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At least 145 records · Page 8

Coarse-Graining Conformational Dynamics with Multidimensional Generalized Langevin Equation: How, When, and Why

A data-driven ab initio generalized Langevin equation (AIGLE) approach is developed to learn and simulate high-dimensional, heterogeneous, coarse-grained (CG) conformational dynamics. Constrained by the fluctuation–dissipation theorem, the approach can build CG models in dynamical consistency (DC) with all-atom molecular dynamics. Here, we also propose practical criteria for AIGLE to enforce long-term DC. Case studies of a toy polymer, with 20 CG sites, and the alanine dipeptide, with two dihedral angles, elucidate why one should adopt AIGLE or its Markovian limit for modeling CG conformational dynamics in practice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Disordering and H-embrittlement of Pb(110) surface using embedded atom method and molecular dynamics

The dynamics and structure of the crystal melt interface are of great importance in crystal growth, melting, and other properties of the solid-liquid interface. The Embedded Atom Method (EAM), a semiempirical method developed by Daw and Baskes for determining the energetics of atoms in a bulk environment, is a useful method in the computer simulation. The EAM functions of PB in conjunction with the MD code are employed to study melting and disordering of the Pb(100) surface. The EAM functions are fitted to the bulk experimental data at zero temperature, and it is not clear if it will behave correctly at higher temperatures. In fact, it is shown that use of a similar type of potential at higher temperatures might result in a negative coefficient of thermal expansion. The primary purpose here is to perform MD simulation combined with the EAM functions of PB to study melting of the Pb(100) surface. This provides an accurate test of the EAM functions at higher temperatures. In particular, we calculate the two dimensional structure factor, the two dimensional distribution function, and density profile as a function of temperature up to the melting point of lead.

Karimi, Majid↗

Temperature Dependent Local Atomic Structure and Vibrational Dynamics of Barium Hydride and Calcium Hydride

Solid-state ionic conductors that exhibit pure ionic transport of hydride anions are rare. Here, we investigate two alkaline earth metal hydrides, barium hydride and calcium hydride, using neutron scattering techniques to understand how the local atomic environment plays a role in the diffusion of hydride ions. At high temperatures, barium hydride exhibits exceptional transport properties with ionic conductivities that are higher than those of many of the typical proton and oxide ion conductors in use today. Total neutron scattering and pair distribution function analysis reveal how a structural phase transition converts barium hydride from a modest ionic conductor into a fast ionic conductor through the introduction of disorder, deuterium site splitting, and dynamic structural fluctuations. Furthermore, neutron vibrational spectroscopy is employed to probe changes in the temperature evolution of the lattice dynamics and local energy landscape. These results improve our fundamental knowledge of the interplay between structure and dynamics governing a rare conduction process of hydride ions in solid-state materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reinforcement learning based hybrid bond-order coarse-grained interatomic potentials for exploring mesoscale aggregation in liquid–liquid mixtures

Exploring mesoscopic physical phenomena has always been a challenge for brute-force all-atom molecular dynamics simulations. Although recent advances in computing hardware have improved the accessible length scales, reaching mesoscopic timescales is still a significant bottleneck. Coarse-graining of all-atom models allows robust investigation of mesoscale physics with a reduced spatial and temporal resolution but preserves desired structural features of molecules, unlike continuum-based methods. Here, we present a hybrid bond-order coarse-grained forcefield (HyCG) for modeling mesoscale aggregation phenomena in liquid–liquid mixtures. The intuitive hybrid functional form of the potential offers interpretability to our model, unlike many machine learning based interatomic potentials. We parameterize the potential with the continuous action Monte Carlo Tree Search (cMCTS) algorithm, a reinforcement learning (RL) based global optimizing scheme, using training data from all-atom simulations. The resulting RL-HyCG correctly describes mesoscale critical fluctuations in binary liquid–liquid extraction systems. cMCTS, the RL algorithm, accurately captures the mean behavior of various geometrical properties of the molecule of interest, which were excluded from the training set. The developed potential model along with the RL-based training workflow could be applied to explore a variety of other mesoscale physical phenomena that are typically inaccessible to all-atom molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct Observation and Analysis of Low-Energy Magnons with Raman Spectroscopy in Atomically Thin NiPS 3

