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At least 1,477 records · Page 82

Floquet–Magnus theory and generic transient dynamics in periodically driven many-body quantum systems

This work explores a fundamental dynamical structure for a wide range of many-body quantum systems under periodic driving. Generically, in the thermodynamic limit, such systems are known to heat up to infinite temperature states in the long-time limit irrespective of dynamical details, which kills all the specific properties of the system. In the present study, instead of considering infinitely long-time scale, we aim to provide a general framework to understand the long but finite time behavior, namely the transient dynamics. In our analysis, we focus on the Floquet–Magnus (FM) expansion that gives a formal expression of the effective Hamiltonian on the system. Although in general the full series expansion is not convergent in the thermodynamics limit, we give a clear relationship between the FM expansion and the transient dynamics. More precisely, we rigorously show that a truncated version of the FM expansion accurately describes the exact dynamics for a certain time-scale. Our theory reveals an experimental time-scale for which non-trivial dynamical phenomena can be reliably observed. We discuss several dynamical phenomena, such as the effect of small integrability breaking, efficient numerical simulation of periodically driven systems, dynamical localization and thermalization. Especially on thermalization, we discuss a generic scenario on the prethermalization phenomenon in periodically driven systems. -- Highlights: •A general framework to describe transient dynamics for periodically driven systems. •The theory is applicable to generic quantum many-body systems including long-range interacting systems. •Physical meaning of the truncation of the Floquet–Magnus expansion is rigorously established. •New mechanism of the prethermalization is proposed. •Revealing an experimental time-scale for which non-trivial dynamical phenomena can be reliably observed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Improving logistic efficiency of WEEE collection through dynamic scheduling using simulation modeling

Highlights: • Latest EU regulation on WEEE require more flexible logistics models. • The implementation of dynamic scheduling is evaluated for WEEE collection. • A hybrid simulation model compares dynamic (pure and “mixed”) and static collection schemes. • Results confirm the higher flexibility and efficiency of dynamic systems. • Dynamic scheduling “mixed” solutions result more efficient than pure ones. - Abstract: The complexity of collection systems for Waste from Electric and Electronic Equipment (WEEE) in the EU is increasing, due to the latest directive that sets new collection targets and modes. The high variability and the uncertainty of reverse flows require innovative logistic approaches. One recent option for increasing efficiency and responsiveness in waste collection services, boosted by new technological solutions for waste level monitoring, is to adopt a dynamic collection scheme, where the collection frequency is not established a priori (based on a fixed plan), but it is based on the actual filling levels of waste bins. This option can allow the service provider to plan the collection service following the actual demand, resulting in a more responsive service, while improving the logistic efficiency. This paper evaluates the implementation of dynamic scheduling schemes for the collection of WEEE. A hybrid simulation model has been developed in order to support researchers and practitioners in assessing quantitative impacts of adopting dynamic scheduling in WEEE collection. Three logistic alternatives (a fixed collection schedule scheme, a pure dynamic scheme and a mixed one) have been compared in a test case based on data of an Italian municipality; collection services for different types of WEEE (i.e. large appliances and small items) have been analyzed. Results show a promising performance of dynamic schedules compared to the fixed one, revealing, for the specific test case, how a mixed solution can combine the advantages of dynamic and fixed scheduling, gaining flexibility towards customer demand while improving truck resource utilization.

42 ENGINEERING↗

Bulk-like and Interfacial Water Dynamics in Nafion Fuel Cell Membranes Investigated with Ultrafast Nonlinear IR Spectroscopy

