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At least 757 records · Page 42

Exploring Li-Ion Transport Properties of Li 3 TiCl 6 : A Machine Learning Molecular Dynamics Study

We performed large-scale molecular dynamics simulations based on a machine-learning force field (MLFF) to investigate the Li-ion transport mechanism in cation-disordered Li 3 TiCl 6 cathode at six different temperatures, ranging from 25°C to 100°C. In this work, deep neural network method and data generated by ab − initio molecular dynamics (AIMD) simulations were deployed to build a high-fidelity MLFF. Radial distribution functions, Li-ion mean square displacements (MSD), diffusion coefficients, ionic conductivity, activation energy, and crystallographic direction-dependent migration barriers were calculated and compared with corresponding AIMD and experimental data to benchmark the accuracy of the MLFF. From MSD analysis, we captured both the self and distinct parts of Li-ion dynamics. The latter reveals that the Li-ions are involved in anti-correlation motion that was rarely reported for solid-state materials. Similarly, the self and distinct parts of Li-ion dynamics were used to determine Haven’s ratio to describe the Li-ion transport mechanism in Li 3 TiCl 6 . Obtained trajectory from molecular dynamics infers that the Li-ion transportation is mainly through interstitial hopping which was confirmed by intra- and inter-layer Li-ion displacement with respect to simulation time. Ionic conductivity (1.06 mS/cm) and activation energy (0.29eV) calculated by our simulation are highly comparable with that of experimental values. Overall, the combination of machine-learning methods and AIMD simulations explains the intricate electrochemical properties of the Li 3 TiCl 6 cathode with remarkably reduced computational time. Thus, our work strongly suggests that the deep neural network-based MLFF could be a promising method for large-scale complex materials.

Selvaraj, Selva Chandrasekaran (ORCID:000000029023↗

Atomistic simulations of nanoindentation on nanoglasses: Effects of grain size and gradient microstructure on the mechanical properties

The use of nanoglass (NG) microstructures has been shown as an effective strategy to improve the ductility of rather brittle metallic glass alloys. To evaluate the effects of grain size and gradient design on the mechanical properties of NGs, we perform molecular dynamics simulations of nanoindentation on Cu 64 Zr 36 NGs. We consider samples with uniform 3 and 7 nm grain sizes as well as gradient microstructures with gradient grain sizes varying from 3 to 7 nm. Here, the results show that the deformation mechanism in NGs with small grain sizes is dominated by the activation and evolution of multiple shear transformation zones. Increasing grain sizes enhances the elastic modulus and hardness at the cost of reduced abrasion resistance. Though the average grain size at the indentation surface plays a crucial role in the deformation behavior of gradient NG models, their strain localization and plastic deformation states are affected by the grain sizes far from the indenter. Desired combinations of mechanical properties can be realized by different NG microstructure designs.

36 MATERIALS SCIENCE↗

Towards Construction of a Novel Nanometer-Resolution MeV-STEM for Imaging Thick Frozen Biological Samples

Driven by life-science applications, a mega-electron-volt Scanning Transmission Electron Microscope (MeV-STEM) has been proposed here to image thick frozen biological samples as a conventional Transmission Electron Microscope (TEM) may not be suitable to image samples thicker than 300–500 nm and various volume electron microscopy (EM) techniques either suffering from low resolution, or low speed. The high penetration of inelastic scattering signals of MeV electrons could make the MeV-STEM an appropriate microscope for biological samples as thick as 10 μm or more with a nanoscale resolution, considering the effect of electron energy, beam broadening, and low-dose limit on resolution. The best resolution is inversely related to the sample thickness and changes from 6 nm to 24 nm when the sample thickness increases from 1 μm to 10 μm. To achieve such a resolution in STEM, the imaging electrons must be focused on the specimen with a nm size and an mrad semi-convergence angle. This requires an electron beam emittance of a few picometers, which is ~1000 times smaller than the presently achieved nm emittance, in conjunction with less than 10 -4 energy spread and 1 nA current. We numerically simulated two different approaches that are potentially applicable to build a compact MeV-STEM instrument: (1) DC (Direct Current) gun, aperture, superconducting radio-frequency (SRF) cavities, and STEM column; (2) SRF gun, aperture, SRF cavities, and STEM column. Beam dynamic simulations show promising results, which meet the needs of an MeV-STEM, a few-picometer emittance, less than 10 -4 energy spread, and 0.1–1 nA current from both options. Also, we designed a compact STEM column based on permanent quadrupole quintuplet, not only to demagnify the beam size from 1 μm at the source point to 2 nm at the specimen but also to provide the freedom of changing the magnifications at the specimen and a scanning system to raster the electron beam across the sample with a step size of 2 nm and the repetition rate of 1 MHz. This makes it possible to build a compact MeV-STEM and use it to study thick, large-volume samples in cell biology.

