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At least 1,603 records · Page 89

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DOE OSTI2015

Different conformational dynamics of β-arrestin1 and β-arrestin2 analyzed by hydrogen/deuterium exchange mass spectrometry

Highlights: • The conformational dynamics of β-arrestin1 or β-arrestin2 were analyzed by HDX-MS. • β-Strands II through IV were more dynamic in β-arrestin2 than in β-arrestin1. • The middle loop was less dynamic in β-arrestin2 than in β-arrestin1. • Upon pre-activation by the R169E mutation, β-arrestins became more dynamic. • Pre-activation affected a wider region of β-arrestin1 compared to β-arrestin2. - Abstract: Arrestins have important roles in G protein-coupled receptor (GPCR) signaling including desensitization of GPCRs and G protein-independent signaling. There have been four arrestins identified: arrestin1, arrestin2 (e.g. β-arrestin1), arrestin3 (e.g. β-arrestin2), and arrestin4. β-Arrestin1 and β-arrestin2 are ubiquitously expressed and regulate a broad range of GPCRs, while arrestin1 and arrestin4 are expressed in the visual system. Although the functions of β-arrestin1 and β-arrestin2 widely overlap, β-arrestin2 has broader receptor selectivity, and a few studies have suggested that β-arrestin1 and β-arrestin2 have distinct cellular functions. Here, we compared the conformational dynamics of β-arrestin1 and β-arrestin2 by hydrogen/deuterium exchange mass spectrometry (HDX-MS). We also used the R169E mutant as a pre-activation model system. HDX-MS data revealed that β-strands II through IV were more dynamic in β-arrestin2 in the basal state, while the middle loop was more dynamic in β-arrestin1. With pre-activation, both β-arrestin1 and β-arrestin2 became more flexible, but broader regions of β-arrestin1 became flexible compared to β-arrestin2. The conformational differences between β-arrestin1 and β-arrestin2 in both the basal and pre-activated states might determine their different receptor selectivities and different cellular functions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Understanding collective human movement dynamics during large-scale events using big geosocial data analytics

Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. Finally, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Weighted Composition Operators for Learning Nonlinear Dynamics

Operator theoretic methods in dynamical system have been dominated by the use of Koopman operators and their continuous time counterparts, such as Koopman Generators and Liouville Operators. The advantage gained from their use primarily stems from the ability to extract subspaces and eigenfunctions within a space of observables that are invariant with respect to the Koopman operator over that space. When this occurs, a dynamic mode decomposition of the systems state provides a linear model for the dynamical system. Not all Koopman operators have eigenfunctions that may be exploited in this manner. However, the framework can still be leveraged for approximations using other operators. In this setting, we present a different operator for the study of dynamical systems, the weighted composition operator. These operators are compact for a wide range of dynamics and spaces, and through their interactions with occupation kernels and vector valued kernels, they admit an estimation of the underlying dynamics. Here, this manuscript presents a new algorithm for the data driven study of dynamical systems from data, and also provides two numerical experiments where convergence is achieved as a proof of concept.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Real-time visualization of dynamic fractures in porcine bones and the loading-rate effect on their fracture toughness

In this work we visualized, in real time, the dynamic fracture behaviors in porcine cortical bone from humerus and porcine trabecular bone from nasal bone at a high loading rate using highspeed synchrotron X-ray phase-contrast imaging (PCI). Dynamic three-point bending loading was applied on notched bone specimens by a modified Kolsky compression bar and images of the entire fracture events were recorded with an ultra-high-speed camera. Experiments at a quasi-static loading rate on material testing system (MTS) were also performed to identify the loading-rate effects on the fracture toughness of the two types of bone. Three-dimensional synchrotron X-ray computed tomography was conducted to examine the initial microstructures in the bone specimens before mechanical loading. At the dynamic loading rate, the onset locations of crack initiation were found to be independent from the bone types. The deleterious effect of dynamic loading rate on bone's fracture toughness was verified in this study and the crack was found to propagate at higher speeds in cortical bone than in trabecular bone. In a comparison of the observed more torturous crack paths at the quasi-static loading rate, cracks in dynamically loaded bone specimens generally followed the paths with less in-plane deflections and out-of-plane twists. However, our experimental results also indicated that, although the extent was diminished at dynamic loading rate, the crack deflections at osteon cement lines still played a role as a major toughening mechanism to dynamic fractures in transversely orientated cortical bone.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Dynamic energy absorption characteristics of hollow microlattice structures