The water confined in the hydrophilic domains of Nafion fuel cell membranes is central to its primary function of ion transport. Water dynamics are intimately linked to proton transfer and are sensitive to the structural features and length scales of confinement. Here, ultrafast polarization-selective pump-probe and two-dimensional infrared vibrational echo (2D IR) experiments were performed on fully hydrated Nafion membranes with sodium counterions to explicate the water dynamics. Like aerosol-OT reverse micelles (AOT RMs), the water dynamics in Nafion are attributed to bulk-like core water in the central region of the hydrophilic domains and much slower interfacial water. Population and orientational dynamics of water in Nafion are slowed by polymer confinement. Comparison of the observed dynamics to those of AOT RMs helps identify local interactions between water and sulfonate anions at the interface and among water molecules in the core. This comparison also demonstrates that the well-known spherical cluster morphology of Nafion is not appropriate. Spectral diffusion of the interfacial water, which arises from structural dynamics, was obtained from the 2D IR experiments taking the core water to have dynamics similar to bulk water. Like the orientational dynamics, spectral diffusion was found to be much slower at the interface compared to bulk water. Together, the dynamics indicate slow reorganization of weakly hydrogen-bonded water molecules at the interface of Nafion. We report these results provide insights into proton transport mechanisms in fuel cell membranes, and more generally, water dynamics near the interface of confining systems.

25 ENERGY STORAGE↗

Heterogeneous chain dynamics and aggregate lifetimes in precise acid-containing polyethylenes: Experiments and simulations

Melt state dynamics for a series of strictly linear polyethylenes with precisely spaced associating functional groups were investigated. The periodic pendant acrylic acid groups form hydrogen-bonded acid aggregates within the polyethylene (PE) matrix. The dynamics of these nanoscale heterogeneous morphologies were investigated from picosecond to nanosecond timescales by both quasi-elastic neutron scattering (QENS) measurements and fully atomistic molecular dynamics (MD) simulations. Two dynamic processes were observed. The faster dynamic processes which occur at the picosecond timescales are compositionally insensitive and indicative of spatially restricted local motions. The slower dynamic processes are highly composition dependent and indicate the structural relaxation of the polymer backbone. Higher acid contents, or shorter PE spacers between pendant acid groups, slow the structural relaxation timescale and increase the stretching parameter (β) of the structural relaxation. Additionally, the dynamics of specific hydrogen atom positions along the backbone correlate structural heterogeneity imposed by the associating acid groups with a mobility gradient along the polymer backbone. At time intervals (<2 ns), the mean-squared displacements for the four methylene groups closest to the acid groups are up to 10 times smaller than those of methylene groups further from the acid groups. At longer timescales acid aggregates rearrange and the chain dynamics of the slow, near-aggregate regions and the faster bridge regions converge, implying a characteristic timescale for the passage of chains between aggregates. As a result, the characterization of the nanoscale chain dynamics in these associating polymer systems both provides validation of simulation force fields and provides understanding of heterogeneous chain dynamics in associating polymers.

36 MATERIALS SCIENCE↗

Theory of the spatial transfer of interface-nucleated changes of dynamical constraints and its consequences in glass-forming films

We formulate a new theory for how caging constraints in glass-forming liquids at a surface or interface are modified and then spatially transferred, in a layer-by-layer bootstrapped manner, into the film interior in the context of the dynamic free energy concept of the Nonlinear Langevin Equation (NLE) theory approach. The dynamic free energy at any mean location (cage center) involves contributions from two adjacent layers where confining forces are not the same. At the most fundamental level of the theory, the caging component of the dynamic free energy varies essentially exponentially with distance from the interface, saturating deep enough into the film with a correlation length of modest size and weak sensitivity to the thermodynamic state. This imparts a roughly exponential spatial variation of all the key features of the dynamic free energy required to compute gradients of dynamical quantities including the localization length, jump distance, cage barrier, collective elastic barrier, and alpha relaxation time. The spatial gradients are entirely of dynamical, not structural or thermodynamic, origin. The theory is implemented for the hard sphere fluid and diverse interfaces which can be a vapor, a rough pinned particle solid, a vibrating (softened) pinned particle solid, or a smooth hard wall. Their basic description at the level of the spatially heterogeneous dynamic free energy is identical, with the crucial difference arising from the first layer where dynamical constraints can be weakened, softened, or hardly changed depending on the specific interface. Numerical calculations establish the spatial dependence and fluid volume fraction sensitivity of the key dynamical property gradients for five different model interfaces. A comparison of the theoretical predictions for the dynamic localization length and glassy modulus with simulations and experiments for systems with a vapor interface reveals good agreement. Finally, the present advance sets the stage for using the Elastically Collective NLE theory to make quantitative predictions for the alpha relaxation time gradient, decoupling phenomena, T g gradient, and many film-averaged properties of both model and experimental (colloids, molecules, and polymers) systems with diverse interfaces and chemical makeup.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamical disparity between hydration shell water and RNA in a hydrated RNA system

