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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ab Initio Molecular Dynamics Insights into Stress Corrosion Cracking and Dissolution of Metal Oxides

Oxide phases such as α-Fe2O3 (hematite) and α-Al2O3 (corundum) are highly insoluble in water; however, subcritical crack growth has been observed in humidity nonetheless. Chemically induced bond breaking at the crack tip appears unlikely due to sterically hindered molecular transport. The molecular mechanics of a crack in corundum with a reactive force field reveal minimal lattice trapping, leading to bond breaking before sufficient space opens for water transport. To address this, we model a pre-built blunt crack with space for H2O molecule adsorption at the tip and show that it reduces fracture toughness by lowering the critical J-integral. Then, we explore stress-enhanced dissolution to understand the mechanism of crack tip blunting in the oxide/water system. Density functional theory combined with metadynamics was employed to describe atomic dissolution from flat hematite and corundum surfaces in pure water. Strain accelerates dissolution, stabilizing intermediate states with broken bonds before full atom detachment, while the free energy profile of unstrained surfaces is almost monotonic. The atomistic calculations provided input for a kinetic model, predicting the shape evolution of a blunt crack tip, which displays three distinct regimes: (i) dissolution primarily away from the tip, (ii) enhanced blunting near but not at the apex, and (iii) sharpening near the apex. The transition between regimes occurs at a low strain, highlighting the critical role of water in the subcritical crack growth of oxide scales, with dissolution as the fundamental microscopic mechanism behind this process.

Chemistry↗
DOE OSTI2024

An examination of the performance of molecular dynamics force fields: Silicon and silicon dioxide reactive ion etching

Classical molecular dynamics (MD) simulations of plasma-surface interactions were performed of physical sputtering and reactive ion etching (RIE), with predictions based on several force fields. In this paper, we focus mainly on SiO 2 but include some results for Si substrates as well. Here, we compare predictions from these MD simulations to experimental studies of SiO 2 physical sputtering (by Ar + ions), RIE of Si, and RIE of SiO 2 (both using F atoms and Ar + ions). MD results using different published force fields are compared to reported yields from published vacuum beam experiments. The near-surface depth profiles predicted using different force fields are compared. One motivation for the present study is to document the nature and magnitude of differences in the predictions for selected systems and conditions of practical interest.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

First principles-based multiscale atomistic methods for input into first principles nonequilibrium transport across interfaces

This issue of PNAS features “nonequilibrium transport and mixing across interfaces,” with several papers describing the nonequilibrium coupling of transport at interfaces, including mesoscopic and macroscopic dynamics in fluids, plasma, and other materials over scales from microscale to celestial. Most such descriptions describe the materials in terms of the density and equations of state rather than specific atomic structures and chemical processes. It is at interfacial boundaries where such atomistic information is most relevant. However, there is not yet a practical way to couple these phenomena with the atomistic description of chemistry. The starting point for including such information is the quantum mechanics (QM). However, practical QM calculations are limited to a hundred atoms for dozens of picoseconds, far from the scales required to inform the continuum level with the proper atomistic description. To bridge this enormous gap, we need to develop practical methods to extend the scale of the atomistic simulation by several orders of magnitude while retaining the level of QM accuracy in describing the chemical process. Here, these developments would enable continuum modeling of turbulent transport at interfaces to incorporate the relevant chemistry. In this perspective, we will focus on recent progress in accomplishing these extensions in first principles-based atomistic simulations and the strategies being pursued to increase the accuracy of very large scales while dramatically decreasing the computational effort.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

On the Network Topology of Cross-Linked Acrylate Photopolymers: A Molecular Dynamics Case Study

A reactive molecular dynamics approach is used to simulate cross-linking of acrylate polymer networks. By employing the same force field and reactive scheme and studying three representative multifunctional acrylate monomers, we isolate the importance of the nonreactive moieties within these model monomers. Analyses of reactive trajectories benchmark the estimated gel points, cyclomatic character, and spatially resolved cross-linking tendencies of the acrylates as a function of conversion. The insights into the similarities and differences of the polymerization and resulting networks presented here suggest molecular mechanics as a useful tool in the rational design of photopolymerization resins.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Predicting CaO-(MgO)-Al2O3-SiO2 glass reactivity in alkaline environments from force field molecular dynamics simulations

