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Results for “Heterogeneous interface”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multiphase layered transition metal oxide positive electrodes for sodium ion batteries

Abstract Multiphase layered transition metal oxides (LTMOs) for sodium ion battery (SIB) positive electrodes with phase interfaces across multiple length scales are a promising avenue toward practical, high‐performance SIBs. Combinations of phases can complement each other's strengths and mitigate their weaknesses if their interfaces are carefully controlled. Intra‐ and interparticle phase interactions from nanoscale to macroscale must be carefully tuned to generate distinct effects on properties and performance. An informed design strategy must be paired with relevant synthesis techniques and complemented by spatially resolved characterization tools to manipulate different length scales and interfaces. This review examines the design, synthesis, and characterization strategies that have been demonstrated for the preparation of heterogeneous, multiphasic LTMOs with phase interfaces across varied length scales.

25 ENERGY STORAGE↗
DOE OSTI2020

An energy-based coupling approach to nonlocal interface problems.

Nonlocal models provide accurate representations of physical phenomena ranging from fracture mechanics to complex subsurface flows, settings in which traditional partial differential equation models fail to capture effects caused by long-range forces at the microscale and mesoscale. However, the application of nonlocal models to problems involving interfaces, such as multimaterial simulations and fluid-structure interaction, is hampered by the lack of a physically consistent interface theory which is needed to support numerical developments and, among other features, reduces to classical models in the limit as the extent of nonlocal interactions vanish. In this paper, we use an energy-based approach to develop a formulation of a nonlocal interface problem which provides a physically consistent extension of the classical perfect interface formulation for partial differential equations. Numerical examples in one and two dimensions validate the proposed framework and demonstrate the scope of our theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Using probability distribution function as a scaling approach to incorporate soil heterogeneity into biogeochemical models for greenhouse gas predictions (Final Technical Report)

The project investigated biogeochemical processes at terrestrial-aquatic interfaces (TAIs), focusing on soil microsite heterogeneity and its impact on greenhouse gas (GHG) fluxes. Using laboratory experiments, modeling, and data integration, researchers explored redox-driven microbial processes under fluctuating hydrological conditions. Key advancements included modifying the DAMM-GHG model to incorporateelectron acceptor availability and enhancing the AquaMEND model for improved microbial metabolism representation. Results highlighted microsite redox variability as a key driver of GHG fluxes, informing Earth system models. The project fostered interdisciplinary collaborations, student training, and the development of novel modeling frameworks to improve Earth'senergy budget.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for inverse problems: Determining material properties for heterogeneous systems

Here, we determine spatially varying discontinuous material properties using a domain-decomposition based physics-informed neural networks (PINNs) framework named the Adaptive Interface-PINNs or AdaI-PINNs (Roy et al., 2024). We propose the use of distinct neural networks for the field variables and material properties within each material, utilizing adaptive activation functions. While the neural networks across different materials share the same weights and biases, their activation functions are uniquely tailored using a hyperparameter that influences the slope of the activation function. The proposed framework is tested on several one-dimensional and two-dimensional benchmark examples, and its performance is compared with conventional PINNs and existing domain-decomposition PINNs frameworks, namely, the Multi-domain physics-informed neural network (M-PINN), and the eXtended physics-informed neural networks (XPINNs). The results demonstrate that the proposed approach can determine randomly distributed discontinuous material properties with an L 2 error of $\mathscr{O}$ (10 -3 ) for the material property and the root-mean-square error of $\mathscr{O}$ (10 -3 ) for the primary variable while the other approaches yield errors that are approximately two orders of magnitude larger (that is, $\mathscr{O}$ (10 -1 )). Moreover, the spatial distribution of material properties obtained using the proposed framework is in close agreement with the true distribution, whereas the other approaches fare much worse. Additionally, the proposed approach is approximately 40% faster than its competitors, indicating its potential as a robust alternative for solving inverse problems in heterogeneous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

11-th order of accuracy for numerical solution of 3-D Poisson equation with irregular interfaces on unfitted Cartesian meshes

