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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Ferroelectric Fractals: Switching Mechanism of Wurtzite AlN

The advent of wurtzite ferroelectrics is enabling new ferroelectric devices for computer memory that have the potential to bypass the von Neumann bottleneck due to their robust polarization and silicon compatibility. However, the atomistic switching mechanism of wurtzites is still undetermined due to the limitations of density functional theory simulation size and experimental temporal and spatial resolution. Thus, physics-informed materials engineering to reduce coercive field and breakdown in these devices has been limited. In this work, the atomistic mechanism of domain wall migration and domain growth in aluminum nitride-based wurtzites is uncovered using molecular dynamics and Monte Carlo simulations. We reveal the anomalous switching mechanism of fast 1D single columns of atoms propagating from a slow-moving 2D fractallike domain wall. We find that the critical nucleus is a single aluminum ion that breaks its bond with one nitrogen and bonds to another nitrogen; this creates a cascade that flips atoms directly only in the same column, due to the extreme locality (sharpness) of the domain walls in wurtzites. We further show how the fractallike shape of the domain wall in the 2D plane breaks assumptions in the Kolmogorov, Avrami, and Ishibashi (KAI) model and leads to the anomalously fast switching in wurtzite structured ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Atomistic Explanation of the Dramatically Improved Oxygen Reduction Reaction of Jagged Platinum Nanowires, 50 Times Better than Pt

Pt is the best catalyst for the oxygen reduction reactions (ORRs), but it is far too slow. Huang and co-workers showed that dealloying 5 nm Ni 7 Pt 3 nanowires (NW) led to 2 nm pure Pt jagged NW (J-PtNW) with ORRs 50 times faster than Pt/C. They suggested that the undercoordinated surface Pt atoms, mechanical strain, and high electrochemically active surface area (ECSA) are the main contributors. We report here multiscale atomic simulations that further explain this remarkably accelerated ORR activity from an atomistic perspective. We used the ReaxFF reactive force field to convert the 5 nm Ni 7 Pt 3 NW to the jagged 2 nm NW. We applied quantum mechanics to find that 14.4% of the surface sites are barrierless for O ads + H 2 O ads → 2OH ads , the rate-determining step (RDS). The reason is that the concave nature of many surface sites pushes the OH bond of the H 2 O ads close to the O ads , leading to a dramatically reduced barrier. We used this observation to predict the performance improvement of the J-PtNW relative to Pt (111). Assuming every surface site reacts independently with this predicted rate leads to a 212-fold enhancement at 298.15 K, compared to 50 times experimentally. The atomic structures of the active sites provide insights for designing high-performance electrocatalysts for ORR.

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

Hydration and reaction mechanisms on sodium silicate glass surfaces from molecular dynamics simulations with reactive force fields

Recent development of reactive force fields have enabled molecular dynamics simulations of interactions between silicate glasses and water at the atomistic scale. While multicomponent silicate glasses encompass a wide variety of compositions and properties, one common structural feature in these glasses is the combination of the network structure that is made up of silica tetrahedra linked through corner sharing interspersed with network modifiers like alkali and alkaline-earth ions that break up the Si–O–Si linkages by forming nonbridging oxygen. In reactions with water, ion exchange between alkali ions in the glass and proton or hydronium in the solution, as well as hydrolysis reaction of the Si–O–Si linkages and subsequent silanol formation, is observed and well documented. Furthermore, we have used a set of recently developed reactive force field to investigate the reactions between water and the surfaces of silica and sodium silicate glasses of different compositions for reactions up to 8 nanoseconds. Our results indicate sodium leaching into water and diffusion of water molecules up to 25 Å into the glass surface. We examined the structural and compositional changes inside the glass and around the diffused ions and use these to explain the rates of silanol formation at the surface. We also observed proton transport in the glass which has an indirect influence on the silanol formation rates. While the surface of the glass was rough to start with, it undergoes further modification into a hydrated gel-like structure in the glass for up to 5 Å in the higher alkali containing glasses. It was found that the leached sodium ions remain close to the interface and that fragments of silicate network from the surface is capable of dislodging from the bulk glass and enter the aqueous solution. These simulations thus provide insights into the formation and structure of an alteration layers commonly observed in multicomponent silicate glasses corroded in aqueous solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Predicting Atomistic Transitions with Transformers

