEI) physically impregnated in the mesopores of SBA-15 silica is widely used. Within these composite materials, the chain dynamics and morphologies of PEI strongly influence the CO2 capture performance, yet little is known about chain and macromolecule mobility in confined pores. Here, we probe the impact of the support-PEI interactions on the dynamics and structures of PEI at the support interface and the corresponding impact on CO2 uptake performance, which yields critical structure-property relationships. The pore walls of the support are grafted with organosilanes with different chemical end groups to differentiate interaction modes (spanning from strong attraction to repulsion) between the pore surface and PEI. Combinations of techniques, such as quasi-elastic neutron scattering (QENS), 1H T1-T2 relaxation correlation solid-state NMR, and molecular dynamics (MD) simulations, are used to comprehensively assess the physical properties of confined PEI. We hypothesized that PEI would have faster dynamics when subjected to less attractive or repulsive interactions. However, we discover that complex interfacial interactions resulted in complex structure-property relationships. Indeed, both the chain conformation of the surface-grafted chains and of the PEI around the surface influenced the chain mobility and CO2 uptake performance. By coupling knowledge of the dynamics and distributions of PEI with CO2 sorption performance and other characteristics, we determine that the macroscopic structures of the hybrid materials dictate the first rapid CO2 uptake, and the rate of CO2 sorption during the subsequent gradual uptake stage is determined by PEI chain motions that promote diffusive jumps of CO2 through PEI-packed domains.
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Aziridinas , Polímeros , Adsorción , Aminas , Dióxido de Carbono/química , Polietileneimina/química , Polímeros/química , Dióxido de Silicio/químicaRESUMEN
We present a quantitative approach to the self-dynamics of polymers under steady flow by employing a set of complementary reference frames and extending the spherical harmonic expansion technique to dynamic density correlations. Application of this method to nonequilibrium molecular dynamics simulations of polymer melts reveals a number of universal features. For both unentangled and entangled melts, the center-of-mass motions in the flow frame are described by superdiffusive, anisotropic Gaussian distributions, whereas the isotropic component of monomer self-dynamics in the center-of-mass frame is strongly suppressed. Spatial correlation analysis shows that the heterogeneity of monomer self-dynamics increases significantly under flow.
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We outline a machine learning strategy for quantitively determining the conformation of AB-type diblock copolymers with excluded volume effects using small angle scattering. Complemented by computer simulations, a correlation matrix connecting conformations of different copolymers according to their scattering features is established on the mathematical framework of a Gaussian process, a multivariate extension of the familiar univariate Gaussian distribution. We show that the relevant conformational characteristics of copolymers can be probabilistically inferred from their coherent scattering cross sections without any restriction imposed by model assumptions. This work not only facilitates the quantitative structural analysis of copolymer solutions but also provides the reliable benchmarking for the related theoretical development of scattering functions.
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Single atom impurities in graphene, substitutional silicon defects in particular, have been observed to diffuse under electron beam irradiation. However, the relative importance of elastic and inelastic scattering in facilitating their mobility remains unclear. Here, we employ excited-state electronic structure calculations to explore potential inelastic effects, and find an electronically nonadiabatic excited-state silicon diffusion pathway involving "softened" Si-C bonding that presents an â¼2 eV lower diffusion barrier than the ground-state pathway. Beam-induced transition rates to this state indicate that the excited-state pathway is accessible through irradiation of the defect site. However, even in the limit of fully elastic scattering, upward nonadiabatic transitions are also possible along the diffusion coordinate, increasing the diffusion barrier and further demonstrating the potential for electronic nonadiabaticity to influence beam-induced atomic transformations in materials. We also propose some experimentally testable signatures of such excited-state pathways.