Hollow microlattice structures are promising candidates for advanced energy absorption and their characteristics under dynamic crushing are explored. The energy absorption can be significantly enhanced by inertial stabilization, shock wave effect and strain rate hardening effect. In this paper we combine theoretical analysis and comprehensive finite element method simulation to decouple the three effects, and then obtain a simple model to predict the overall dynamic effects of hollow microlattice structures. Inertial stabilization originates from the suppression of sudden crushing of the microlattice and its contribution scales with the crushing speed, v. Shock wave effect comes from the discontinuity across the plastic shock wave front during dynamic loading and its contribution scales with e. The strain rate effect increases the effective yield strength upon dynamic deformation and increases the energy absorption density. A mechanism map is established that illustrates the dominance of these three dynamic effects at a range of crushing speeds. Compared with quasi-static loading, the energy absorption capacity a dynamic loading of 250 m/s can be enhanced by an order of magnitude. The study may shed useful insight on designing and optimizing the energy absorption performance of hollow microlattice structures under various dynamic loads. (C) 2014 Elsevier Ltd. All rights reserved.

Liu, YL↗

DOE OSTI2024

Deformation and Delamination of Dynamically Bulging Bilayered Films

We employ finite element simulations to study the dynamic bulging of films under shock tube conditions and compare these responses with quasi-static bulging. Both scenarios subject the film to time-varying pressure. Two film types are considered: uniform material films and bilayers with a relatively soft interior layer and a hard exterior layer. The interface between the materials in the bilayer cases is modeled as a cohesive zone that follows a bilinear normal traction-separation cohesive law. Additionally, bilayer films with preexisting cracks in the interior layer are analyzed. Parametric studies are also conducted to explore the effects of loading rate and specimen size. The mechanical response of all materials is assumed to be strain-rate independent, focusing solely on the inertial effects in the response of the films under dynamic loading, and the absence of such effects under quasi-static loading. The results indicate that quasi-static bulging exhibits a predictable plate bending like deformation. In contrast, depending on the loading rate and specimen size, dynamic bulging can give rise to elastic waves, and a sequence of deformation processes including initial uniform acceleration, followed by bending-like deformation, and finally through-thickness biaxial stretching. Dynamic loading also leads to larger bulge formation and greater deformation than quasi-static loading. A key finding is the role of preexisting cracks in driving delamination under dynamic loading, which is absent in quasi-static loading. This work enhances our understanding of dynamic bulging and motivates further research on characterizing delamination in layered films using dynamic bulge tests.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A dynamic price model based on supply and demand with application to techno-economic assessments of rare earth element recovery technologies

Rare Earth Elements (REEs) are essential for sustainable energy technologies. Techno-economic Assessments (TEAs) have been conducted to evaluate innovative approaches to recover REEs from waste streams. However, most TEA studies do not consider the price volatility of REEs, which raises concern over the reliability of the analysis in an unpredictable dynamic market. To address this shortcoming, a dynamic price model is proposed that adjusts REE price based upon supply-demand conditions. The dynamic market behavior is simulated and its effect on a TEA is examined via a case study. The results of the dynamic simulation indicate a growing trend of the market price for REE materials/products. Compared to a conventional TEA that does not consider price dynamics, a significant difference in economic performance metrics is identified from the dynamic TEA results. Finally, the proposed dynamic TEA method is not limited to a specific application and can provide insights for evaluating a broad range of technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Real-Space Local Dynamics in 1,2,3-Triazole Using Inelastic Neutron Scattering