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find these transitions are extremely computationally intensive. Even with large-scale, accelerated material simulations, the computational cost constrains the applicable domain in practice. Machine learning models, with the potential to learn the complex emergent behaviors governing atomistic transitions as a fast surrogate model, have great promise to predict transitions with a vastly reduced computational cost. Here, we demonstrate how transformers can be trained to predict atomistic transitions in nano-clusters. We show how we evaluate physical validity of the predictions and how a multitude of additional, different microstates can be generated by slightly varying the data provided to the model.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of a creep model informed by lower-length scale simulations to simulate creep in doped UO 2

Using molecular dynamics, we predict information at the atomistic scale used to develop a mechanistic UO 2 creep model for use in higher length-scale fuel performance codes. The ultimate objective of the model is to better describe the grain size dependence and therefore impact of doping on creep rates in UO 2 . In a previous NEAMS milestone, we found that Nabarro-Herring (bulk diffusional) creep was too low to capture the experimentally observed creep rates in standard UO 2 . Moreover, in that milestone, other mechanisms were explored, such as Coble (grain boundary) creep and dislocation climb, with each mechanism exhibiting different grain size dependencies. Again, these were orders of magnitude too low to describe the experimental creep rates. In this work, we address the previous assumptions made for the Coble creep mechanism by investigating the diffusivity of various defects at grain boundaries in UO 2 and, critically, to determine if enhanced grain boundary diffusivity allows the model to better reproduce experimental results. The diffusivity as a function of temperature for different concentrations of uranium vacancies and interstitials for bulk UO 2 have also been examined using cluster dynamics. Furthermore, using a concentration dependent segregation model, the concentration of defects at the grain boundary were predicted. This atomistic data was then input into the various creep mechanisms and the creep rates compared to the empirical MATPRO correlation (used in BISON) and experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Atomistic Modeling of the Interphase Structure between Alumina and Al12Fe2Cr Quasicrystal Approximant

Molecular dynamics simulations are performed to study the stability of an fcc metallic interlayer phase between an iron aluminide quasicrystal approximant (QCA) phase (84.2 Al, 5.7 Fe, 5.4 Ni, and 4.7 at.% Cr) and aluminum oxides (α-Al 2 O 3 and γ-Al 2 O 3 ). The presence of the interlayer phase was experimentally observed in some regions of the inner diameter surface of a TPBAR cladding tube. The simulations employed existing many-body (MEAM and EAM) interatomic potentials to describe atomic interactions in the interlayer and QCA phases, and Buckingham+Coulomb pair interactions for the alumina and between the alumina and the QCA (or fcc). Interface systems of QCA/alumina, fec/alumina, and QCA/fcc are modeled and the fracture energy of the interfaces is calculated. Based on the fracture energies, for the γ-Al 2 O 3 , both MEAM and EAM suggest that the fcc interlayer phase would not form. For the α-Al 2 O 3 , the MEAM predicts that the fcc phase would form, however, the EAM predicts that it forms only if the α-Al 2 O 3 is Al-terminated at the interface. For the O-terminated α-Al 2 O 3 , the EAM predicts the fcc phase would not form, consistent with the results for γ-Al 2 O 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development and Applications of an eReaxFF Force Field for Graphitic Anodes of Lithium-Ion Batteries

