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At least 415 records · Page 23

Iron Dissolution from Goethite (alpha-FeOOH) Surfaces in Water by Ab Initio Enhanced Free-Energy Simulations

Dissolution of redox-active metal oxides plays a key role in a variety of phenomena, including (photo)electrocatalysis, degradation of battery materials, corrosion of metal oxides, and biogeochemical cycling of metals in natural environments. Despite its widespread significance, mechanisms of metal-oxide dissolution remain poorly understood on the atomistic level. This study is aimed at elucidating the long-standing problem of iron dissolution from Fe(III)-oxide, a complex process involving coupled hydrolysis, surface protonation, electron transfer, and metal oxygen bond cleavage. We examine the case of goethite (alpha-FeOOH), a representative phase, bearing structural similarities with many other metal (hydr)oxides. By employing quantum molecular dynamics simulations (metadynamics combined with the Blue Moon ensemble approach), we unveil the mechanistic pathways and rates of both nonreductive and reductive dissolution of iron from the (110) and (021) goethite facets in aqueous solutions at room temperature. Our simulations reveal the interplay between concerted internal (structural) and external (from solution) protonations as essential for breaking Fe-O bonds as well as for stabilizing intermediate configurations of dissolving Fe. We demonstrate specifically how Fe(III) reduction to Fe(II) yields higher dissolution rates than the proton-mediated pathway, whereas the most rapid dissolution is expected for these two processes combined, in agreement with experiments.

Klyukin, Konstantin↗

Protein–Mineral Interactions: Molecular Dynamics Simulations Capture Importance of Variations in Mineral Surface Composition and Structure

Molecular dynamics simulations, conventional and metadynamics, were performed to determine the interaction of model protein Gb1 over kaolinite (001), Na+-montmorillonite (001), Ca2+-montmorillonite (001), goethite (100), and Na+-birnessite (001) mineral surfaces. Gb1, a small (56 residue) protein with a well-characterized solution-state nuclear magnetic resonance (NMR) structure and having α-helix, four-fold β-sheet, and hydrophobic core features, is used as a model protein to study protein soil mineral interactions and gain insights on structural changes and potential degradation of protein. From our simulations, we observe little change to the hydrated Gb1 structure over the kaolinite, montmorillonite, and goethite surfaces relative to its solvated structure without these mineral surfaces present. Over the Na+-birnessite basal surface, however, the Gb1 structure is highly disturbed as a result of interaction with this birnessite surface. Unraveling of the Gb1 β-sheet at specific turns and a partial unraveling of the α-helix is observed over birnessite, which suggests specific vulnerable residue sites for oxidation or hydrolysis possibly leading to fragmentation.

Environmental Molecular Sciences Laboratory↗

Energetics and the Role of Defects in Fe(II)-Catalyzed Goethite Recrystallization from Molecular Simulations

Goethite is one of the most stable and common iron (III) minerals at the Earth’s near surface. However, recent isotope- tracer studies suggest that goethite continuously recrystallizes in the presence of aqueous Fe(II) ions. Such studies often indicate the presence of two regimes of atom exchange kinetics, a rapid stage assigned to reactive defect sites initially available at particle surfaces, followed by slower continuous exchange. An autocatalytic solid-state electron conduction model coupling Fe(II) oxidative adsorption to its reductive release at spatially distinct sites has been proposed, but the thermodynamic driving force has yet to be pinpointed. Here, using a novel hybrid/reactive molecular simulation method, for goethite (110) surfaces at circumneutral pH, we rigorously tested whether surface free energy minimization, including examining the role of structural defects, is sufficient to overcome the activation energy for interfacial electron transfer and conduction. The simulations quantitatively show that: (i). on smooth stable surfaces the available thermal energy at dynamic equilibrium is sufficient to sustain the slow continuous regime of atom exchange kinetics via short intra-surface electron conduction pathways of 1-2 nm (3-5 Fe site hops); (ii). in this slower regime, the model converges to atom exchange kinetics of 10 -5 Fe s -1 cm -2 , a rate recently deduced from stochastic modeling of experimental data and linked to the reductive dissolution rate of goethite; (iii). the driving force for initially rough defective goethite surfaces to smoothen can accelerate atom exchange to an extent quantitatively consistent with that observed in the initial rapid stage, in this case accessing conduction pathways of up to 8 nm. The findings suggest that the interaction of Fe(II) with initially defective goethite surfaces can drive, by the conduction model, atom exchange that is capable of recrystallizing the interiors of nanoscale particles, and that, closer to equilibrium on smooth surfaces, slower atom exchange continues in perpetuity but likely involving only the outermost atomic layers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks

Zr-based metal organic frameworks (MOFs) have been recently shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. We report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination of DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. These experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulations of Cyclic Voltammetry for Electric Double Layers in Asymmetric Electrolytes: A Generalized Modified Poisson-Nernst-Planck Model

This paper presents a generalized modified Poisson–Nernst–Planck (MPNP) model derived from first principles based on excess chemical potential and Langmuir activity coefficient to simulate electric double-layer dynamics in asymmetric electrolytes. The model accounts simultaneously for (1) asymmetric electrolytes with (2) multiple ion species, (3) finite ion sizes, and (4) Stern and diffuse layers along with Ohmic potential drop in the electrode. It was used to simulate cyclic voltammetry (CV) measurements for binary asymmetric electrolytes. The results demonstrated that the current density increased significantly with decreasing ion diameter and/or increasing valency |z i | of either ion species. By contrast, the ion diffusion coefficients affected the CV curves and capacitance only at large scan rates. Dimensional analysis was also performed, and 11 dimensionless numbers were identified to govern the CV measurements of the electric double layer in binary asymmetric electrolytes between two identical planar electrodes of finite thickness. A self-similar behavior was identified for the electric double-layer integral capacitance estimated from CV measurement simulations. Two regimes were identified by comparing the half cycle period τ CV and the “RC time scale” τ RC corresponding to the characteristic time of ions’ electrodiffusion. For τ RC ← τ CV , quasi-equilibrium conditions prevailed and the capacitance was diffusion-independent while for τ RC → τ CV , the capacitance was diffusion-limited. The effect of the electrode was captured by the dimensionless electrode electrical conductivity representing the ratio of characteristic times associated with charge transport in the electrolyte and that in the electrode. The model developed here will be useful for simulating and designing various practical electrochemical, colloidal, and biological systems for a wide range of applications.

Wang, Hainan↗

Aggregation of cyclic polypeptoids bearing zwitterionic end-groups with attractive dipole–dipole and solvophobic interactions: a study by small-angle neutron scattering and molecular dynamics simulation

Aggregation behavior of cyclic polypeptoids bearing zwitterionic end-groups in methanol has been studied using a combination of experimental and simulation techniques. Here, the data from SANS and cryo-TEM indicate that the solution contains small clusters of these cyclic polypeptoids, ranging from a single polypeptoid chain to small oligomers, while the linear counterpart shows no cluster formation. Atomistic molecular dynamics simulations reveal that the driving force for this clustering behavior is due to the interplay between the effective repulsion due to the solvation of the dipoles formed by the charged end-groups in each polypeptoid chain and the attractive forces due to dipole–dipole interactions and the solvophobic effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Verification of a Monte Carlo binary collision model for simulating elastic and inelastic collisions in particle-in-cell simulations

We present the development and verification of a Monte Carlo binary collision model for simulating elastic and inelastic collisions in particle-in-cell simulations. We apply the corrected binary collision model originally developed for charged-particles collisions to all considered scattering channels, including Coulomb collisions, elastic neutral–neutral and charged–neutral collisions, ionization, excitation, and fusion. The model's implementation is described and verified through a series of simulations, including charged- and neutral-particle thermal equilibration, slowing of electrons in warm solid-density aluminum, collisional damping of a Langmuir wave, helium gas breakdown in an applied electric field, and thermonuclear and beam–target fusion. Then, we demonstrate the model within simulations of hydrogen plasma formation in the Princeton Field-Reversed Configuration as well as of the burning of aneutronic fusion fuel p-11B. The latter includes measurement of the fusion power density in a low-density plasma and fusion production due to the stopping of a proton ignitor beam in a compressed boron target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Insights into the structure and dynamics of K + ions at the muscovite–water interface from machine learning potential simulations

The surfaces of many minerals are covered by naturally occurring cations that become partially hydrated and can be replaced by hydronium or other cations when the surface is exposed to water or an aqueous solution. These ion exchange processes are relevant to various chemical and transport phenomena, yet elucidating their microscopic details is challenging for both experiments and simulations. Here, in this work, we make a first step in this direction by investigating the behavior of the native K + ions at the interface between neat water and the muscovite mica (001) surface with ab-initio -based machine learning molecular dynamics and enhanced sampling simulations. Our results show that the desorption of the surface K + ions in pure ion-free water has a significant free energy barrier irrespective of their local surface arrangement. In contrast, facile K + diffusion between mica’s ditrigonal cavities characterized by different Al/Si orderings is observed. This behavior suggests that the K + ions may favor a dynamic disordered surface arrangement rather than complete desorption when exposed to deionized water.