In this investigation, force field-based molecular dynamics (MD) simulations have been employed to generate detailed structural representations for a range of amorphous quaternary CaO-MgO-Al{sub 2}O{sub 3}-SiO{sub 2} (CMAS) and ternary CaO-Al{sub 2}O{sub 3}-SiO{sub 2} (CAS) glasses. Comparison of the simulation results with select experimental X-ray and neutron total scattering and literature data reveals that the MD-generated structures have captured the key structural features of these CMAS and CAS glasses. Based on the MD-generated structural representations, we have developed two structural descriptors, specifically (i) average metal oxide dissociation energy (AMODE) and (ii) average self-diffusion coefficient (ASDC) of all the atoms at melting. Both structural descriptors are seen to more accurately predict the relative glass reactivity than the commonly used degree of depolymerization parameter, especially for the eight synthetic CAS glasses that span a wide compositional range. Hence these descriptors hold great promise for predicting CMAS and CAS glass reactivity in alkaline environments from compositional information.

36 MATERIALS SCIENCE↗
DOE OSTI2020

ReaxFF-based molecular dynamics study of bio-derived polycyclic alkanes as potential alternative jet fuels

This work investigates the initial stages of the pyrolysis of HtH-1 (C 18 H 32 ; 2,2,7,7,8a,8b-hexamethyl-dodecahydrobiphenylene) and HtH-2 (C 18 H 34 ; 1,1',3,3,3',3'-hexamethyl-1,1'-bi(cyclohexane)), which are bio-derived polycyclic alkanes and potential jet fuels, using ReaxFF force field based molecular dynamics (MD) simulations. Global Arrhenius parameters, such as activation energies and pre-exponential factors, are calculated and used to analyze the overall decomposition kinetics of the fuels. HtH-1 decomposes faster than HtH-2 at the same temperature and density conditions, and they have a faster decomposition rate compared to some existing jet-fuels, such as JP-10. A systematic reaction analysis framework developed in this work is applied to determine a temperature-dependent decomposition mechanism. At lower temperature, the central C-C bond connecting the two cyclohexane rings is dominantly broken in both HtH-1 and HtH-2. However, C-CH 3 bond breaking becomes dominant with increasing temperature due to the large increase in entropy during this reaction. Major products from HtH-1 are C 5 H 8 and C 4 H 8 , and those from HtH-2 are C 4 H 8 and C 2 H 4 . The major products predict that HtH-1 has a higher sooting tendency than HtH-2, which is consistent with measurements. The impact of HtH-2 on the pyrolysis of HtH-1 is also investigated in their binary mixtures. HtH-1 and HtH-2 decompose by unimolecular reactions, and they rarely interact with each other during the pyrolysis of the mixtures. Furthermore, this work demonstrates that ReaxFF can be used to investigate pyrolysis and combustion chemistry of existing or future fuels and to contribute to the development of their chemical kinetic models without any a priori input and chemical intuition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Role of Capping Agents in the Synthesis of Salicylate-Capped Zinc Oxide Nanoparticles