Graphene is one of the most promising materials for lithium-ion battery anodes due to its superior electronic conductivity, high surface area for lithium intercalation, fast ionic diffusivity and enhanced specific capacity. A reliable description of many battery processes requires an explicit description of electrochemical interactions involving electrons. A detailed atomistic modeling of electronic conduction and non-zero voltage simulations of graphitic materials require the inclusion of an explicit electronic degree of freedom. To enable large length- and time-scale simulations of electron conduction in graphitic anodes, we developed an eReaxFF force field concept describing graphitic materials with an explicit electron. The newly developed force field, verified against quantum chemistry-based data describing, amongst others, electron affinities and equation of states, reproduces the qualitative behavior of electron conductivity in pristine and imperfect graphitic materials at different applied temperatures and voltages. In addition, excess electron localization near a defect site estimated from eReaxFF simulations agree quite well with the corresponding density functional theory calculations. Here, our eReaxFF simulations show the initiation of lithium-metal-plating driven by electron transfer from the graphene surface to the exposed lithium ions demonstrating the method’s potential for studying lithium-graphene interactions with explicit electrons and explain many unresolved electrode and electrode-electrolyte interface processes.

25 ENERGY STORAGE↗
DOE OSTI2025

Atomistic Insights into the Reactive Diffusion of CO 2 in Guanidine-Based Facilitated Transport Membranes

The pressing need to address climate change has led to significant advancements in carbon dioxide (CO 2 ) capture technologies. Notably, facilitated transport membranes (FTMs) are distinguished by their exceptional selectivity and permeance, attributed to their reversible chemical reactions with CO 2 . This study, for the first time, sheds light on the reactive diffusion mechanism of CO 2 in FTMs, utilizing 1,1,3,3-tetramethylguanidine (TMG) as a mobile carrier. Specifically, state-ofthe- art molecular dynamics (MD) simulations, augmented by a reparameterized reactive force field (ReaxFF) capable of describing atomistic interactions and reaction pathways, are conducted to investigate the transport of CO 2 in TMG. The analysis of mean squared displacement (MSD) and diffusion coefficients reveals a clear hierarchy in the mobility of reaction components. Our findings highlight a unique hopping diffusion mechanism between bicarbonate ions and TMG molecules, increasing the diffusivity of reacted CO 2 by 1.4 times. The hopping events observed not only enhance our understanding of molecular mobility but also offer a means to boost the performance of FTMs in CO 2 capture applications. Overall, this research lays the groundwork for the future design of FTMs with optimal carrier properties.

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

Demonstration of Advanced Experimental and Theoretical Characterization of Hydrogen Dynamics and Associated Behavior in Advanced Reactors

Advanced materials development, manufacturing, and modeling capabilities for innovative reactor designs support nuclear security and mission-focused science through enhanced technology for safer and more efficient and secure production of nuclear energy. The research in this project has established: 1) a state-of-the-art neutron-based hydrogen mapping and cross-section measurement capability as well as detailed crystallographic characterization of hydrogen atoms at LANSCE, and 2) a multi-physics framework for simulating behavior of moderator materials and other material performance in advanced nuclear reactors. Through the course of this project, we successfully developed and demonstrated measurement techniques for hydrogen distribution and atomistic-scale behavior of hydrogen atoms using pulsed neutron techniques. In parallel, advanced multi-physics simulation tools to predict the behavior of hydrogen atoms, e.g. in a moderator for a nuclear reactor, through materials performance, neutron transport, and thermal mechanical behavior were enhanced. Multi-discipline areas across the laboratory were involved in the project as the integration of improved experimental capabilities with enhanced modeling and simulation through MST, NEN, SIGMA, and XCP division subject matter experts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Probing the electronic properties of the electrified silicon/water interface by combining simulations and experiments.

Silicon (Si) is broadly used in electrochemical and photoelectrochemical devices, where the capacitive and Faradaic reactions at the Si/water interfaces are critical for signal transduction or noise generation. However, probing the electrified Si/water interface at the microscopic level remains a challenging task. Here we focus on hydrogenated Si surfaces in contact with water, relevant to transient electronics and photoelectrochemical modulation of biological cells and tissues. We show that by carrying out first principles molecular dynamics simulations of the Si(100)/water interface in the presence of an electric field we can realistically correlate the computed flat-band potential and tunneling current images at the interface with experimentally measured capacitive and Faradaic currents. Specifically, we validate our simulations in the presence of bias by performing pulsed chronoamperometry measurements on Si wafers in solution. Consistent with prior experiments, our measurements and simulations indicate the presence of voltage-dependent capacitive currents at the interface. We also find that Faradaic currents are weakly dependent on the applied bias, which we relate to surface defects present in newly prepared samples.