Enhancing proton transport in polymer electrolytes is crucial for advancing next-generation solid-state batteries, yet our understanding of proton conductivity in nonaqueous environments remains limited due to a lack of atomic-scale insights. Here, in this study, we investigated the atomic-scale dynamics of 1,2,3-triazole, a small molecule capable of dynamic hydrogen bonding, as a model system for proton hopping in nonaqueous environments. Using the real-space correlation function determined by the double Fourier transformation of inelastic neutron scattering spectra, we identified that the self-motion of protons and intermolecular dynamics occur on comparable time scales. Furthermore, we observed that the activation energy associated with the intermolecular dynamics matches the energy barrier for molecular rotations determined through Density Functional Theory calculations. These findings underscore the importance of controlling molecular dynamics at the atomic scale to control proton transport. Additionally, we demonstrated that intermolecular dynamics in systems involving protons can be studied using inelastic neutron scattering even without deuteration, thereby providing a broader avenue for studying atomic-scale dynamics in soft matter systems.

Shinohara, Yuya [Oak Ridge National Laboratory (OR↗

DOE OSTI2016

Protein-style dynamical transition in a non-biological polymer and a non-aqueous solvent

Using neutron scattering and molecular dynamics simulation, techniques most often associated with protein dynamical transition studies, we have investigated the microscopic dynamics of one of the most common polymers, polystyrene, which was exposed to toluene vapor, mimicking the process of protein hydration from water vapor. Polystyrene with adsorbed toluene is an example of a solvent-solute system, which, unlike biopolymers, is anhydrous and lacks hydrogen bonding. Nevertheless, it exhibits the essential traits of the dynamical transition in biomolecules, such as a specific dependence of the microscopic dynamics of both solvent and host on the temperature and the amount of solvent adsorbed. Ultimately, we conclude that the protein dynamical transition is a manifestation of a universal solvent-solute dynamical relationship, which is not specific to either biomolecules as solute, or aqueous media as solvent, or even a particular type of interactions between solvent and solute.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Charge Dependence of Local Hydration Dynamics in Poly(Acrylic Acid) Solutions

Localized measurements of hydration dynamics surrounding poly(acrylic acid) (pAA) chains are executed using Overhauser dynamic nuclear polarization relaxometry to determine the role of polymer protonation state on the polymer solvation environment. Alterations in polymer concentration and solution pH uncovered three different regimes of local water dynamics ranging from bulk-water-like to subdued water diffusivity. These experiments, combined with molecular dynamics simulations, reveal that the presence of deprotonated carboxylic acid groups promotes a hydrophilic local environment and extended polymer chain configurations that together incentivize the incorporation of bulk-like water near the polymer. This results in a stretched polymer conformation that leads to faster observed hydration dynamics in the local hydration environment. Meanwhile, protonated carboxylic acid groups are expected to engage in intrapolymer hydrogen bonding between monomer groups, resulting in a more collapsed conformation and slower observed hydration dynamics. The importance of the carboxylic acid groups on mediating hydration behavior is further illustrated by their role in dictating the solvation environment around poly(acrylic acid-stat-(poly(ethylene glycol) methyl ether acrylate) (p(AA-stat-PEGMEA)) copolymers with varying monomer ratios. Furthermore, these local hydration measurements establish a connection between local water dynamics and polymer chain conformation and may provide additional molecular perspective into poly(acrylic acid)’s classification as a superabsorbent polymer.