Capping agents are often used for controlling the size, aggregation, and properties of nanoparticles. To guide the design of improved nanomaterials for targeted performance, one can use mechanistic insights into the interactions between capping agents and nanoparticles. Here, we employ density functional theory (DFT), reactive force-field molecular dynamics (ReaxFF MD) simulations, and optical spectroscopy to study the interactions between salicylate, as a model capping agent, and zinc oxide (ZnO) nanoparticles. In this work, we find that salicylate strongly interacts with the nanoparticle via the formation of O–Zn bonds in a distorted six-membered coordination ring structure. We describe the mechanisms of capping of ZnO nanoparticles by salicylate via three different binding modes. Simulations indicate that salicylate undergoes dissociative adsorption at the highly active surface Zn sites via a hydrogen-transfer process, thereby forming a tridentate configuration. The water-mediated interaction also facilitates the dissociative adsorption, leading to two salicylate O atoms coordinating with a surface Zn atom, while the other salicylate O atom bonds with another surface Zn atom. For molecular adsorption, binding free energies indicate that salicylate binds more strongly to ZnO, often in a bidentate configuration, than water does. The formation of the salicylate–ZnO complex is substantiated by UV–visible and Fourier transform infrared spectra. We find that the C=O stretching mode of salicylate becomes softened when it interacts with the nanoparticle, suggesting chemisorption of salicylate on ZnO. Although DFT predicts strong interaction between salicylate and ZnO, ReaxFF MD simulation indicates the moderate interaction between these two components in aqueous solution. Water molecules in close contact with the nanoparticle surface undergo dissociation, thus resulting in a surface hydroxyl, a reactive oxygen species that may influence the nanoparticle’s catalytic properties. Overall, the atomic-level information provided here can guide the selection process of salicylate as an appropriate agent for ZnO nanoparticle synthesis when strong interactions of particles with capping agents are required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Ferroelectric materials such as BaTiO 3 show tremendous potential for emerging advances in memory devices, particular neuromorphic type devices. High density of memory can be obtained by stabilising polar domain walls at the nanoscale, regions of discontinuity between the well-defined polarization order parameter, but little is known about what controls their structure and dynamics in real nanoscale materials. Indeed, chiral polar domain walls have been observed in heterogeneous ferroelectrics, such as oxygen-deficient BaTiO 3 , but very little is known about how such polar-domains walls interact with defects. Indeed, a critical understanding of how dynamics of domain-walls depend on point-defects is crucial to create engineered ferroelectric memory devices. For this work, we perform large-scale simulations of nansocale domain-wall dynamics in pristine and defective BaTiO 3 using reactive force-field developed by us earlier (Phys. Chem. Chem. Phys., 2019, 21, 18240–18249), and capture their dynamical dependence on point defects using a graph dynamical neural-network approach, which we adapted to interrogate solids with well-defined order-parameters, and implemented using Pytorch based libraries. Our machine learning (ML) approach goes beyond the traditional post-processing methods to capture both spatial and temporal heterogeneities of large-scale molecular dynamics simulations of complex defective ferroelectric oxide materials. We crucially find that isolated oxygen vacancies introduce very localized spatial regions (~1–2 unit-cell in length) that show slow dipole relaxation due to formation of defect-dipoles, and that these defect-dipoles in turn slow the intrinsic dynamics of domain walls. Further, the roughness of domain walls, also influenced by vacancies, introduce dynamic heterogeneity along the domain-wall. As such we find a novel mechanism by which quenched disorder due to defects introduce dynamic heterogeneity thereby influencing response to external fields (particularly time varying fields) in a ferroelectric. Our study also emphasizes the need for creating digital twins of dynamical quantities to achieve autonomous in operando control of nanoscale switching.

42 ENGINEERING↗
DOE OSTI2022

Water Weakening of Calcium Oxide

Chemomechanical processes such as water weakening can control the permeability and deformation of rocks and manmade materials. Here, atomistic modeling and nanomechanical experiments were used to identify molecular origins of chemomechanical effects in calcium oxide (CaO) and its effect on observed elastic, plastic, and brittle deformation. Classical molecular dynamics simulations with the bond order-based reactive force-field ReaxFF were used to assess brittle fracture. In the presence of water, CaO fractured earlier and more often during quasi-static loading, with a calculated reduction in fracture toughness of ~80% associated with changes in the stress distribution around the crack tip. Experimentally, elastic and plastic deformation of CaO surfaces exposed to water was assessed experimentally using in situ liquid nanoindentation. Nanoindentation showed that following exposure to water, the contact hardness decreased by 1–2 orders of magnitude and decreased the modulus by 2–3 orders of magnitude due to surface hydroxylation. Furthermore, the strong chemomechanical effects on the mechanical processes in CaO suggests that minerals with similar structures may exhibit comparable effects, influencing the stability of cements and geomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Single-Step Direct Laser Writing of Multimetal Oxygen Evolution Catalysts from Liquid Precursors