We have performed large-scale molecular dynamics simulations on hammerhead RNA in water and observed disparity in the dynamical properties between water and RNA. The simulations are carried out above the dynamical transition temperature of RNA and is varied from below freezing to ambient temperature. Using this model, we observed different types of relaxation dynamics for water and RNA. While RNA shows a single stretched exponential decay, the water molecules show a double-exponential decay. Both water and RNA dynamics show temperature and spatial dependence on relaxation times. The RNA relaxations are many orders of magnitude slower compared to water for all temperature and spatial length scales. RNA relaxations show predominantly heterogeneous dynamics. Water dynamics in the hydration shell show a combination of interfacial water and bulk-like water properties and the water dynamics are decoupled from the RNA dynamics. Furthermore, these results explain the dynamics of water in the hydration shell and that of RNA.

59 BASIC BIOLOGICAL SCIENCES↗

Nonlinear Modeling of Macroscopic Plasma Dynamics Final Scientific Report May 1, 2006 – April 30, 2018

The project entitled, "Nonlinear Modeling of Macroscopic Plasma Dynamics," applied numerical computation to solve mathematical models of plasma behavior in laboratory systems. Plasma is the state of matter with sufficiently large internal energy density such that electrons dissociate from atoms to form gas of electrically charged particles. It occurs naturally in stars, planetary magnetospheres, and interstellar and intergalactic media. It is also used for industrial purposes and in lighting. Fusion energy science seeks to create and sustain plasma conditions where atomic nuclei fuse to create energy that can be captured for power production. Many laboratory experiments for this effort use magnetic field to contain plasma and to thermally insulate it from its surroundings. Possible plasma dynamics in magnetized systems include collective behavior over spatial scales that are comparable to the configuration size, and these dynamics often include evolution of the magnetic field that is used for confinement. Solving the mathematical models that describe these dynamics in specific experiments often requires computer simulations, as done in this project. This project analyzed plasma magnetic relaxation dynamics in the laboratory configurations known as the reversed-field pinch (RFP), the spheromak, and the spherical torus (ST). It also developed capabilities for modeling disruptive plasma dynamics in the tokamak, which has achieved the highest performance for magnetized plasma and is the design of the large international ITER experiment (https://www.iter.org) that is under construction and is expected to be the first to achieve self-heating conditions. Dynamic evolution to states of low energy, the aforementioned magnetic relaxation, is known to be important for generating the RFP and spheromak configurations. Nonlinear computational modeling with the Non-Ideal Magnetohydrodynamics with Rotation, Open Discussion code (NIMROD, https://nimrodteam.org) was applied to understand specific aspects of magnetic relaxation in RFPs, spheromaks, and STs. The RFP study considered how the nonlinear transfer of power among different fluctuation harmonics is altered due to the application of pulses of electric field, as done experimentally in the Madison Symmetric Torus RFP device at the University of Wisconsin-Madison. It also investigated the separation of electron and ion dynamics, known as two-fluid effects, including effects on the evolution of the plasma flow profile. The spheromak study considered the influence of these two-fluid effects in conditions relevant to the Sustained Spheromak Experiment (SSPX), formerly at Lawrence Livermore National Laboratory. Our study found that two-fluid effects enhance stability with respect to interchange in SSPX-relevant conditions, but having a complete model with two-fluid effects in separate electron and ion temperature equations is important. The study for STs focused on plasma startup in the Pegasus Toroidal Experiment at UW-Madison, which uses DC voltage applied through a small plasma gun. The simulations show how the resulting helical current stream relaxes through repetitive merging, forming current rings that accumulate into a tokamak-like configuration. Analytical theory was also developed to help explain behavior that was observed in the RFP and spheromak computations. Although the tokamak configuration has outperformed other magnetic confinement configurations, it has a tendency to undergo discharge-terminating dynamics that release energy onto plasma-facing surfaces and exert electromechanical forces on magnetic coils and structures. Our efforts have improved NIMROD's capabilities to model tokamak disruption by incorporating a resistive wall model that can be applied to axisymmetric, as well as asymmetric, distortions of the magnetic field configuration. Computations addressed whether mathematical conditions applied to plasma flow at the wall influence disruptive dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High frequency dynamic engine simulation