Conformation↗

DOE OSTI2017

Dynamics of Nanoparticles in Entangled Polymer Solutions

The mean square displacement < r 2 > of nanoparticle probes dispersed in simple isotropic liquids and in polymer solutions is interrogated using fluorescence correlation spectroscopy and single-particle tracking (SPT) experiments. Probe dynamics in different regimes of particle diameter (d), relative to characteristic polymer length scales, including the correlation length (ξ), the entanglement mesh size (a), and the radius of gyration (R g ), are investigated. In simple fluids and for polymer solutions in which d >> R g , long-time particle dynamics obey random-walk statistics < r 2 >:t, with the bulk zero-shear viscosity of the polymer solution determining the frictional resistance to particle motion. In contrast, in polymer solutions with d < R g , polymer molecules in solution exert noncontinuum resistances to particle motion and nanoparticle probes appear to interact hydrodynamically only with a local fluid medium with effective drag comparable to that of a solution of polymer chain segments with sizes similar to those of the nanoparticle probes. Under these conditions, the nanoparticles exhibit orders of magnitude faster dynamics than those expected from continuum predictions based on the Stokes–Einstein relation. SPT measurements further show that when d > a, nanoparticle dynamics transition from diffusive to subdiffusive on long timescales, reminiscent of particle transport in a field with obstructions. This last finding is in stark contrast to the nanoparticle dynamics observed in entangled polymer melts, where X-ray photon correlation spectroscopy measurements reveal faster but hyperdiffusive dynamics. As a result, we analyze these results with the help of the hopping model for particle dynamics in polymers proposed by Cai et al. and, on that basis, discuss the physical origins of the local drag experienced by the nanoparticles in entangled polymer solutions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

Learning stochastic dynamics and predicting emergent behavior using transformers

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Data-driven discovery of dynamics from time-resolved coherent scattering

Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is often limited by one or more factors—the ability to visualize dynamics in real space, computational cost of high-fidelity simulations, and effectiveness of approximate or phenomenological models. In this work, we develop a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved CXS measurements without solving the phase reconstruction problem for the entire time series of diffraction patterns. Our approach uses neural differential equations to parameterize unknown real-space dynamics and implements a computational scattering forward model to relate real-space predictions to reciprocal-space observations. This method is shown to recover the dynamics of several computational model systems under various simulated conditions of measurement resolution and noise. Moreover, the trained model enables estimation of long-term dynamics well beyond the maximum observation time, which can be used to inform and refine experimental parameters in practice. Finally, we demonstrate an experimental proof-of-concept by applying our framework to recover the probe trajectory from a ptychographic scan. Our proposed framework bridges the wide existing gap between approximate models and complex data.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Ultrafast hot-hole injection modifies hot-electron dynamics in Au/p-GaN heterostructures

A fundamental understanding of hot-carrier dynamics in photo-excited metal nanostructures is needed to unlock their potential for photodetection and photocatalysis. Despite numerous studies on the ultrafast dynamics of hot electrons, so far, the temporal evolution of hot holes in metal-semiconductor heterostructures remains unknown. Here, we report ultrafast (t < 200 fs) hot-hole injection from Au nanoparticles into the valence band of p-type GaN. The removal of hot holes from below the Au Fermi level is observed to substantially alter the thermalization dynamics of hot electrons, reducing the peak electronic temperature and the electron-phonon coupling time of the Au nanoparticles. First-principles calculations reveal that hot-hole injection modifies the relaxation dynamics of hot electrons in Au nanoparticles by modulating the electronic structure of the metal on timescales commensurate with electron-electron scattering. Overall, these results advance our understanding of hot-hole dynamics in metal-semiconductor heterostructures and offer additional strategies for manipulating the dynamics of hot carriers on ultrafast timescales. Photo-excited gold nanoparticles are shown to provide ultrafast and efficient hot-hole injection to the valence band of p-type GaN, substantially altering hot-electron dynamics in the nanoparticles and forming a basis to design hot-hole-based optoelectronics.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Bridging length scales in organic mixed ionic–electronic conductors through internal strain and mesoscale dynamics

Understanding the structural and dynamic properties of disordered systems at the mesoscale is crucial. This is particularly important in organic mixed ionic-electronic conductors (OMIECs), which undergo significant and complex structural changes when operated in an electrolyte. Here, in this study, we investigate the mesoscale strain, reversibility and dynamics of a model OMIEC material under external electrochemical potential using operando X-ray photon correlation spectroscopy. Our results reveal that strain and structural hysteresis depend on the sample's cycling history, establishing a comprehensive kinetic sequence bridging the macroscopic and microscopic behaviours of OMIECs. Furthermore, we uncover the equilibrium and non-equilibrium dynamics of charge carriers and material-doping states, highlighting the unexpected coupling between charge carrier dynamics and mesoscale order. These findings advance our understanding of the structure-dynamics-function relationships in OMIECs, opening pathways for designing and engineering materials with improved performance and functionality in non-equilibrium states during device operation. Understanding mesoscale structure and dynamics in organic mixed ionic-electronic conductors is crucial. Mesoscale strain kinetics and structural hysteresis have been studied, and they uncover the coupling between charge carrier dynamics and mesoscale order in organic mixed ionic-electronic conductors.