We investigate a laser direct-write method to synthesize and deposit metastable, mixed transition metal oxides and evaluate their performance as oxygen evolution reaction catalysts. This laser processing method enabled the rapid synthesis of diverse heterogeneous alloy and oxide catalysts directly from cost-effective solution precursors, including catalysts with a high density of nanocrystalline metal alloy inclusions within an amorphous oxide matrix. The nanoscale heterogenous structures of the synthesized catalysts were consistent with reactive force-field Monte Carlo calculations. By evaluating the impact of varying transition metal oxide composition ratios, we created a stable Fe 0.63 Co 0.19 Ni 0.18 O x /C catalyst with a Tafel slope of 38.23 mV dec -1 and overpotential of 247 mV, a performance similar to that of IrO 2 . Synthesized Fe 0.63 Co 0.19 Ni 0.18 O x /C and Fe 0.14 Co 0.46 Ni 0.40 O x /C catalysts were experimentally compared in terms of catalytic performance and structural characteristics to determine that higher iron content and a less crystalline structure in the secondary matrix decreases the charge transfer resistance and thus is beneficial for electrocatalytic activity. Furthermore, this conclusion is supported by density-functional theory calculations showing distorted active sites in ternary metal catalysts are key for lowering overpotentials for the oxygen evolution reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Effects of interlayer confinement and hydration on capacitive charge storage in birnessite

Nanostructured birnessite exhibits high specific capacitance and nearly ideal capacitive behaviour in aqueous electrolytes, rendering it an important electrode material for low-cost, high-power energy storage devices. The mechanism of electrochemical capacitance in birnessite has been described as both Faradaic (involving redox) and non-Faradaic (involving only electrostatic interactions). To clarify the capacitive mechanism, we characterized birnessite’s response to applied potential using ex situ X-ray diffraction, electrochemical quartz crystal microbalance, in situ Raman spectroscopy and operando atomic force microscope dilatometry to provide a holistic understanding of its structural, gravimetric and mechanical responses. These observations are supported by atomic-scale simulations using density functional theory for the cation-intercalated structure of birnessite, ReaxFF reactive force field-based molecular dynamics and ReaxFF-based grand canonical Monte Carlo simulations on the dynamics at the birnessite–water–electrolyte interface. We show that capacitive charge storage in birnessite is governed by interlayer cation intercalation. We conclude that the intercalation appears capacitive due to the presence of nanoconfined interlayer structural water, which mediates the interaction between the intercalated cation and the birnessite host and leads to minimal structural changes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Condensation and growth of amorphous aluminosilicate nanoparticles via an aggregation process

The precipitation of zeolite nanoparticles involves the initial formation of metastable precursors, such as amorphous entities, that crystallize through non-classical pathways. Here, using reactive force field-based simulations, we reveal how aluminosilicate oligomers grow concomitantly to the decondensation of silicate entities during the initial step of the reaction. Aluminate clusters first form in the solution, thus violating the Loewenstein rule in the first instant of the reaction, which is then followed by their connection with silicate oligomers at the terminal silanol groups before reorganization to finally diffuse within the silicate oligomers to form stable amorphous aluminosilicate nanoparticles that do obey the Loewenstein rule. Our results clearly indicate that aluminate does not serve as the nucleation center for the growth of aluminosilicates in a nucleation-like process but rather proceeds via an aggregation process. Furthermore, the coexistence of aluminosilicate oligomers and small silicate entities induces a phase separation that promotes the precipitation of zeolites with aging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Surface structure of linear nanopores in amorphous silica: Comparison of properties for different pore generation algorithms

In this work, we compare the surface structure of linear nanopores in amorphous silica (a-SiO 2 ) for different versions of “pore drilling” algorithms (where the pores are generated by the removal of atoms from the preformed bulk a-SiO 2 ) and for “cylindrical resist” algorithms (where a-SiO 2 is formed around a cylindrical exclusion region). After adding H to non-bridging O, the former often results in a moderate to high density of surface silanol groups, whereas the latter produces a low density. The silanol surface density for pore drilling can be lowered by a final dehydroxylation step, and that for the cylindrical resist approach can be increased by a final hydroxylation step. In this respect, the two classes of algorithms are complementary. We focus on the characterization of the chemical structure of the pore surface, decomposing the total silanol density into components corresponding to isolated and vicinal mono silanols and geminal silanols. The final dehyroxylation and hydroxylation steps can also be tuned to better align some of these populations with the target experimental values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