36 MATERIALS SCIENCE↗

Protein folding from heterogeneous unfolded state revealed by time-resolved X-ray solution scattering

One of the most challenging tasks in biological science is to understand how a protein folds. In theoretical studies, the hypothesis adopting a funnel-like free-energy landscape has been recognized as a prominent scheme for explaining protein folding in views of both internal energy and conformational heterogeneity of a protein. Despite numerous experimental efforts, however, comprehensively studying protein folding with respect to its global conformational changes in conjunction with the heterogeneity has been elusive. Here we investigate the redox-coupled folding dynamics of equine heart cytochrome c (cyt-c) induced by external electron injection by using time-resolved X-ray solution scattering. A systematic kinetic analysis unveils a kinetic model for its folding with a stretched exponential behavior during the transition toward the folded state. With the aid of the ensemble optimization method combined with molecular dynamics simulations, we found that during the folding the heterogeneously populated ensemble of the unfolded state is converted to a narrowly populated ensemble of folded conformations. These observations obtained from the kinetic and the structural analyses of X-ray scattering data reveal that the folding dynamics of cyt-c accompanies many parallel pathways associated with the heterogeneously populated ensemble of unfolded conformations, resulting in the stretched exponential kinetics at room temperature. This finding provides direct evidence with a view to microscopic protein conformations that the cyt-c folding initiates from a highly heterogeneous unfolded state, passes through still diverse intermediate structures, and reaches structural homogeneity by arriving at the folded state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Grain Boundary Misorientation on Spall Strength in Ta via Shock-Free Simulations with Relatively Few Atoms

A suite of 37 molecular dynamics simulations is conducted at two system sizes to systematically characterize the role of grain boundary (GB) misorientation on spall strength in pure BCC tantalum (Ta). The systems studied consist of bicrystals with a single [110] symmetric tilt grain boundary. Two loading conditions are compared: (i) homogeneous extension under uniaxial strain simulated in this study and (ii) piston/flyer impact of sample, which induces heterogeneous deformation via shockwave propagation along the length of the sample. The piston/flyer impact is taken from the literature and run on the same set of GB misorientation angles using LAMMPS. The major finding here is that both methods result in similar spall strength predictions, but the homogeneous extension method generally requires two to three orders of magnitude fewer atoms and similar reductions in computational costs. Spall strength results systematically overpredict using this method, by about 10% for the dataset three orders of magnitude smaller than piston/flyer simulations, and 5% for the dataset two orders of magnitude smaller. Lastly, the effect of system size and pre-compression magnitude on spall strength is systematically characterized.

36 MATERIALS SCIENCE↗

Photoinduced Electron–Nuclear Dynamics of Fullerene and Its Monolayer Networks in Solvated Environments

The recently synthesized monolayer fullerene network in a quasi-hexagonal phase (qHP-C 60 ) exhibits superior electron mobility and optoelectronic properties compared to molecular fullerene (C 60 ), making it highly promising for a variety of applications. However, the microscopic carrier dynamics of qHP-C 60 remain unclear, particularly in realistic environments, which are of significant importance for applications in optoelectronic devices. Unfortunately, traditional ab initio methods are prohibitive for capturing the real-time carrier dynamics of such large systems due to their high computational cost. In this work, we present the first real-time electron–nuclear dynamics study of qHP-C 60 using velocity-gauge density functional tight binding, which enables us to perform several picoseconds of excited-state electron–nuclear dynamics simulations for nanoscale systems with periodic boundary conditions. When applied to C 60 , qHP-C 60 , and their solvated counterparts, we demonstrate that water/moisture significantly increases the electron–hole recombination time in C 60 but has little impact on qHP-C 60 . Our excited-state electron–nuclear dynamics calculations show that qHP-C 60 is extremely unique and enable exploration of time-resolved dynamics for understanding excited-state processes of large systems in complex, solvated environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoscale simulation of the thylakoid membrane response to extreme temperatures