A digital computer simulation of a mixed flow, twin spool turbofan engine was assembled to evaluate and improve the dynamic characteristics of the engine simulation to disturbance frequencies of at least 100 Hz. One dimensional forms of the dynamic mass, momentum and energy equations were used to model the engine. A TF30 engine was simulated so that dynamic characteristics could be evaluated against results obtained from testing of the TF30 engine at the NASA Lewis Research Center. Dynamic characteristics of the engine simulation were improved by modifying the compression system model. Modifications to the compression system model were established by investigating the influence of size and number of finite dynamic elements. Based on the results of this program, high frequency engine simulations using finite dynamic elements can be assembled so that the engine dynamic configuration is optimum with respect to dynamic characteristics and computer execution time. Resizing of the compression systems finite elements improved the dynamic characteristics of the engine simulation but showed that additional refinements are required to obtain close agreement simulation and actual engine dynamic characteristics.

Schuerman, J. A.↗

Dual redundant arm system operational quality measures and their applications - Dynamic measures

Dual-arm dynamic operation quality measures are presented which quantify the efficiency and capability of generating Cartesian accelerations by two cooperative arms based on the analysis of dual-arm dynamic interactions. Dual-arm dynamic manipulability is defined as the efficiency of generating Cartesian accelerations under the dynamic and kinematic interactions between individual arms and an object under manipulation. The analysis of dual-arm dynamic interactions is based on the so-called Cartesian space agent model of an arm, which represents an individual arm as a force source acting upon a point mass with the effective Cartesian space arm dynamics and an environment or an object under manipulation. The Cartesian space agent model of an arm makes it possible to derive the dynamic and kinematic constraints involved in the transport, assembly and grasping modes of dual-arm cooperation. A task-oriented operational quality measure, (TOQd) is defined by evaluating dual-arm dynamic manipulability in terms of given task requirements. TOQd is used in dual-arm joint configuration optimization. Simulation results are shown. A complete set of forward dynamic equations for a dual-arm system is derived, and dual-arm dynamic operational quality measures for various modes of dual-arm cooperation allowing sliding contacts are established.

Lee, Sukhan↗

Self-Supervised Dynamical Systems

Some progress has been made in a continuing effort to develop mathematical models of the behaviors of multi-agent systems known in biology, economics, and sociology (e.g., systems ranging from single or a few biomolecules to many interacting higher organisms). Living systems can be characterized by nonlinear evolution of probability distributions over different possible choices of the next steps in their motions. One of the main challenges in mathematical modeling of living systems is to distinguish between random walks of purely physical origin (for instance, Brownian motions) and those of biological origin. Following a line of reasoning from prior research, it has been assumed, in the present development, that a biological random walk can be represented by a nonlinear mathematical model that represents coupled mental and motor dynamics incorporating the psychological concept of reflection or self-image. The nonlinear dynamics impart the lifelike ability to behave in ways and to exhibit patterns that depart from thermodynamic equilibrium. Reflection or self-image has traditionally been recognized as a basic element of intelligence. The nonlinear mathematical models of the present development are denoted self-supervised dynamical systems. They include (1) equations of classical dynamics, including random components caused by uncertainties in initial conditions and by Langevin forces, coupled with (2) the corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces, denoted supervising forces, composed of probability densities and functionals thereof. The equations of classical mechanics represent motor dynamics that is, dynamics in the traditional sense, signifying Newton s equations of motion. The evolution of the probability densities represents mental dynamics or self-image. Then the interaction between the physical and metal aspects of a monad is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. This feedback is what makes the evolution of probability densities nonlinear. The deviation from linear evolution can be characterized, in a sense, as an expression of free will. It has been demonstrated that probability densities can approach prescribed attractors while exhibiting such patterns as shock waves, solitons, and chaos in probability space. The concept of self-supervised dynamical systems has been considered for application to diverse phenomena, including information-based neural networks, cooperation, competition, deception, games, and control of chaos. In addition, a formal similarity between the mathematical structures of self-supervised dynamical systems and of quantum-mechanical systems has been investigated.