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Polymer interfaces are key to a range of applications including membranes for chemical separations, hydrophobic coatings, and passivating layers for antifouling. While important, challenges remain in probing the interfacial monolayer where the molecular ordering and orientation can change depending on the chemical makeup or processing conditions. In this work, we leverage surface specific vibrational sum frequency generation (SFG) and the associated dependence on molecular symmetry to elucidate the ordering and orientations of key functional groups for poly(2,2,2-trifluoroethyl methacrylate) bottlebrush polymers and their linear polymer analogues. These measurements were framed by atomistic molecular dynamic simulations to provide a complementary physical picture of the gas-polymer interface. Simulations and SFG measurements show that methacrylate backbones are buried beneath a layer of trifluoroethyl containing side groups that result in structurally similar interfaces regardless of the polymer molecular weight or architecture. The average orientational angles of the trifluoroethyl containing side groups differ depending on polymer linear and bottlebrush architectures, suggesting that the surface groups can reorient via available rotational degrees of freedom. Results show that the surfaces of the bottlebrush and linear polymer samples do not strongly depend on molecular weight or architecture. As such, one cannot rely on increasing the molecular weight or altering the architecture to tune surface properties. This insight into the polymer interfacial structure is expected to advance the design of new material interfaces with tailored chemical/functional properties.
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Efficient carbon capture from stationary point sources can be achieved using hybrid adsorbents comprising nanoporous substrates coated with imine polymers. The physical properties of the CO2-adsorbing, nanodispersed polymers are altered by their interactions with the substrate, which in turn may impact their capture capacity. We study silica and carbon nanoporous substrates with different pore morphologies that were impregnated with polymer imine with the goal of characterizing the polymer dispersions in the pores. For silica and carbon samples, the mean densities of confined poly(ethylene imine) (PEI) were measured as functions of polymer loading and temperature using small-angle neutron scattering. Strong densification is found for imine polymers imbibed in mesoporous carbon. PEI in nanoporous silica does not experience this strong densification. At high loadings, plugs form, preferably at the pore throats, and can reduce accessible porosity. CO2 capture measurements show that PEI interactions with the substrate play an important role. PEI in carbon shows the highest capture capacity at low temperatures and the lowest CO2 adsorption at high temperatures, making it well-suited for temperature swing adsorption applications.
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Using electron beam manipulation, we enable deterministic motion of individual Si atoms in graphene along predefined trajectories. Structural evolution during the dopant motion was explored, providing information on changes of the Si atom neighborhood during atomic motion and providing statistical information of possible defect configurations. The combination of a Gaussian mixture model and principal component analysis applied to the deep learning-processed experimental data allowed disentangling of the atomic distortions for two different graphene sublattices. This approach demonstrates the potential of e-beam manipulation to create defect libraries of multiple realizations of the same defect and explore the potential of symmetry breaking physics. The rapid image analytics enabled via a deep learning network further empowers instrumentation for e-beam controlled atom-by-atom fabrication. The analysis described in the paper can be reproduced via an interactive Jupyter notebook at https://git.io/JJ3Bx.
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We investigate (1) electron-beam-induced plasmon absorption spectra of Ag molecular nanowire dimers and (2) electron-beam-induced energy transfer between two nanowires. We employ linear-response time-dependent density functional theory (TDDFT) and real-time TDDFT methods to simulate the electron-beam-induced plasmonic excitations, dynamics, and corresponding electron energy loss spectrum for small models of a single molecular nanowire with four Ag atoms and for two Ag nanowires. An array of different relative orientations of nanowires and of different initial excitation conditions resulting from applying an electron beam at different positions with respect to the Ag nanowires is investigated. The results demonstrate (1) an electron beam can induce plasmonic excitations from the molecular Ag nanowire ground state to the excited states that are both optically allowed and forbidden, (2) a tunability for selective excitations that can be controlled by the position of a focused electron beam, and (3) kinetic and dynamic behaviors of time-dependent electron-beam-induced energy transfer between two Ag molecular nanowires depend on the position of the beam source and nanowire separation distance, providing insights into the spatial dependences of plasmonic couplings in nanowire arrays.
