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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Controlling Deformation in Al/Ti: How Interface Roughness and Orientation Drive Bimetal Mechanics

The microstructural characteristics and morphology of interfaces in metals can be crucial in governing the initiation of plasticity and early deformation mechanisms under extreme conditions. During high-strain-rate deformation, these interfaces significantly affect dislocation nucleation, twinning, and other mechanisms that directly impact material strength and failure. Despite their importance, a substantial knowledge gap remains between the observed macroscopic material behavior and the underlying role of bimetal interfaces in plasticity initiation. Here, to address this gap, large-scale molecular dynamics simulations are performed on Al/Ti bimetal structures to examine the effect of interface characteristics on the onset of plasticity under uniaxial compression. Specifically, this study investigates how interface roughness (flat vs waveform interfaces) modifies the initiation of plastic events in the microstructure. Atomistic simulations indicate that interface roughness (a microscopic behavior) reduces the stress required for dislocation nucleation, thereby reducing the peak stress relative to a flat interface. For the square interface, the step height strongly influences plasticity initiation by setting the separation of locally flat regions. Varying the interface rotation relative to the loading direction (macroscopic behavior) reveals that the peak stress for both flat and waveform interfaces initially decreases and then increases with rotation, accompanied by a shift in dominant mechanisms—from Al twinning (flat) to interface sliding and Ti-dominated phase transformation and twinning at lower angles. The change in the stress-strain slope during initial compression reflects how rotation alters the resolved shear stress and activates different slip systems. Overall, the study provides valuable insights into the role of bimetal interfaces in controlling plasticity initiation and early deformation pathways for Al/Ti under extreme loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Characterizing the diverse hydrogeology underlying rivers and estuaries using new floating transient electromagnetic methodology

We report the hydrogeology below large surface water features such as rivers and estuaries is universally under-informed at the long reach to basin scales (tens of km+). This challenge inhibits the accurate modeling of fresh/saline groundwater interfaces and groundwater/surface water exchange patterns at management-relevant spatial extents. Here we introduce a towed, floating transient electromagnetic (TEM) system (i.e. FloaTEM) for rapid (up to 15 km/h) high resolution electrical mapping of the subsurface below large water bodies to depths often a factor of 10 greater than other towed instruments. The novel FloaTEM system is demonstrated at a range of diverse 4th through 6th-order riverine settings across the United States including 1) the Farmington River, near Hartford, Connecticut; 2) the Upper Delaware River near Barryville, New York; 3) the Tallahatchie River near Shellmound, Mississippi; and, 4) the Eel River estuary, on Cape Cod, near Falmouth, Massachusetts. Airborne frequency-domain electromagnetic and land-based towed TEM data are also compared at the Tallahatchie River site, and streambed geologic scenarios are explored with forward modeling. A range of geologic structures and pore water salinity interfaces were identified. Process-based interpretation of the case study data indicated FloaTEM can resolve varied sediment-water interface materials, such as the accumulation of fines at the bottom of a reservoir and permeable sand/gravel riverbed sediments that focus groundwater discharge. Bedrock layers were mapped at several sites, and aquifer confining units were defined at comparable resolution to airborne methods. Terrestrial fresh groundwater discharge with flowpaths extending hundreds of meters from shore was also imaged below the Eel River estuary, improving on previous hydrogeological characterizations of that nutrient-rich coastal exchange zone. In summary, the novel FloaTEM system fills a critical gap in our ability to characterize the hydrogeology below surface water features and will support more accurate prediction of groundwater/surface water exchange dynamics and fresh-saline groundwater interfaces.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nonequilibrium statistical thermodynamics of multicomponent interfaces