Ab-initio molecular dynamics↗

Heterogeneous energetic material damage simulator (HEDS): A deep learning approach to simulate damage–sensitivity linkages

Damage in the microstructures of energetic materials (EMs), such as propellants and plastic bonded explosives (PBXs), can significantly alter their response to external loads. Both sensitization and desensitization can occur, causing concerns with safety and performance in the field; predictive models that connect damage and the sensitivity of EMs can enable design and provide confidence in their robustness and reliability. However, modeling of damage evolution is challenging for real microstructures of EMs; samples of damaged EMs are difficult to obtain, thereby hindering experiments and direct numerical simulations to determine the sensitivity of EMs at various stages of damage. Here, we develop an approach to generate synthetic, i.e., in silico produced, damaged microstructures for use in simulations to connect damage levels to sensitivity. The development of the present workflow to generate and impose varying levels of damage in microstructures, known as HEDS (Heterogeneous Energetic Material Damage Simulator), begins with a small set of images of damaged PBXs and combines a collection of deep neural network techniques to generate microstructures with varying levels of damage. By making the synthetic microstructures conform closely to those observed in available real, imaged microstructures, we develop an ensemble of damaged microstructures that can be used for in silico shock experiments. HEDS develops these microstructure ensembles as level set fields, which are directly employed in a sharp interface Eulerian hydrocode where shock simulations are performed to quantify the energy release rate from hotspot fields generated in the microstructure. These capabilities can be useful for the analysis and assessment of changes in the sensitivity of EMs and to design formulations that are less susceptible to damage-induced changes in sensitivity and performance.

Fang, Irene (ORCID:0009000844557122)↗

Quantum simulator of an open quantum system using superconducting qubits: exciton transport in photosynthetic complexes

Open quantum system approaches are widely used in the description of physical, chemical and biological systems. A famous example is electronic excitation transfer in the initial stage of photosynthesis, where harvested energy is transferred with remarkably high efficiency to a reaction center. This transport is affected by the motion of a structured vibrational environment, which makes simulations on a classical computer very demanding. Here we propose an analog quantum simulator of complex open system dynamics with a precisely engineered quantum environment. Our setup is based on superconducting circuits, a well established technology. As an example, we demonstrate that it is feasible to simulate exciton transport in the Fenna–Matthews–Olson photosynthetic complex. Our approach allows for a controllable single-molecule simulation and the investigation of energy transfer pathways as well as non-Markovian noise-correlation effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Wind Farm Simulation and Layout Optimization in Complex Terrain: Preprint

This work reports on incorporating complex terrain into wind farm simulations for the purpose of layout optimization. Adding complex terrain boundary conditions to NREL's medium fidelity computational fluid dynamics model, WindSE, produces significant separation, flow curvature, and speedup effects that would otherwise be difficult to capture with lower-fidelity models or a flat-terrain assumption. These flow features, in turn, can significantly impact the optimal turbine array layout. We demonstrate the impact of complex terrain on flow in both an idealized and real-world setting, and discuss modifications to the code that enable gradient-based optimization using terrain-aware adjoint gradients. Through several optimization case studies, we show that the layout optimization process takes advantage of speedup effects on terrain high points, and leverages flow curvature effects that modify wake trajectories. This yields substantial power improvements over gridded layouts, and hints at future research directions in simulation and optimization for wake trajectories in complex terrain.

17 WIND ENERGY↗

Two-dimensional implosion simulations with a kinetic particle code [2D implosion simulations with a kinetic particle code]

Here, we perform two-dimensional implosion simulations using a Monte Carlo kinetic particle code. The application of a kinetic transport code is motivated, in part, by the occurrence of nonequilibrium effects in inertial confinement fusion capsule implosions, which cannot be fully captured by hydrodynamic simulations. Kinetic methods, on the other hand, are able to describe both continuum and rarefied flows. We perform simple two-dimensional disk implosion simulations using one-particle species and compare the results to simulations with the hydrodynamics code rage. The impact of the particle mean free path on the implosion is also explored. In a second study, we focus on the formation of fluid instabilities from induced perturbations. We find good agreement with hydrodynamic studies regarding the location of the shock and the implosion dynamics. Differences are found in the evolution of fluid instabilities, originating from the higher resolution of rage and statistical noise in the kinetic studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Transformational Regional-Scale Earthquake Simulations with the DOE EarthQuake SIMulation Exascale Framework