36 MATERIALS SCIENCE↗

DOE OSTI2016

The hydrogen-bond collective dynamics in liquid methanol

The relatively simple molecular structure of hydrogen-bonded (HB) systems is often belied by their exceptionally complex thermodynamic and microscopic behaviour. For this reason, after a thorough experimental, computational and theoretical scrutiny, the dynamics of molecules in HB systems still eludes a comprehensive understanding. Aiming at shedding some insight into this topic, we jointly used neutron Brillouin scattering and molecular dynamics simulations to probe the dynamics of a prototypical hydrogen-bonded alcohol, liquid methanol. The comparison with the most thoroughly investigated HB system, liquid water, pinpoints common behaviours of their THz microscopic dynamics, thereby providing additional information on the role of HB dynamics in these two systems. This study demonstrates that the dynamic behaviour of methanol is much richer than what so far known, and prompts us to establish striking analogies with the features of liquid and supercooled water. In particular, based on the strong differences between the structural properties of the two systems, our results suggest that the assignment of some dynamical properties to the tetrahedral character of water structure should be questioned. We finally highlight the similarities between the characteristic decay times of the time correlation function, as obtained from our data and the mean lifetime of hydrogen bond known in literature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Impact of hydration and temperature history on the structure and dynamics of lignin

The full utilization of plant biomass for the production of energy and novel materials often involves high temperature treatment. Examples include melt spinning of lignin for manufacturing low-cost carbon fiber and the relocalization of lignin to increase the accessibility of cellulose for production of biofuels. These temperature-induced effects arise from poorly understood changes in lignin flexibility. Here, we combine molecular dynamics simulations with neutron scattering and dielectric spectroscopy experiments to probe the dependence of lignin dynamics on hydration and thermal history. We find a dynamical and structural hysteresis: at a given temperature, the lignin molecules are more expanded and their dynamics faster when the lignin is cooled than when heated. The structural hysteresis is more pronounced for dry lignin. The difference in dynamics, however, follows a different trend, it is found to be more significant at high temperatures and high hydration levels. The simulations also reveal syringyl units to be more dynamic than guiacyl. The results provide an atomic-detailed description of lignin dynamics, important for understanding lignin role in plant cell wall mechanics and for rationally improving lignin processing. The lignin glass transition, at which the polymer softens, is lower when lignin is cooled than when heated, therefore extending the cooling phase of processing and shortening the heating phase may offer ways to lower processing costs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Relevance of hydrogen bonded associates to the transport properties and nanoscale dynamics of liquid and supercooled 2-propanol

2-Propanol was investigated, in both the liquid and supercooled states, as a model system to study how hydrogen bonds affect the structural relaxation and the dynamics of mesoscale structures, of approximately several Ångstroms, employing static and quasi-elastic neutron scattering and molecular dynamics simulation. Dynamic neutron scattering measurements were performed over an exchanged wave-vector range encompassing the pre-peak, indicative of the presence of H-bonding associates, and the main peak. The dynamics observed at the pre-peak is associated with the formation and disaggregation of the H-bonded associates and is measured to be at least one order of magnitude slower than the dynamics at the main peak, which is identified as the structural relaxation. Additionally, the measurements indicate that the macroscopic shear viscosity has a similar temperature dependence as the dynamics of the H-bonded associates, which highlights the important role played by these structures, together with the structural relaxation, in defining the macroscopic rheological properties of the system. Importantly, the characteristic relaxation time at the pre-peak follows an Arrhenius temperature dependence whereas at the main peak it exhibits a non-Arrhenius behavior on approaching the supercooled state. The origin of this differing behavior is attributed to an increased structuring of the hydrophobic domains of 2-propanol accommodating a more and more encompassing H-bond network, and a consequent set in of dynamic cooperativity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