Abstract The thylakoid membrane is in a temperature‐sensitive equilibrium that shifts repeatedly during the life cycle in response to ambient temperature or solar irradiance. Plants respond to seasonal temperature variation by changing their thylakoid lipid composition, while a more rapid mechanism for short‐term heat exposure is required. The emission of the small organic molecule isoprene has been postulated as one such possible rapid mechanism. The protective mechanism of isoprene is unknown, but some plants emit isoprene at high temperature. We investigate the dynamics and structure for lipids within a thylakoid membrane across temperatures and varied isoprene content using classical molecular dynamics simulations. The results are compared with experimental findings for temperature‐dependent changes in the lipid composition and shape of thylakoids. The surface area, volume, and flexibility of the membrane, as well as the lipid diffusion, increase with temperature, while the membrane thickness decreases. Saturated thylakoid 34:3 glycolipids derived from eukaryotic synthesis pathways exhibit altered dynamics relative to lipids from prokaryotic synthesis paths, which could explain the upregulation of specific lipid synthesis pathways at different temperatures. Increasing isoprene concentration was not observed to have a significant thermoprotective effect on the thylakoid membranes, and that isoprene readily permeated the membrane models tested.

59 BASIC BIOLOGICAL SCIENCES↗

Phase diagram of the TIP4P/Ice water model by enhanced sampling simulations

In this work, we studied the phase diagram for the TIP4P/Ice water model using enhanced sampling molecular dynamics simulations. Our approach is based on the calculation of ice–liquid free energy differences from biased coexistence simulations that reversibly sample the melting and growth of layers of ice. We computed a total of 19 melting points for five different ice polymorphs, which are in excellent agreement with the melting lines obtained from the integration of the Clausius–Clapeyron equation. For proton-ordered and fully proton-disordered ice phases, the results are in very good agreement with previous calculations based on thermodynamic integration. For the partially proton-disordered ice III, we find a large increase in stability that is in line with previous observations using direct coexistence simulations for the TIP4P/2005 model. This issue highlights the robustness of the approach employed here for ice polymorphs with diverse degrees of proton disorder. Our approach is general and can be applied to the calculation of other complex phase diagrams.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atomistic simulations to reveal HIP-bonding mechanisms of Al6061/Al6061

Molecular dynamics simulations were employed to understand the diffusion bonding process during hot isostatic pressing (HIP) of Al6061/Al6061 alloy. Simulations of the HIP process reveal atomistic phenomena that are difficult or unlikely to be observed experimentally and provide useful insights into the mechanism of diffusion and bonding. Here, the results reveal that at the start of the HIP process, a massive incursion of oxygen atoms occurs from the pre-existing γ-Al 2 O 3 to the 6061 region across the interphase interface. These oxygen atoms interact with the enriched Mg atom layer present at the existing γ-Al 2 O 3 and 6061 matrix to form a secondary complex Mg 2 Al 2 O 5 phase. Diffusion calculations also show that transport of atoms due to the applied pressure is 4–5 orders of magnitude higher than would occur in the absence of HIP conditions. The Mg 2 Al 2 O 5 phase also provides efficient pathways for the rapid transport of Mg atoms. Because of the higher diffusion coefficients observed for Mg within the phase, Mg atoms can move more swiftly compared to their diffusion within other phases such as γ-Al 2 O 3 . This accelerated mobility facilitates the rapid movement of Mg atoms across the interface, leading to changes in the local composition and the potential growth of the Mg 2 Al 2 O 5 phase.

36 MATERIALS SCIENCE↗

Double Paddle‐Wheel Enhanced Sodium Ion Conduction in an Antiperovskite Solid Electrolyte

Abstract Antiperovskite structure compounds (X 3 AB, where X is an alkali cation and A and B are anions) have the potential for highly correlated motion between the cation and a cluster anion on the A or B site. This so‐called “paddle‐wheel” mechanism may be the basis for enhanced cation mobility in solid electrolytes. Through combined experiments and modeling, the first instance of a double paddle‐wheel mechanism, leading to fast sodium ion conduction in the antiperovskite Na 3− x O 1− x (NH 2 ) x (BH 4 ), is shown. As the concentration of amide (NH 2 − ) cluster anions is increased, large positive deviations in ionic conductivity above that predicted from a vacancy diffusion model are observed. Using electrochemical impedance spectroscopy, powder X‐ray diffraction, synchrotron X‐ray diffraction, neutron diffraction, ab initio molecular dynamics simulations, and NMR, the cluster anion rotational dynamics are characterized and it is found that cation mobility is influenced by the rotation of both NH 2 − and BH 4 − species, resulting in sodium ion conductivity a factor of 10 2 higher at x = 1 than expected for the vacancy mechanism alone. Generalization of this phenomenon to other compounds could accelerate fast ion conductor exploration and design.