First principles reactive simulation for equation of state prediction

The high cost of density functional theory (DFT) has hitherto limited the ab initio prediction of the equation of state (EOS). In this article, we employ a combination of large scale computing, advanced simulation techniques, and smart data science strategies to provide an unprecedented ab initio performance analysis of the high explosive pentaerythritol tetranitrate (PETN). Comparison to both experiment and thermochemical predictions reveals important quantitative limitations of DFT for EOS prediction and thus the assessment of high explosives. In particular, we find that DFT predicts the energy of PETN detonation products to be systematically too high relative to the unreacted neat crystalline material, resulting in an underprediction of the detonation velocity, pressure, and temperature at the Chapman–Jouguet state. The energetic bias can be partially accounted for by high-level electronic structure calculations of the product molecules. Furthermore we demonstrate a modeling strategy for mapping chemical composition across a wide parameter space with limited numerical data, the results of which suggest additional molecular species to consider in thermochemical modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Can a deep-learning model make fast predictions of vacancy formation in diverse materials?

The presence of point defects, such as vacancies, plays an important role in materials design. Here, we explore the extrapolative power of a graph neural network (GNN) to predict vacancy formation energies. We show that a model trained only on perfect materials can also be used to predict vacancy formation energies (E vac ) of defect structures without the need for additional training data. Such GNN-based predictions are considerably faster than density functional theory (DFT) calculations and show potential as a quick pre-screening tool for defect systems. To test this strategy, we developed a DFT dataset of 530 E vac consisting of 3D elemental solids, alloys, oxides, semiconductors, and 2D monolayer materials. We analyzed and discussed the applicability of such direct and fast predictions. We applied the model to predict 192 494 E vac for 55 723 materials in the JARVIS-DFT database. Our work demonstrates how a GNN-model performs on unseen data.

2D materials↗
DOE OSTI2023

Detailed studies of the processes in low energy H irradiation of Li and Li-compound surfaces

We have used a combination of pico-to-nano temporal/spatial scale computational physics and chemistry modeling of plasma–material interfaces in the tokamak fusion plasma edges to unravel the evolving characteristics, not readily accessible by empirical means, of lithium-, oxygen-, and hydrogen-containing materials of plasma-facing components under irradiation by hydrogen and its isotopes. In the present calculation, amorphous lithium compound surfaces containing oxygen, Li 2 O, and LiOH were irradiated by 1-100 eV particles at incident angles on the surface ranging from perpendicular to almost grazing angles. Consequential surface processes, reflection, retention, and sputtering were studied at “the same footing” and compared to earlier results from amorphous Li and LiH surfaces. In conclusion, the critical role of charging dynamics of lithium, oxygen, and hydrogen atoms in the surface chemistry during hydrogen-fuel irradiation was found to drive the kinetics and dynamics of these surfaces in unexpected ways that ultimately could have profound effects on fusion plasma confinement behavior and surface erosion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Chemical evolution in nitrogen shocked beyond the molecular stability limit

Evolution of nitrogen under shock compression up to 100 GPa is revisited via molecular dynamics simulations using a machine-learned interatomic potential. The model is shown to be capable of recovering the structure, dynamics, speciation, and kinetics in hot compressed liquid nitrogen predicted by first-principles molecular dynamics, as well as the measured principal shock Hugoniot and double shock experimental data, albeit without shock cooling. Our results indicate that a purely molecular dissociation description of nitrogen chemistry under shock compression provides an incomplete picture and that short oligomers form in non-negligible quantities. Finally, this suggests that classical models representing the shock dissociation of nitrogen as a transition to an atomic fluid need to be revised to include reversible polymerization effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