Nonequilibrium interfacial thermodynamics has important implications for crucial biological, physical, and industrial-scale transport processes. Here, we discuss a theory of local equilibrium for multiphase multicomponent interfaces that builds upon the “sharp” interface concept first introduced by Gibbs, allowing for a description of nonequilibrium interfacial processes such as those arising in evaporation, condensation, adsorption, etc. By requiring that the thermodynamics be insensitive to the precise location of the dividing surface, one can identify conditions for local equilibrium and develop methods for measuring the values of intensive variables at the interface. We then use extensive, high-precision nonequilibrium molecular dynamics (NEMD) simulations to verify the theory and establish the validity of the local equilibrium hypothesis. In particular, we demonstrate that equilibrium equations of state are also valid out of equilibrium, and can be used to determine interfacial temperature and chemical potential(s) that are consistent with nonequilibrium generalizations of the Clapeyron and Gibbs adsorption equations. We also show, for example, that, far from equilibrium, temperature or chemical potential differences need not be uniform across an interface and may instead exhibit pronounced discontinuities. However, even in these circumstances, we demonstrate that the local equilibrium hypothesis and its implications remain valid. These results provide a thermodynamic foundation and computational tools for studying or revisiting a wide variety of interfacial transport phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Facet-dependent structure and dissociation of water at pristine IrO 2 /water interfaces

Understanding the microscopic structure of water at metal oxide interfaces is crucial for advancing electrocatalysis. IrO 2 , specifically, has shown exceptional activity for electrochemical water oxidation, but we currently lack a fundamental understanding of how the surface structure of IrO 2 impacts water reactivity. In this work, we developed a machine learning potential trained to first-principles accuracy for modeling IrO 2 /water interfaces across different facets: (110), (100), (101), and (001). Using extensive machine learning molecular dynamics simulations, we investigated the spontaneous dissociation of water molecules at these interfaces. Our results reveal a distinct dissociation probability trend: (110) > (100) ≈ (101) > (001), which we attribute primarily to the reaction thermodynamics of surface water dissociation. A strong correlation is observed between the surface Ir–O bond distances and the dissociation probabilities, highlighting the role of surface geometry in modulating reactivity. As a consequence, the interfacial solvation structures and hydrogen bonding environments are dynamically tuned by the varying water dissociation capabilities across facets. This work elucidates how water dissociation energetics depend on surface orientation and interfacial structure, offering atomistic insights into manipulating reaction chemistry at electrocatalytic interfaces.

organic↗
DOE OSTI2024

Spiers Memorial Lecture: Water at interfaces

In this article we discuss current issues in the context of the four chosen subtopics for the meeting: dynamics and nano-rheology of interfacial water, electrified/charged aqueous interfaces, ice interfaces, and soft matter/water interfaces.

Devlin, Shane W.↗
DOE OSTI2021

Anomalous interfacial dynamics of single proton charges in binary aqueous solutions

Our understanding of the dynamics of charge transfer between solid surfaces and liquid electrolytes has been hampered by the difficulties in obtaining interface, charge, and solvent-specific information at both high spatial and temporal resolution. Here, we measure at the single charge scale the dynamics of protons at the interface between an hBN crystal and binary mixtures of water and organic amphiphilic solvents (alcohols and acetone), evidencing a marked influence of solvation on interfacial dynamics. Applying single-molecule localization microscopy to emissive crystal defects, we observe correlated activation between adjacent ionizable surface defects, mediated by the transport of single excess protons along the solid/liquid interface. Solvent content has a nontrivial effect on interfacial dynamics, leading at intermediate water fraction to an increased surface diffusivity, as well as an increased affinity of the proton charges to the solid surface. Our measurements evidence the notable role of solvation on interfacial proton charge transport.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Visualization of Aluminum Ions at the Mica Water Interface Links Hydrolysis State-to-Surface Potential and Particle Adhesion

When hydrolyzable cations such as aluminum interact with solid-water interfaces, macroscopic interfacial properties (e.g., surface charge and potential) and interfacial phenomena (e.g., particle adhesion) become tightly linked with the microscopic details of ion adsorption and speciation. We use in situ atomic force microscopy to directly image individual aluminum ions at a mica-water interface and show how adsorbate populations change with pH and aluminum activity. Complementary streaming potential measurements then allow us to build a triple layer model (TLM) that links surface potentials to adsorbate populations, via equilibrium binding constants. Our model predicts that hydrolyzed species dominate the mica-water interface, even when unhydrolyzed species dominate the solution. Ab initio molecular dynamics (AIMD) simulations confirm that aluminum hydrolysis is strongly promoted at the interface. The TLM indicates that hydrolyzed adsorbates are responsible for surface-potential inversions, and we find strong correlations between hydrolyzed adsorbates and particle-adhesion forces, suggesting that these species mediate adhesion by chemical bridging.