Ye, Zifan↗
DOE OSTI2023

Universal and interpretable classification of atomistic structural transitions via unsupervised graph learning

Materials processing often occurs under extreme dynamic conditions leading to a multitude of unique structural environments. These structural environments generally occur at high temperatures and/or high pressures, often under non-equilibrium conditions, which results in drastic changes in the material's structure over time. Computational techniques, such as molecular dynamics simulations, can probe the atomic regime under these extreme conditions. However, characterizing the resulting diverse atomistic structures as a material undergoes extreme changes in its structure has proved challenging due to the inherently non-linear relationship between structures as large-scale changes occur. Here, we introduce SODAS++, a universal graph neural network framework, that can accurately and intuitively quantify the atomistic structural evolution corresponding to the transition between any two arbitrary phases. We showcase SODAS++ for both solid–solid and solid–liquid transitions for systems of increasing geometric and chemical complexity, such as colloidal systems, elemental Al, rutile and amorphous TiO 2 , and the non-stoichiometric ternary alloy Ag 26 Au 5 Cu 19 . Finally, we show that SODAS++ can accurately quantify all transitions in a physically interpretable manner, showcasing the power of unsupervised graph neural network encodings for capturing the complex and non-linear pathway, a material's structure takes as it evolves.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An atomistic model for the thermal resistance of a liquid–solid interface

The thermal resistance associated with the interface between a solid and a liquid is analysed from an atomistic point of view. Partial evaluation of the associated Green–Kubo integral elucidates the various factors governing heat transport across the interface and leads to a quantitative model for the thermal resistance in terms of atomistic-level system parameters. The model is validated using molecular dynamics simulations.

Mechanics↗
DOE OSTI2026

Conserved Macromolecular Architecture of Poplar Secondary Cell Walls Revealed by ssNMR and Atomistic Modeling

The macromolecular architecture of plant secondary cell walls governs wood's mechanical and biochemical properties, yet its natural intra-species variability remains poorly characterized. Here, we combined 13C solid-state NMR (ssNMR), multivariate statistical analysis, and molecular modeling to profile nanoscale structure across 13 genetically diverse Populus trichocarpa genotypes grown in 13C-enriched atmospheres. SsNMR-derived phenotypes spanning composition, structure, mobility, and inter-polymer proximities reveal a conserved architecture, with a subtle yet coordinated variation organizing into dominant structural and secondary mobility axes. A representative atomistic model captures these features and reproduces experimental metrics. Molecular dynamics simulations support a weak but consistent positive correlation between cellulose abundance and crystalline-like order, with interior cellulose chains enriched in tg (trans-gauche) conformations without expanding crystalline cores. Together, experiment and simulation reveal a genetically buffered, broadly conserved nanoscale architecture across genotypes, where subtle fine-tuning of cellulose bundling and matrix packing balances mechanical performance with biological function.

09 BIOMASS FUELS↗
DOE OSTI2025

Mechanistic Multiscale Uncertainty Propagation in Support of Accelerated Fuel Qualification

Taking a nuclear fuel concept through the research, development, and qualification stages has historically taken on the order of 20 to 25 years because of extensive irradiation tests required for a variety of conditions. The concept of accelerated fuel qualification (AFQ) has been proposed to increase the innovation pace for nuclear fuels. The goal of AFQ is not to replace the traditional qualification approach but rather to reduce the total number of experiments required to ensure approval from the regulatory authority. Of the many AFQ approaches being explored, advanced modeling—and, in particular, mechanistic modeling—is in a uniquely cross-cutting position to reduce the number of required integral tests through the inclusion of separate-effects testing, while helping to extrapolate reactor performance during rare events. We make the case that propagation of uncertainty through various computational length scales helps contextualize mechanistic modeling. We will utilize UO 2 fission gas diffusion predictions from the atomistically informed cluster dynamics code Centipede to inform fuel performance rodlet simulations using the BISON finite element code as the metric for showing how multiscale mechanistic uncertainty quantification can help reduce uncertainty in fuel performance. In conclusion, by quantifying uncertainty and its reduction through multiscale modeling, the qualification process may be accelerated through the reduction of costly irradiation experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Unveiling oxidation mechanism of bulk ZrS2