van der Waals (vdW) magnets have rapidly emerged as a fertile playground for fundamental physics and exciting applications. Despite the impressive developments over the past few years, technical limitations pose a severe challenge to many other potential breakthroughs. High on the list is the lack of suitable experimental tools for studying spin dynamics on atomically thin samples. Here, Raman scattering techniques are employed to directly observe the low-lying magnon (~1 meV) even in bilayer NiPS 3 . Further, the advantage is that it offers excellent energy resolutions far better on low-energy sides than most inelastic neutron spectrometers can offer. More importantly, with appropriate theoretical analysis, the polarization dependence of the Raman scattering by those low-lying magnons also provides otherwise hidden information on the dominant spin-exchange scattering paths for different magnons. By comparing with high-resolution inelastic neutron scattering data, these low-energy Raman modes are confirmed to be indeed of magnon origin. Because of the different scattering mechanisms involved in inelastic neutron and Raman scattering, this information is fundamental in pinning down the final spin Hamiltonian. This work demonstrates the capability of Raman spectroscopy to probe the genuine two-dimensional spin dynamics in atomically thin vdW magnets, which can provide insights that are obscured in bulk spin dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular-Level Insights into the Influence of Ionic Liquids on the Structure and Dynamics of Neutral and Charged Polyimides

We use all-atom molecular dynamics simulations to investigate how increasing ionic functionalization influences polyimide (PI) behavior in ionic liquid (IL) solvation environments. Here, we examine three polymer systems with varying charge densities: a neutral polyimide [N−PI] containing imidazole rings and progressively introduce charge through quaternization to create singly [C−PI] + and doubly charged [C−2PI] 2+ variants across a wide range of IL concentration (0−90 wt %). Through comprehensive structural, mechanical, and electrostatic analyses, we reveal that polymer charge density plays a central role in shaping IL organization and interaction with the polymer matrix. At low IL content, charged systems exhibit strong electrostatic complexation, leading to chain compaction, localized ESP environments, and elevated dielectric constants. As IL concentration increases, the effect of the different polymer charge states becomes less significant. Notably, an intermediate composition regime at approximately 50 wt % IL is associated with changes in IL-rich domain connectivity and overall system behavior across all three PI systems.

36 MATERIALS SCIENCE↗

Ab Initio Bulk Free Energy Surface of Proper Ferroelectrics

We report a systematic and accurate approach for deriving the bulk free energy surface (FES), a function of temperature, polarization, and strain, from the first-principles density functional theory (DFT) of proper ferroelectrics. The core of our approach is the metadynamics algorithm that extracts the polarization dependence of the FES from all-atom molecular dynamics simulations without an a priori ansatz. The rest of the FES is derived from the metadynamics trajectories that span the relevant phase space. We demonstrate our approach in the case of lead titanate. The errors across the phase transition, due to DFT numerics, all-atom molecular dynamics, and free energy evaluation by enhanced sampling, can be systematically controlled and are of the order of 1 meV/atom. The accuracy of the resulting ab initio FES is only limited by the adopted functional approximation of DFT.

Xie, Pinchen [Lawrence Berkeley National Laborator↗

Roadmap on multiscale materials modeling

Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware.

36 MATERIALS SCIENCE↗

Atomic force microscopy phase imaging of epitaxial graphene films

Abstract Dynamic mode atomic force microscopy phase imaging is known to produce distinct contrast between graphene areas of different atomic thickness. But the intrinsic complexity of the processes controlling the tip motion and the phase angle shift excludes its use as an independent technique for a quantitative type of analysis. By investigating the relationship between the phase shift, the tip-surface interaction, and the thickness of the epitaxial graphene areas grown on silicon carbide, we shed light on the origin of such phase contrast, and on the complex energy dissipation processes underlying phase imaging. In particular, we study the behavior of phase shift and energy dissipation when imaging the interfacial buffer layer, single-layer, and bilayer graphene regions as a function of the tip-surface separation and the interaction forces. Finally, we compare these results with those obtained on differently-grown quasi free standing single- and bilayer graphene samples.

Lavini, Francesco (ORCID:0000000257223040)↗

Unexpected Observation of Disorder and Multiple Phase-Transition Pathways in Shock-Compressed Zr

The response of materials under dynamic compression involves a complex interplay of various deformation mechanisms aimed at relieving shear stresses, yielding a remarkable diversity in material behavior. Here, in this Letter, we utilize femtosecond x-ray diffraction coupled with nanosecond laser compression to reveal an intricate competition between multiple shear-relieving mechanisms within an elemental metal. Our observations in shocked-compressed single-crystal Zr indicate a disorder-mediated shear relaxation at lower pressures. Above the phase-transition pressure, we observe the increasing contribution of structural phase transition in relieving shear stress. We detect not one but three concurrent pathways during the transition from the hcp to a hex-3 structure. These complex dynamics are partially corroborated through multimillion-atom molecular dynamics simulations employing a machine-learned interatomic potential. Our observation of multiple concurrent pathways and disorder during shock compression underscore the far greater intricacies in the dynamic response of metals than previously assumed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Defect formation and bending properties in graphite under He atom implantation investigated by molecular dynamics method

The formation and evolution of radiation defects and their effects on bending property of a single graphite under low energy helium atom implantation have been studied at atomic scale through molecular dynamics simulations. Various simple interstitial and vacancy defects are observed during the implantation process, which is a function of incident energy and cross section of helium-carbon interaction. Large defects are observed after continuous helium atom implantations. The effects of incident energy on the density, size and distribution of defects are analyzed in detail. Furthermore, the kinetic evolution process of radiation defects at different annealing temperatures have also been simulated, including the migration, aggregation, transformation, coalescence, and self-healing. Here, the large defect clusters, crossing several carbon layers, have been confirmed to be the primary reasons that affect the bending property of graphite. All these results provide a new understanding for further applications of graphite in nuclear reactors.