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An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Lipids are capable of forming a variety of structures, including multi-lamellar vesicles. Layered lipid membranes are found in cell organelles, such as autophagosomes and mitochondria. Here, we present a mechanism for the formation of a double-walled vesicle (i.e., two lipid bilayers) from a unilamellar vesicle through the partitioning and phase separation of a small molecule. Using molecular dynamics simulations, we show that double membrane formation proceeds via a nucleation and growth process - i.e., after a critical concentration of the small molecules, a patch of double membrane nucleates and grows to cover the entire vesicle. We discuss the implications of this mechanism and theoretical approaches for understanding the evolution and formation of double membranes.
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Membrana Dobles de Lípidos , Simulación de Dinámica MolecularRESUMEN
Electron-phonon coupling in two-dimensional nanomaterials plays a fundamental role in determining their physical properties. Such interplay is particularly intriguing in semiconducting black phosphorus (BP) due to the highly anisotropic nature of its electronic structure and phonon dispersions. Here we report the direct observation of symmetry-dependent electron-phonon coupling in BP by performing the polarization-selective resonance Raman measurement in the visible and ultraviolet regimes, focusing on the out-of-plane Ag1 and in-plane Ag2 phonon modes. Their intrinsic resonance Raman excitation profiles (REPs) were extracted and quantitatively compared. The in-plane Ag2 mode exhibits remarkably strong resonance enhancement across the excitation wavelengths when the excitation polarization is parallel to the armchair (Ag2//AC) direction. In contrast, a dramatically weak resonance effect was observed for the same mode with the polarization parallel to zigzag (Ag2//ZZ) direction and for the out-of-plane Ag1 mode (Ag1//AC and Ag1//ZZ). Analysis on quantum perturbation theory and first-principles calculations on the anisotropic electron distributions in BP demonstrated that electron-phonon coupling considering the symmetry of the involved excited states and phonon vibration patterns is responsible for this phenomenon. Further analysis of the polarization-dependent REPs for Ag phonons allows us to resolve the existing controversies on the physical origin of Raman anomaly in BP and its dependence on excitation energy, sample thickness, phonon modes, and crystalline orientation. Our study gives deep insights into the underlying interplay between electrons and phonons in BP and paves the way for manipulating the electron-phonon coupling in anisotropic nanomaterials for future device applications.
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We propose a fast and accurate calculation method to compute the electronic couplings between molecular units in a thiophene-ring-based polymer chain mimicking a real organic semiconducting polymer, poly(3-hexylthiophene). Through a unit block diabatization scheme, the method employed minimal number of diabatic orbitals to compute the site energies and electronic couplings, which were validated by comparing with benchmark density functional theory calculations. In addition, by using the obtained electronic couplings, a quantum dynamics simulation was carried out to propagate a hole initially localized in a thiophene-ring unit of the polymer chain. This work establishes a simple, efficient, and robust means for the simulation of electron or hole transfer processes in organic semiconducting materials, an important capability for study and understanding of the class of organic optoelectronic and photovoltaic materials. © 2018 Wiley Periodicals, Inc.
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The extraordinary optoelectronic performance of hybrid organic-inorganic perovskites has resulted in extensive efforts to unravel their properties. Recently, observations of ferroic twin domains in methylammonium lead triiodide drew significant attention as a possible explanation for the current-voltage hysteretic behaviour in these materials. However, the properties of the twin domains, their local chemistry and the chemical impact on optoelectronic performance remain unclear. Here, using multimodal chemical and functional imaging methods, we unveil the mechanical origin of the twin domain contrast observed with piezoresponse force microscopy in methylammonium lead triiodide. By combining experimental results with first principles simulations we reveal an inherent coupling between ferroelastic twin domains and chemical segregation. These results reveal an interplay of ferroic properties and chemical segregation on the optoelectronic performance of hybrid organic-inorganic perovskites, and offer an exploratory path to improving functional devices.