Legg, Benjamin A.↗
DOE OSTI2022

Rotational Dynamics and Transition Mechanisms of Surface-Adsorbed Proteins

Assembly of biomolecules at solid-water interfaces requires molecules to traverse complex orientation-dependent energy landscapes through processes that are poorly understood, largely due to the dearth of in-situ single molecule measurements and statistical analyses of the rotational dynamics that define directional selection. Emerging capabilities in high-speed atomic force microscopy and machine learning have allowed us to directly determine the orientational energy landscape and observe and quantify the rotational dynamics for protein nanorods on the surface of muscovite mica under a variety of conditions. Comparisons with kinetic Monte Carlo simulations show that the transition rates between adjacent orientation-specific energetic minima can largely be understood through traditional models of in-plane Brownian rotation across a biased energy landscape, with resulting transition rates that are exponential in the energy-barriers between states. However, transitions between more distant angular states are decoupled from barrier height, with jump-size distributions showing a power-law decay that is characteristic of a non-classical Levy-flight random walk, indicating that large jumps are enabled by alternative modes of motion via activated states. The findings provide new insights into the dynamics of biomolecules at solid-liquid interfaces that lead to self-assembly, epitaxial matching and other orientationally anisotropic outcomes and define a general procedure for exploring such dynamics with implications for hybrid biomolecular-inorganic materials design.

Orientational energy landscapes, Rotational dynami↗
DOE OSTI2020

Probing potential energy landscapes via electron-beam-induced single atom dynamics

Structure, bonding, and chemical dynamics of reactions at surfaces and interfaces, and therefore most material properties are intrinsically tied to the energetic landscape in which each atom resides. Here, we demonstrate that a moving atom under electron beam excitation can be used to probe the energy landscape along (confined) step edges, providing information about atomic-scale potentials. In conclusion, the techniques for experimentally exploring atomic potentials holds promise for predictive atom-by-atom fabrication using electron beams.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simulations of nonradiative processes in semiconductor nanocrystals

The description of carrier dynamics in spatially confined semiconductor nanocrystals (NCs), which have enhanced electron–hole and exciton–phonon interactions, is a great challenge for modern computational science. These NCs typically contain thousands of atoms and tens of thousands of valence electrons with discrete spectra at low excitation energies, similar to atoms and molecules, that converge to the continuum bulk limit at higher energies. Computational methods developed for molecules are limited to very small nanoclusters, and methods for bulk systems with periodic boundary conditions are not suitable due to the lack of translational symmetry in NCs. This perspective focuses on our recent efforts in developing a unified atomistic model based on the semiempirical pseudopotential approach, which is parameterized by first-principle calculations and validated against experimental measurements, to describe two of the main nonradiative relaxation processes of quantum confined excitons: exciton cooling and Auger recombination. Here, we focus on the description of both electron–hole and exciton–phonon interactions in our approach and discuss the role of size, shape, and interfacing on the electronic properties and dynamics for II–VI and III–V semiconductor NCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

DyG-DPCD: A Distributed Parallel Community Detection Algorithm for Large-Scale Dynamic Graphs

Dynamic (Temporal) graphs capture the valuable evolution of real-world systems, from the continuously evolving patterns of social interactions and genetic pathways to the dynamic fluctuations of economic forces. Detecting communities for such evolving networks poses unique challenges. Detecting and analyzing the evolution of communities within dynamic graphs unlocks valuable insights into the underlying structural and temporal patterns of real-world systems. However, the sheer volume of modern graph data and the inherent complexity of the temporal dimension pose significant challenges to scalable community detection algorithms. Addressing this gap, our work explores the limited landscape of scalable distributed-memory parallel methods specifically designed for dynamic network community detection. We propose a novel parallel algorithm, DyG-DPCD (Dynamic Graph Distributed Parallel Community Detection), to detect communities in dynamic networks using the Message Passing Interface (MPI) framework. We present a vertex-centric approach, allowing us to detect communities through local optimization. Furthermore, we enhance our baseline algorithm by incorporating three heuristics, which improve the algorithm’s performance significantly while maintaining the quality of the solutions. We demonstrate the efficiency of our algorithm by experimenting on several real-world large-scale networks with hundreds of millions of edges spanning diverse domains. Notably, DyG-DPCD achieves speedups between 25× and 30× for large networks that we experimented on using NERSC compute nodes. In conclusion, our algorithm outperforms the STINGER parallel re-agglomeration algorithm by 30×.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Physics–Informed Neural Networks of the Saint–Venant Equations for Downscaling a Large–Scale River Model