For the first time the optimal local truncation error method (OLTEM) with 125-point stencils and unfitted Cartesian meshes has been developed in the general 3-D case for the Poisson equation for heterogeneous materials with smooth irregular interfaces. The 125-point stencils equations that are similar to those for quadratic finite elements are used for OLTEM. The interface conditions for OLTEM are imposed as constraints at a small number of interface points and do not require the introduction of additional unknowns, i.e., the sparse structure of global discrete equations of OLTEM is the same for homogeneous and heterogeneous materials. The stencils coefficients of OLTEM are calculated by the minimization of the local truncation error of the stencil equations. These derivations include the use of the Poisson equation for the relationship between the different spatial derivatives. Such a procedure provides the maximum possible accuracy of the discrete equations of OLTEM. In contrast to known numerical techniques with quadratic elements and third order of accuracy on conforming and unfitted meshes, OLTEM with the 125-point stencils provides 11-th order of accuracy, i.e., an extremely large increase in accuracy by 8 orders for similar stencils. The numerical results show that OLTEM yields much more accurate results than high-order finite elements with much wider stencils. The increased numerical accuracy of OLTEM leads to an extremely large increase in computational efficiency. Additionally, a new post-processing procedure with the 125-point stencil has been developed for the calculation of the spatial derivatives of the primary function. The post-processing procedure includes the minimization of the local truncation error and the use of the Poisson equation. It is demonstrated that the use of the partial differential equation (PDE) for the 125-point stencils improves the accuracy of the spatial derivatives by 6 orders compared to post-processing without the use of PDE as in existing numerical techniques. At an accuracy of 0.1% for the spatial derivatives, OLTEM reduces the number of degrees of freedom by 900 - 4∙10 6 times compared to quadratic finite elements. The developed post-processing procedure can be easily extended to unstructured meshes and can be independently used with existing post-processing techniques (e.g., with finite elements).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Zero-Strain Metal-Insulator Transition by the Local Fluctuation of Cation Dimerization

The coupled electronic and structural transitions in metal-insulator transition (MIT) hinder ultrafast switching and ultimate endurance. Decoupling these transitions and achieving a zero-strain electronic MIT can overcome the fundamental limitations of MIT in solid materials. Here, this study demonstrates that iso-valent Ti dopants in supercooled VO 2 epitaxial films cause MIT with minimal hysteresis without changing unit-cell volume and crystal symmetry. The Ti dopants in the VO 2 lattice locally alter the configuration of V-V pairs, where the long-range ordering in V-V pairs is disrupted, and the nano-domains of V-V dimers are formed. Strikingly, these local V-V dimers persist even above the electronic transition temperature (T MI ), facilitating the zero-strain electronic MIT with nanoscale structural heterogeneity. The geometrically compatible interface between insulating and metallic phases drastically enhances switching speed and endurance during electrically and optically driven zero-strain MIT. In conclusion, this discovery offers a fresh perspective on the scientific understanding of MIT and the improved functionality in terms of device speed and reliability by decoupling electronic and structural transitions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Interface PINNs (I-PINNs): A physics-informed neural networks framework for interface problems

Here, we present a novel physics-informed neural networks (PINNs) framework for modeling interface problems, termed Interface PINNs (I-PINNs). I-PINNs uses different neural networks for any two subdomains separated by a sharp interface such that the neural networks differ only through their activation functions while the other parameters remain identical. The performance of I-PINNs, conventional PINNs, and other existing domain-decomposition PINNs methods such as extended PINNs (XPINNs) and multi-domain PINN (M-PINN) is compared through several one-dimensional, two-dimensional, and three-dimensional benchmark elliptic interface problems. The results demonstrate that I-PINNs provides a root-mean-square-error accuracy, at least two orders of magnitude better than conventional PINNs and XPINNs at approximately one-tenth of the computational cost of conventional PINNs and half the cost of XPINNs. Additionally, while I-PINNs and M-PINN provide comparable accuracies, M-PINN is found to be approximately 50% more expensive.

42 ENGINEERING↗
DOE OSTI2022

Medium-independent hydrogen atom binding isotherms of nickel oxide electrodes

Adsorption and transfer of hydrogen atoms at solid/solution interfaces are fundamental to heterogeneous catalysis for chemical energy transformations and other processes. Reported here are electrochemical and spectroelectrochemical measurements of the thermodynamics of H-atom binding to nickel oxide electrodes, both the average and the distribution of NiO–H bond dissociation free energies (BDFEs). These are perhaps the first measurements of binding isotherms at non-metal electrodes. Remarkably, both the BDFEs and the non-Langmuirian isotherms are the same in water, acetonitrile, and dimethylformamide, and with different buffers and proton activities. Such medium independence of the BDFEs and isotherms has not been previously reported for any binary material. The medium independence supports the common use of computed hydrogen binding energies as intrinsic descriptors of surface reactivity, while the broadened isotherms add a level of complexity to such analyses. Furthermore, this work demonstrates the capability to derive key thermodynamic parameters at chemically reactive solid-liquid interfaces.