25 ENERGY STORAGE↗

Clustering Effects on the Structure of Ionomer Solutions: A Combined SANS and Simulations Study

Ionic assemblies, or clusters, determine the structure and dynamics of ionizable polymers and enable their many applications. Fundamental to attaining well-defined materials is controlling the balance between van der Waals interactions that govern the backbone behavior and the forces that drive the formation of ionic clusters. Here, using small angle neutron scattering and fully atomistic molecular dynamics simulations, the structure of a model ionomer, sulfonated polystyrene in toluene solutions, was investigated as the cluster cohesion was tweaked by the addition of ethanol. The static structure factor was measured by both techniques and correlated with the size of the ionic clusters as the polymer concentration was varied. The conjunction of SANS results and molecular insight from MD simulations enabled the determination of the structure in these inhomogeneous networks on multiple length scales. Additionally, we find that across the entire concentration range studied, a network driven by the formation of ionic clusters was formed, where the size of the clusters drives the inhomogeneity of these systems. Tweaking the ionic clusters through the addition of ethanol impacts the packing of the sulfonated groups, their shape, and their size distribution, which in turn, affects the structure of these networks.

36 MATERIALS SCIENCE↗

Investigating Morphology and Diffusion in Simulations of Precise Anion-Conducting Polymers

Using atomistic molecular dynamics simulations, we investigate the morphology and transport properties of a new class of polymers which are functionalized with quaternary ammonium groups for use as anion exchange membranes. The polymers are precision polyolefins with either a trimethylammonium (p5CNMe3) or a dimethyl-hexyl ammonium (p5CNMe2Hx) pendant group at every fifth carbon along a polyethylene backbone. Simulations are performed at hydration levels of 5, 10, 15, and 20 water molecules per ammonium group. The hydrated polymers form nanoscale, percolated hydrophilic domains (water channels) in the hydrophobic polymer matrix that become wider with increasing water content. Water and hydroxide anion diffusion coefficients also increase with increasing water content. The morphology of the water domains is similar in both polymers, while the diffusion coefficients are somewhat lower in p5CNMe2Hx at fixed water content. Furthermore, the diffusion coefficients in both polymers fall on the same curve as a function of the fractal dimension of the percolated water channels, which appears to be a useful scalar measure of the effects of the nanoscale morphology on water and hydroxide anion transport.

Anion exchange membrane↗

Dynamics of poly[n]catenane melts

Inspired by advances in the chemical synthesis of interlocking polymer architectures, extensive molecular dynamics simulations have been conducted to study the dynamical properties of poly[n]catenanes-polymers composed entirely of interlocking rings-in the melt state. Both the degree of polymerization (number of links) and the number of beads per ring are systematically varied, and the results are compared to linear and ring polymers. Herein, a simple Rouse-like model is presented, and its analytical solution suggests a decomposition of the dynamics into "ring-like" and "linear-like" regimes at short and long times, respectively. In agreement with this picture, multiple sub-diffusive regimes are observed in the monomer mean-squared-displacements even though interchain entanglement is not prevalent in the system. However, the Rouse-type model does not account for the topological effects of the mechanical bonds, which significantly alter the dynamics at intermediate length scales both within the rings and at the chain segment scales. The stress relaxation in the system is extremely rapid and may be conveniently separated into ring-like and linear-like contributions, again in agreement with the Rouse picture. However, the viscosity has a non-monotonic dependence on the ring size for long chains, which disagrees strongly with theoretical predictions. This unexpected observation cannot be explained in terms of chain disentanglement and is inconsistent with other measures of polymer relaxation. Possible mechanisms for this behavior are proposed and implications for materials design are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient simulation of optical spectra via machine learning and physical decomposition of environmental effects

Simulations of optical spectra can provide key insights to aid experimental interpretation of electronic excitation phenomena. For chromophores in the condensed phase, these spectra, which incorporate the coupling between electronic excitation and molecular and solvent nuclear motions, can be simulated using excitation energies obtained from molecular dynamics simulations of the chromophore and solvent. Here, we present a hybrid scheme that exploits machine learning and physically informed spectral densities to show that as few as 25 ground and excited state energetic gradient calculations can be used to construct models that accurately predict environment-influenced vibronic coupling in optical spectra. We demonstrate our approach for the green fluorescent protein chromophore in water and the cresyl violet chromophore in methanol. We show that our hybrid approach, employing a machine learning model for the high-frequency spectral density and an ab initio parameterized Debye spectral density for the low-frequency, results in a systematic improvement of the optical absorption lineshape, leading to a simple machine learning scheme that can be used for the simulation of spectral densities and optical spectra.