Atomic implantation↗

Precision Local Burnup Assessment Through Dynamic Peak Fitting in Atom Probe Tomography for Depleted, Enriched, and Irradiated Metallic and Ceramic Fuels

Abstract Burnup estimation in nuclear fuels is vital for evaluating fuel performance, transportation, and safe fuel storage. Accurate assessments of burnup from service period and spent fuels involve tracking the consumption of fissile isotopes of uranium (U) offering a direct insight into energy changes within the fuels especially for thermal spectrum reactors. In current approach, mass spectroscopic technique in atom probe tomography (APT) is utilized for accurate quantification of U isotopes. Quantification of U peaks in mass spectrum is performed on asymmetric shapes due to delayed signals, known as thermal tails, particularly for poorly conducting samples analyzed in laser mode. In this study, we introduce a novel quantification tool for isotopic analysis from APT datasets by developing a fitting algorithm based on shapes of the peaks. A MATLAB-based dynamic peak fitting toolbox is developed and designed to adapt to various peak shapes, ensuring accurate quantification of U isotopes. The effectiveness of this approach is demonstrated in standard Ni-Cr sample, depleted and enriched U samples, and U-based fuels with different burnup levels. The viability of this approach for isotopic quantification is demonstrated on both metallic and ceramic fuels.

Burnup↗

Effect of Sulfonation Level on the Percolated Morphology and Proton Conductivity of Hydrated Fluorine-Free Copolymers: Experiments and Simulations

Using all-atom molecular dynamics simulations and a variety of experimental methods, we previously reported on a linear polyethylene with pendant phenyl sulfonated groups precisely on every fifth carbon along the backbone. With increasing relative humidity this fluorine-free polymer self-assembled to form nanoscale water channels and exhibited exceptional proton conductivity. Expanding upon those findings, here we explore partially sulfonated random copolymers, referred to as p 5PhSH-Y. Using either acetyl sulfate or sulfuric acid, a wide range of sulfonation levels were prepared ( Y = 34−98%) corresponding to ion-exchange capacities (IEC) of 2.0−4.4 mmol/g. Combining experimental techniques and all-atom molecular dynamics simulations, we study the effect of Y on water uptake, nanoscale morphology, and the proton/water transport properties of p5PhSH- Y . The proton conductivity of p 5PhSH- Y increases with relative humidity and with Y and achieves values in excess of 0.1 S/cm. These high conductivities are attributed to high IEC and welldeveloped nanoscale percolated hydrophilic domains made possible by the flexible backbone. We quantitatively describe the nature of the water channels using the characteristic distance, channel width distribution, the area per sulfonate group at the hydrophilic/ hydrophobic interface, and the fractal dimension. Notably, the channel widths and the areas per sulfonate group are nominally independent of the level of sulfonation, while depending significantly on the level of hydration. The fractal dimension of the water channels correlates strongly with the water diffusion coefficients calculated from the molecular dynamics (MD) simulations. These findings demonstrate that the p 5PhSH- Y hydrocarbon copolymers can be modified to tune properties, particularly proton conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Trifan, Anda↗

Lattice dynamics, sound velocities, and atomic environments of szomolnokite at high pressure

Complex mixtures of sulfates, silicates, and ice have been observed in a variety of planetary environments on Earth, Mars and the icy satellites of the solar system. Characterizing the properties of the corresponding compositional endmembers is important for understanding the interiors of a range of planetary bodies in which these phases are observed. To measure the electronic and vibrational properties of the pure ferrous iron endmember of the kieserite group, szomolnokite, (FeSO 4 ∙H 2 O), we have performed synchrotron 57 Fe nuclear resonant inelastic and forward scattering experiments in the diamond-anvil cell up to 14.5 GPa. This pressure range covers depths within Earth’s interior relevant to sulfur cycling in subduction zones and the range of pressures expected within icy satellite interiors. We find evidence of crystal lattice softening, changes in elastic properties, and changes in the electric field gradients of iron atoms associated with two structural transitions occurring within the experimental pressure range. Here we apply these findings to icy satellite interiors, including discussion of elastic properties, modeling of ice-sulfate aggregates, and implications for tidal observations.

58 GEOSCIENCES↗