Large-scale river models are being refined over coastal regions to improve the scientific understanding of coastal processes, hazards and responses to climate change. However, coarse mesh resolutions and approximations in physical representations of tidal rivers limit the performance of such models at resolving the complex flow dynamics near the river-ocean interface, resulting in inaccurate simulations of flood inundation. In this research, we propose a machine learning (ML) framework based on the state-of-the-art physics-informed neural network (PINN) to simulate the downscaled flow at the subgrid scale. First, we demonstrate that PINN is able to assimilate observations of various types and solve the one-dimensional (1-D) Saint-Venant equations (SVE) directly. We perform the flow simulations over a floodplain and along an open channel in several synthetic case studies. The PINN performance is evaluated against analytical solutions and numerical models. Our results indicate that the PINN solutions of water depth have satisfactory accuracy with limited observations assimilated. In the case of flood wave propagation induced by storm surge and tide, a new neural network architecture is proposed based on Fourier feature embeddings that seamlessly encodes the periodic tidal boundary condition in the PINN's formulation. Furthermore, we show that the PINN-based downscaling can produce more reasonable subgrid solutions of the along-channel water depth by assimilating observational data. The PINN solution outperforms the simple linear interpolation in resolving the topography and dynamic flow regimes at the subgrid scale. This study provides a promising path towards improving emulation capabilities in large-scale models to characterize fine-scale coastal processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Variations in proton transfer pathways and energetics on pristine and defect-rich quartz surfaces in water: Insights into the bimodal acidities of quartz

Hypothesis. Understanding the mechanisms of proton transfer on quartz surfaces in water is critical for a range of processes in geochemical, environmental, and materials sciences. The wide range of surface acidities (>9 pKa units) found on the ubiquitous mineral quartz is caused by the structural variations of surface silanol groups. Molecular scale simulations provide essential tools for elucidating the origin of site-specific surface acidities. Simulations. Here, we used density-functional tight-binding-based molecular dynamics combined with rare-event metadynamics simulations to probe the mechanisms of deprotonation reactions from ten representative surface silanol groups found on both pristine and defect-rich quartz (1 0 1) surfaces with Si vacancies. Findings. The results show that deprotonation is a highly dynamic process where both the surface hydroxyls and bridging oxygen atoms serve as the proton acceptors, in addition to water. Deprotonation of embedded silanols through intrasurface proton transfer exhibited lower pKa values with less H-bond participation and higher energy barriers, suggesting a new mechanism to explain the bimodal acidity observed on quartz surface. Defect sites, recently shown to comprise a significant portion of the quartz (1 0 1) surface, diversify the coordination and local H-bonding environments of the surface silanols, changing both the deprotonation pathways and energetics, leading to a wider range of pKa values (2.4 to 11.5) than that observed on pristine quartz surface (10.4 and 12.1).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Constant-potential molecular dynamics simulations of molten salt double layers for FLiBe and FLiNaK

We report the results of constant-potential molecular dynamics simulations of the double layer interface between molten 2LiF–BeF 2 (FLiBe) and 23LiF–6NaF–21KF (FLiNaK) fluoride mixtures and idealized solid electrodes. Employing methods similar to those used in studies of chloride double layers, we compute the structure and differential capacitance of molten fluoride electric double layers as a function of applied voltage. The role of molten salt structure is probed through comparisons between FLiBe and FLiNaK, which serve as models for strong and weak associate-forming salts, respectively. In FLiBe, screening involves changes in Be–F–Be angles and alignment of the oligomers parallel to the electrode, while in FLiNaK, the electric field is screened mainly by rearrangement of individual ions, predominantly the polarizable potassium cation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chemical order transitions within extended interfacial segregation zones in NbMoTaW