Abstract Transition metal dichalcogenides have shown great potential for next-generation electronic and optoelectronic devices. However, native oxidation remains a major issue in achieving their long-term stability, especially for Zr-containing materials such as ZrS 2 . Here, we develop a first principles-informed reactive forcefield for Zr/O/S to study oxidation dynamics of ZrS 2 . Simulation results reveal anisotropic oxidation rates between (210) and (001) surfaces. The oxidation rate is highly dependent on the initial adsorption of oxygen molecules on the surface. Simulation results also provide reaction mechanism for native oxide formation with atomistic details. Graphic Abstract

Yang, Liqiu↗
DOE OSTI2020

Lithiation of Sulfur-Graphene Compounds Using Reactive Force-Field Molecular Dynamics Simulations

We performed molecular dynamics simulations of lithium-sulfur-graphene compounds using reactive force fields, providing a time scale to observe atomistic features relevant to the microscopic behavior of the of the bulk of sulfur-based cathodes to be used beyond our present Li-ion batteries. The samples we used were set to realistic geometries through sophisticated protocols to simulate ultrafast reactions that occur within the picosecond range, thus allowing us to get some insights into the characteristics of the bulk material in working cathodes of Li–S batteries, which are mixed with carbon to increase the poor electronic conductivity of S. We report chemical speciation and geometrical data at atomistic levels. We observed that slowly lithiated cathodes were more stable and with higher density than those that were suddenly fully-lithiated. We did not observe molecular Li 2 S formation; however, we observed an amorphous solid arrangement with the same stoichiometry of Li and S, with S–Li–S angles of ~111° and smaller ones due to the interaction between polysulfides that did not reacted totally. In addition, graphene keeps its planar shape; however, S8 changes its shape from rings to chains. Lithiated structures are more stable with lower energies, and more close-packed structures than structures with Li already inserted.

25 ENERGY STORAGE↗
DOE OSTI2021

Advances in Clayff Molecular Simulation of Layered and Nanoporous Materials and Their Aqueous Interfaces

As a general-purpose force field for molecular simulations of layered materials and their fluid interfaces, Clayff continues to see broad usage in atomistic computational modeling for numerous geoscience and materials science applications due to its (1) success in predicting properties of bulk nanoporous materials and their interfaces, (2) transferability to a range of layered and nanoporous materials, and (3) simple functional form which facilitates incorporation into a variety of simulation codes. Here, we review applications of Clayff to model bulk phases and interfaces not included in the original parameter set and recent modifications for modeling surface terminations such as hydroxylated nanoparticle edges. Overall, we conclude with a discussion of expectations for future developments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. In this work, we address these challenges by leveraging distributions of per-sample errors obtained during training and employing a distance-based similarity search in the model latent space. Our method, which we call LTAU (Loss Trajectory Analysis for Uncertainty), efficiently estimates the full probability distribution function of errors for any test point using the logged training errors, achieving speeds that are 2–3 orders of magnitudes faster than typical ensemble methods and allowing it to be used for tasks where training or evaluating multiple models would be infeasible. We apply LTAU towards estimating parametric uncertainty in atomistic force fields (LTAU-FF), demonstrating that it produces well-calibrated confidence intervals and predicts errors that correlate strongly with the true errors for data near the training domain. Furthermore, we show that the errors predicted by LTAU-FF can be used in practical applications for detecting out-of-domain data, tuning model performance, and predicting failure during simulations. We believe that LTAU will be a valuable tool for uncertainty quantification in atomistic force fields and is a promising method that should be further explored in other domains of machine learning.

97 MATHEMATICS AND COMPUTING↗