Snider, Andrew [Univ. of California, Merced, CA (U↗

Bridging microscopic dynamics and rheology in the yielding of charged colloidal suspensions

The yielding of soft materials is critical to many natural and industrial processes, yet experimental insights into microscopic aspects of yielding are limited. This study combines angle X-ray scattering, X-ray photon correlation spectroscopy, and in situ rheology (Rheo-SAXS-XPCS) with fast lubrication dynamics simulations to examine how interparticle interactions influence yielding in charged colloidal suspensions. By tuning attraction through salt addition, we compare repulsive and attractive systems under deformation. Repulsive suspensions yield uniformly with Andrade-like creep and minimal structural change. In contrast, attractive suspensions show complex behaviors, including shear banding, delayed yielding, and resolidification, governed by transient dynamics at shear band interfaces. These results directly link microscopic particle dynamics to macroscopic flow and demonstrate how interaction potentials control rheological behavior. This work offers a framework for designing soft materials with tailored properties for applications in coatings, food processing, drug delivery, and other technologies requiring precise mechanical control.

Molecular Dynamics Simulation↗

Continuous and discontinuous transitions in the depinning of two-dimensional dusty plasmas on a one-dimensional periodic substrate

We report Langevin dynamical simulations are performed to study the depinning dynamics of two-dimensional dusty plasmas on a one-dimensional periodic substrate. From the diagnostics of the sixfold coordinated particles P 6 and the collective drift velocity V x , three different states appear, which are the pinning, disordered plastic flow, and moving ordered states. It is found that the depth of the substrate is able to modulate the properties of the depinning phase transition, based on the results of P 6 and V x , as well as the observation of hysteresis of V x while increasing and decreasing the driving force monotonically. When the depth of the substrate is shallow, there are two continuous phase transitions. When the potential well depth slightly increases, the phase transition from the pinned to the disordered plastic flow states is continuous; however, the phase transition from the disordered plastic flow to the moving ordered states is discontinuous. When the substrate is even deeper, the phase transition from the pinned to the disordered plastic flow states changes to discontinuous. When the depth of the substrate further increases, as the driving force increases, the pinned state changes to the moving ordered state directly, so that the disordered plastic flow state disappears completely.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Subharmonic Shapiro steps in depinning dynamics of a two-dimensional solid dusty plasma modulated by one-dimensional nonlinear deformed periodic substrates

Langevin dynamical simulations are performed to investigate the depinning dynamics of a two-dimensional (2D) solid dusty plasma, which is modulated by one-dimensional (1D) nonlinear deformed periodic substrates, and also driven by the combination of the DC and AC forces. As the DC driving force increases gradually, pronounced subharmonic and harmonic Shapiro steps are discovered under the combined modulation of the deformed substrate and the external AC drive. Here, these observed subharmonic and harmonic Shapiro steps are attributed to the dynamic mode locking. The data analysis results indicate that the nonlinear deformed substrate strongly influences these subharmonic Shapiro steps, which can be accurately diagnosed using the fraction of sixfold coordinated particles. Furthermore, the diagnostic of the kinetic temperature clearly indicates the difference between harmonic and subharmonic Shapiro steps, i.e., the particle motion is slightly less synchronized at subharmonic Shapiro steps, caused by the unstable locations of the deformed substrate.

36 MATERIALS SCIENCE↗

Toward wide-spectrum antivirals against coronaviruses: Molecular characterization of SARS-CoV-2 NSP13 helicase inhibitors

To date, effective therapeutic treatments that confer strong attenuation against coronaviruses (CoVs) remain elusive. Among potential drug targets, the helicase of CoVs is attractive due to its sequence conservation and indispensability. We rely on atomistic molecular dynamics simulations to explore the structural coordination and dynamics associated with the SARS-CoV-2 Nsp13 apo enzyme, as well as their complexes with natural ligands. A complex communication network is revealed among the five domains of Nsp13, which is differentially activated because of the presence of the ligands, as shown by shear strain analysis, principal components analysis, dynamical cross-correlation matrix analysis, and water transport analysis. The binding free energy and the corresponding mechanism of action are presented for three small molecules that were shown to be efficient inhibitors of the previous SARS-CoV Nsp13 enzyme. Together, our findings provide critical fresh insights for rational design of broad-spectrum antivirals against CoVs.

59 BASIC BIOLOGICAL SCIENCES↗