Interfacial segregation and chemical short-range ordering influence the behavior of grain boundaries in complex concentrated alloys. In this study, we use atomistic modeling of a NbMoTaW refractory complex concentrated alloy to provide insight into the interplay between these two phenomena. Hybrid Monte Carlo and molecular dynamics simulations are performed on columnar grain models to identify equilibrium grain boundary structures. Here our results reveal extended near-boundary segregation zones that are much larger than traditional segregation regions, which also exhibit chemical patterning that bridges the interfacial and grain interior regions. Furthermore, structural transitions pertaining to an A2-to-B2 transformation are observed within these extended segregation zones. Both grain size and temperature are found to significantly alter the widths of these regions. An analysis of chemical short-range order indicates that not all pairwise elemental interactions are affected by the presence of a grain boundary equally, as only a subset of elemental clustering types are more likely to reside near certain boundaries. The results emphasize the increased chemical complexity that is associated with near-boundary segregation zones and demonstrate the unique nature of interfacial segregation in complex concentrated alloys.

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

Tuning water dissociation at oxide–electrolyte interfaces with electric fields

Understanding how electric fields influence water dissociation at heterogeneous interfaces is crucial for controlling interfacial chemical reactions and advancing next-generation energy technologies. Herein, ab initio–based machine learning simulations show that even small electric field changes can significantly alter the water dissociation fraction at planar TiO 2 –electrolyte interfaces. The resulting free energy difference between undissociated and dissociated interfacial water exhibits a linear dependence on the field change with a slope of 1.97 eÅ, which far exceeds the dissociation-induced dipole change of a water molecule. Employing a machine-learned collective variable to investigate the reaction statistics of thousands of water dissociation/recombination events, we find that small electric field changes exert minor effects on individual reaction energy barriers but significantly influence the populations of local configurations associated with initial states that are most favorable for reactions. These findings elucidate the pronounced impact of electric fields on interfacial water dissociation and reveal a mechanism for electric-field-controlled chemical reactions.

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

Kinetic Growth of Multicomponent Microcompartment Shells

An important goal of systems and synthetic biology is to produce high value chemical species in large quantities. Microcompartments, which are protein nanoshells encapsulating catalytic enzyme cargo, could potentially function as tunable nanobioreactors inside and outside cells to generate these high value species. Modifying the morphology of microcompartments through genetic engineering of shell proteins is one viable strategy to tune cofactor and metabolite access to encapsulated enzymes. However, this is a difficult task without understanding how changing interactions between the many different types of shell proteins and enzymes affect microcompartment assembly and shape. Here, we use multiscale molecular dynamics and experimental data to describe assembly pathways available to microcompartments composed of multiple types of shell proteins with varied interactions. As the average interaction between the enzyme cargo and the multiple types of shell proteins is weakened, the shell assembly pathway transitions from (i) nucleating on the enzyme cargo to (ii) nucleating in the bulk and then binding the cargo as it grows to (iii) an empty shell. Atomistic simulations and experiments using the 1,2-propanediol utilization microcompartment system demonstrate that shell protein interactions are highly varied and consistent with our multicomponent, coarse-grained model. Furthermore, our results suggest that intrinsic bending angles control the size of these microcompartments. Altogether, our simulations and experiments provide guidance to control microcomparmtent size and assembly by modulating the interactions between shell proteins.

defects↗
DOE OSTI2025

Understanding LIB Battery Electrodes Through Classical Electrochemical Interface Theory

Classical models of the electrochemical interface can be applied to complex and dynamic electrodes to understand important mechanisms that are relevant to device-level phenomena like calendar aging or cycle life. Here, we show that negative alloy electrodes with wide electrochemical windows cannot be assumed to have static interfaces throughout all states of charge. Under high states of charge, the interface -including the solid electrolyte interphase - has characteristics that resemble a highly polarized electrode far from the point of zero charge. Under these conditions, the interface can be understood through the Helmholtz model. At lower states of charge, the interface capacitance decreases and the space charge layer length increases. This transformation resembles a metal electrode approaching the point of zero charge which is understood through the Gouy-Chapman-Stern-Grahame model of the electrochemical interface. This transformation happens at both silicon and carbon-coated silicon interfaces. From voltage-limited cycling experiments, in the limit of the diffuse double layer, the silicon electrode impedance rises significantly in the first few cycles. This rise is related to the continuous electrochemical reduction of electrolyte components from an interface that is not electronically screened from the electrolyte. In other words, an electrode interface for batteries should resemble a 'Helmholtz-like' structure.

anode↗