Zak, Michail↗

Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This proposal describes an approach to validate the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft. The research described here is absolutely cutting edge. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional"validation by test only'' mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computationaf Fluid Dynamics can be used to veritY these requirements; however, the model must be validated by test data. The proposed research project includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT and OPEN FOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid . . . Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. To date, the author is the only person to look at the uncertainty in the entire computational domain. For the flow regime being analyzed (turbulent, threedimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

Groves, Curtis E.↗

An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. While considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here in this paper, we examine the importance of substrate dynamics in the cleavage of Kunitz-BPTI protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4 Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals a dramatic conformational change in the substrate upon proteolysis. Using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning three orders of magnitude, we identify global and local dynamic features of substrates on the ns-μs timescale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substratelike and product-like states, linking substrate dynamics on the ns-μs timescale with large collective substrate motions on the much slower timescale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding dynamic properties of materials using neutron spectroscopy and atomistic simulation

Recent developments in first-principles lattice dynamics and classical force field based molecular dynamics are revolutionising the field of neutron spectroscopy. Herein we present a short review of these methods, their critical role in the supporting of cutting-edge experiments, and how they are improved by matching experimental data. We begin with a brief overview of how lattice dynamics calculations can be compared to inelastic neutron scattering (INS) and molecular dynamics simulations to both INS and quasi-elastic neutron scattering (QENS). We then provide a series of exemplar applications where lattice dynamics and molecular dynamics have been used in conjunction with neutron spectroscopy to bring significant understanding to topical areas of materials science namely: (i) lattice dynamics and INS for the study of hybrid organic-inorganic perovskites (ii) lattice dynamics and INS for the study of flexible porous solids and (iii) molecular dynamics and QENS for probing molecular behaviour in zeolite catalysis. In all three cases, the understanding gained through the synergy of experiment and computation would have been significantly reduced using either in isolation. Finally, we consider the current state of the art, describing outstanding challenges and suggesting future directions in this exciting and fertile area of physical science.

36 MATERIALS SCIENCE↗

Atomistic details of protein dynamics and the role of hydration water

The importance of protein dynamics for their biological activity is nowwell recognized. Different experimental and computational techniques have been employed to study protein dynamics, hierarchy of different processes and the coupling between protein and hydration water dynamics. But, understanding the atomistic details of protein dynamics and the role of hydration water remains rather limited. Based on overview of neutron scattering, molecular dynamic simulations, NMR and dielectric spectroscopy results we present a general picture of protein dynamics covering time scales from faster than ps to microseconds and the influence of hydration water on different relaxation processes. Internal protein dynamics spread over a wide time range fromfaster than picosecond to longer than microseconds. We suggest that the structural relaxation in hydrated proteins appears on the microsecond time scale, while faster processes present mostly motion of side groups and some domains. Hydration water plays a crucial role in protein dynamics on all time scales. It controls the coupled protein-hydration water relaxation on 10 100 ps time scale. Our process defines the friction for slower protein dynamics. Analysis suggests that changes in amount of hydration water affect not only general friction, but also influence significantly the protein's energy landscape.

59 BASIC BIOLOGICAL SCIENCES↗

Anomaly analysis and visualization for dynamic networks through spatiotemporal graph segmentations

With recent technology advance in Internet of Things (IoT) that involves human, sensors, and mobile devices, networks are not only growing much larger but more complex and dynamic in nature. The spatiotemporal dynamics of networks are represented by both topological changes and temporal shifts of attribute information associated with network components. Understanding the pattern and trend of dynamic networks is increasingly important. While data mining approaches are generally useful in analyzing the statistical properties of networks, there has been recent trend to consider bringing human into the loop, and to examine how feedback from visualizations of large-scale dynamic networks can further improve data mining and machine learning. Traditional visualization methods based on animation and sequences of snapshot graphs are also limited by human cognitive capability. Here, we present a dynamic network analysis and visualization (DNAV) tool which explores the spatiotemporal dimensions of graph components. In particular, nodes and edges are augmented with spatiotemporal segmentation based on both topological and attribute dynamics (e.g., time and locations of connectivity). To further facilitate analysis of large dynamic networks, DNAV includes statistical dynamic overviews alongside graph views, as well as data filtering modules for scalable analysis. Using case studies on public datasets, we demonstrate the effectiveness of DNAV in understanding and analyzing anomalies in dynamic networks such as computer communication networks.