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Curvature-induced domain sorting, a strategy exploited by cells to organize membrane components, is a promising mechanism to control self-assembly of materials. To understand this phenomenon, this work explores the effects of curvature on component rearrangement in thin polymer films and lipid bilayers supported on sinusoidal substrates. Specifically, self-consistent field theory (SCFT) was used to study the spatial distribution of polymers in blends containing conformationally asymmetric chains. In addition, coarse-grained molecular dynamics (MD) simulations were used to probe the arrangement of rigid lipid domains in a relatively soft lipid matrix. Besides the expected preference of rigid species localizing in regions with low mean curvature, both systems exhibit unexpected localization of rigid components in comparatively high curvature regions. The origins of this unexpected sorting are discussed in terms of entropic and enthalpic contributions. In summary, this study demonstrates that domain distribution strongly depends on local topography and further highlights the collective effects that thermodynamic forces have on the morphological behavior of membranes.
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Polymerized ionic liquids (PolyILs) are promising materials for applications in electrochemical devices spanning from fuel cells to capacitors and batteries. In principle, PolyILs have a competitive advantage over traditional electrolytes in being single ion conductors and thus enabling a transference number close to unity. Despite this perceived advantage, surprisingly low room temperature ionic conductivities measured in the lab raise an important fundamental question: how does the molecular structure mediate conductivity? In this work, wide-angle X-ray scattering (WAXS), vibrational sum frequency generation (vSFG), and density functional theory (DFT) calculations were used to study the bulk and interfacial structure of PolyILs, while broad band dielectric spectroscopy (BDS) was used to probe corresponding dynamics and conductive properties for a series of the PolyIL samples with tunable chemistries and structures. Our results reveal that the size of the mobile anions has a tremendous impact on chain packing in PolyILs that wasn't addressed previously. Larger mobile ions tend to create a well-packed structure, while smaller ions frustrate chain packing. The magnitude of these changes and level of structural heterogeneity are shown to depend on the chemical functionality and flexibility of studied PolyILs. Furthermore, these experimental and computational results provide new insight into the correlation between conductivity and structure in PolyILs, suggesting that structural heterogeneity helps to reduce the activation energy for ionic conductivity in the glassy state.
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Porous carbons with different textural properties exhibit great differences in CO2 adsorption capacity. It is generally known that narrow micropores contribute to higher CO2 adsorption capacity. However, it is still unclear what role each variable in the textural properties plays in CO2 adsorption. Herein, a deep neural network is trained as a generative model to direct the relationship between CO2 adsorption of porous carbons and corresponding textural properties. The trained neural network is further employed as an implicit model to estimate its ability to predict the CO2 adsorption capacity of unknown porous carbons. Interestingly, the practical CO2 adsorption amounts are in good agreement with predicted values using surface area, micropore and mesopore volumes as the input values simultaneously. This unprecedented deep learning neural network (DNN) approach, a type of machine learning algorithm, exhibits great potential to predict gas adsorption and guide the development of next-generation carbons.
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Two-dimensional materials such as layered transition-metal dichalcogenides (TMDs) are ideal platforms for studying defect behaviors, an essential step towards defect engineering for novel material functions. Here, we image the 3D lattice locations of selenium-vacancy V_{Se} defects and manipulate them using a scanning tunneling microscope (STM) near the surface of PdSe_{2}, a recently discovered pentagonal layered TMD. The V_{Se} show a characterisitc charging ring in a spatially resolved conductance map, based on which we can determine its subsurface lattice location precisely. Using the STM tip, not only can we reversibly switch the defect states between charge neutral and charge negative, but also trigger migrations of V_{Se} defects. This allows a demonstration of direct "writing" and "erasing" of atomic defects and tracing the diffusion pathways. First-principles calculations reveal a small diffusion barrier of V_{Se} in PdSe_{2}, which is much lower than S vacancy in MoS_{2} or an O vacancy in TiO_{2}. This finding opens an opportunity of defect engineering in PdSe_{2} for such as controlled phase transformations and resistive-switching memory device application.