Earthquakes present worldwide risk to economic and human safety. The 2023 earthquakes in Turkiye provided a reminder of the potential for catastrophic consequences with 50,700 deaths and 15.7 million people affected. The ability to predict ground motions and infrastructure damage for earthquakes continues to be a challenging problem for scientists and engineers. Until now, estimates of ground motions have been performed empirically by looking at sparse data from past earthquakes. This approach can provide statistical information on intensity amplitudes but cannot inform site-specific ground motions essential to developing the most effective resilience. Interest has grown in large-scale computational models to simulate earthquakes at regional scale. The U.S. Department of Energy EarthQuake SIMulation (EQSIM) framework was developed for regional-scale earthquake simulations at unprecedented fidelity, taking advantage of emerging GPU-accelerated systems. This article describes the EQSIM workflow and demonstrates regional-scale simulations with the new computational capability available to scientists in their quest to mitigate future disasters.

58 GEOSCIENCES↗

Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations

Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.

Du, Jincheng↗

Modification of the TASMIP x-ray spectral model for the simulation of microfocus x-ray sources

Purpose: The availability of accurate and simple models for the estimation of x-ray spectra is of great importance for system simulation, optimization, or inclusion of photon energy information into data processing. There is a variety of publicly available tools for estimation of x-ray spectra in radiology and mammography. However, most of these models cannot be used directly for modeling microfocus x-ray sources due to differences in inherent filtration, energy range and/or anode material. For this reason the authors propose in this work a new model for the simulation of microfocus spectra based on existing models for mammography and radiology, modified to compensate for the effects of inherent filtration and energy range. Methods: The authors used the radiology and mammography versions of an existing empirical model [tungsten anode spectral model interpolating polynomials (TASMIP)] as the basis of the microfocus model. First, the authors estimated the inherent filtration included in the radiology model by comparing the shape of the spectra with spectra from the mammography model. Afterwards, the authors built a unified spectra dataset by combining both models and, finally, they estimated the parameters of the new version of TASMIP for microfocus sources by calibrating against experimental exposure data from a microfocus x-ray source. The model was validated by comparing estimated and experimental exposure and attenuation data for different attenuating materials and x-ray beam peak energy values, using two different x-ray tubes. Results: Inherent filtration for the radiology spectra from TASMIP was found to be equivalent to 1.68 mm Al, as compared to spectra obtained from the mammography model. To match the experimentally measured exposure data the combined dataset required to apply a negative filtration of about 0.21 mm Al and an anode roughness of 0.003 mm W. The validation of the model against real acquired data showed errors in exposure and attenuation in line with those reported for other models for radiology or mammography. Conclusions: A new version of the TASMIP model for the estimation of x-ray spectra in microfocus x-ray sources has been developed and validated experimentally. Similarly to other versions of TASMIP, the estimation of spectra is very simple, involving only the evaluation of polynomial expressions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The Pele Simulation Suite for Reacting Flows at Exascale

In this work, we present the Pele suite of software tools for compressible and incompressible reacting flows. The Pele suite leverages several different libraries, notably AMReX and SUNDIALS, to achieve performance portability on heterogeneous computing architectures across the supercomputing landscape. The Pele suite is comprised of PeleC, a compressible reacting flow block-structured adaptive mesh refinement solver, PeleLMeX, a low-Mach number reacting flow block-structured adaptive mesh refinement solver, Pele-Physics, a library for transport, thermodynamics, finite rate chemistry, soot, spray and radiation physics. The objective of this paper is (i) to present the code development efforts necessary to achieve highly effective and scalable applications for exascale machines and (ii) to detail the performance results of the Combustion-Pele project applications on Oak Ridge National Laboratory's Frontier. We show good weak and strong scaling results for both PeleC and PeleLMeX up to more than 50 billion cells on more than 4096 Frontier graphics processing unit nodes. We also present a capability demonstration simulation of a dual-fuel pulse compression ignition engine (six adaptive mesh refinement levels, and 60 billion cells or 2.1 trillion degrees of freedom) on Frontier, to date one of the largest simulations performed on the first exascale-class supercomputer.

adaptive mesh refinement↗