97 MATHEMATICS AND COMPUTING↗

Non-monotonic temperature dependence of nanoscopic dynamics measured in living housefly larvae

We have studied nanoscopic dynamics on pico-to nano-second time scale in living housefly ( Musca domestica ) larvae using quasielastic neutron scattering. Model-independent data exhibit two distinct dynamic components measurable on the time scale probed in the experiment. The broad component is reminiscent of water dynamics, but somewhat slower, and must be associated with the scattering contribution from the hemolymph in larvae. The narrow (slow) component is similar in appearance to the dynamics measured previously in the living planarian flatworms. Unlike the monotonic temperature dependence for the hemolymph dynamics, the temperature dependence for the slow dynamic component shows an increase at 298 K, in the middle of the measured (on cooling down) range of 303.8 to 289.3 K. A similar increase at 298 K, in the middle of the measured (on warming up, and with different sample environment temperature control equipment used) range of 284.5–304.1 K, has been previously observed for the slow dynamic component in living planarian flatworms. Here, an increase in the measurable nanoscopic dynamics at a mid-range temperature of 298 K, decoupled from the hemolymph dynamics, is an unexpected phenomenon, apparently observable among organisms from different phyla, such as flatworms and arthropods.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamics of polymer segments, polymer chains, and nanoparticles in polymer nanocomposite melts: A review

The addition of nanoparticles (NPs) to a polymer matrix, forming a polymer nanocomposite (PNC), is known to alter the microscopic dynamic processes of both species which leads to unique macroscopic material properties of the PNC. Because the NPs and polymers have overlapping characteristic length, time, and energy scales, the interactions within these materials are complex and the dynamics are interrelated. In this review, we present an overview of experimental, simulation, and theoretical results that probe multi-scale polymer and nanoparticle dynamics in polymer nanocomposites and navigate the dense parameter space presented by these multicomponent systems. Although a variety of PNC systems are mentioned, we focus this discussion on linear thermoplastics filled with hard spherical or cylindrical NPs in the melt state. We begin by introducing PNCs, the dynamic processes within them, and the importance of dynamics for properties and processing. At the smallest length and time scales, we discuss segmental dynamics in PNCs, including the role of polymer attributes, NP attributes, and NP-polymer interactions. Then, we present measurements of collective motions and intermediate (Rouse) dynamics in various PNC materials. At longer length and time scales, we discuss polymer center-of-mass diffusion in PNCs with either spherical or anisotropic NPs. We then explore the dynamics of the NPs in PNCs and polymer melts, including theoretical predictions, simulation results, and experimental observations. Lastly, we note some of the remaining challenges in probing dynamics in PNC materials and fundamentally studying PNCs more generally.

36 MATERIALS SCIENCE↗

Understanding Interfacial Block Copolymer Structure and Dynamics

Here, block copolymer (BCP) structure and dynamics were studied using small-angle neutron scattering (SANS), neutron spin echo (NSE) spectroscopy, and molecular dynamics (MD) simulations to obtain a fundamental understanding of the impact of an interfacial block on chain dynamics. A glassy block acted as the interface, and the dynamics of a rubbery block was studied. The rubbery block was protonated near the interface in one sample and near the chain end in another sample to observe the interfacial effect on the rubbery polymer. Analysis of the structure and dynamics revealed that the interfacial rubbery block was confined in layered morphologies and exhibited much slower dynamics than the chain-end rubbery block that was dispersed in the rubbery matrix. The interfacial rubbery block showed weaker dynamical relaxation than that at the chain end, and it also had critically important length scale dependence. Dynamical slowing was only observed at length scales significantly larger than the characteristic segmental length, and the disparity between interfacial and chain-end dynamics increased with increasing length.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