13 HYDRO ENERGY↗
DOE OSTI2023

Heterostructure engineering in electrode materials for sodium-ion batteries: Recent progress and perspectives

Sodium-ion batteries (SIBs) have stepped into the spotlight as a promising alternative to lithium-ion batteries for large-scale energy storage systems. However, SIB electrode materials, in general, have inferior performance than their lithium counterparts because Na + is larger and heavier than Li + . Heterostructure engineering is a promising strategy to overcome this intrinsic limitation and achieve practical SIBs. We provide a brief review of recent progress in heterostructure engineering of electrode materials and research on how the phase interface influences Na + storage and transport properties. Efficient strategies for the design and fabrication of heterostructures (in situ methods) are discussed, with a focus on the heterostructure formation mechanism. The heterostructure's influence on Na + storage and transport properties arises primarily from local distortions of the structure and chemomechanical coupling at the phase interface, which may accelerate ion/electron diffusion, create additional active sites, and bolster structural stability. Finally, we offer our perspectives on the existing challenges, knowledge gaps, and opportunities for the advancement of heterostructure engineering as a means to develop practical, high-performance sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Probing Heterogeneous Charge Distributions at the α-Al 2 O 3 (0001)/H 2 O Interface

Unlike metal or semiconductor electrodes, the surface charge resulting from the protonation or deprotonation of insulating mineral oxides is highly localized and heterogeneous in nature. In this work the Stark active C≡N stretch of potassium thiocyanate is used as a molecular probe of the heterogeneity of the interfacial electrostatic potential at the α-Al 2 O 3 (0001)/H 2 O interface. Vibrational sum frequency generation (vSFG) measurements performed in the OH stretching region suggest that thiocyanate species organize interfacial water similarly to halide ions. Changes in the electrostatic potential are then tracked via Stark shifts of the vibrational frequency of the thiocyanate stretch. Our vSFG measurements show that we can simultaneously measure the vSFG response of SCN – ions experiencing charged and neutral surface sites. We assign local potentials of +308 and -154 mV to positively and negatively charged aluminol groups that are present at pH = 4 and pH = 10, respectively. Thiocyanate anions at positively charged surface sites and negatively charged surface sites and those participating in contact ion pairing adopt similar orientations and are oppositely oriented relative to thiocyanate ions near neutral surface sites. All four species followed Langmuir adsorption isotherms. Density functional theory–molecular dynamics (DFT-MD) simulations of SCN – near the neutral α-Al 2 O 3 (0001)/H 2 O interface show that the vSFG response in the C≡N stretch region originates from a SCN–H–O–Al complex, suggesting the surface site specificity of these experiments. To our knowledge this is the first spectroscopic measurement of local potentials associated with a heterogeneously charged surface. The ability to probe the evolution of local charges in situ could provide vital insight into many industrial, electrochemical, and geochemically relevant interfaces.

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

Hierarchical Defect Engineering for LiCoO 2 through Low-Solubility Trace Element Doping

Real-world industry-relevant battery composite electrodes are hierarchically structured. Their structural and chemical complexity is featured by ubiquitous multi-scale porosity and cracks, solid-solid and solid-liquid interfaces, compositional and redox heterogeneity, as well as lattice disordering and deformation. In particular for the active cathode particles, which are the fundamental building blocks for the energy reservoir, it is a consensus that these structural and chemical defects could have a profound impact on the battery performance. An in-depth understanding of the underlying mechanisms could critically inform the cathode material engineering, which would have a tremendous potential but remains a daunting challenge at present. In this work, we tackle this question by studying LiCoO 2 (LCO) with trace doping of Ti, which exhibits a low solubility in the LCO layered lattice. Additionally, we observed the spontaneous and heterogeneous segregation of the dopant (Ti) across a wide range of length scales. In addition to the modification of the particle surface and the buried grain boundaries within the particle, we reveal that the Ti doping has induced a significant amount of lattice distortions, which, in turn, promotes the robustness of the LCO lattice at high state of charge (above 4.5V). Our result formulates a multi-scale defect engineering strategy that could be applicable to the synthesis of a broad range of energy materials for applications in batteries and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Capturing Surface Coverage Effects in Heterogeneous Catalysis

Adsorbate–adsorbate lateral interactions at relevant surface coverages have a significant effect on chemical kinetics, thereby influencing the activity of a heterogeneous catalyst. Coverage-dependent kinetic and thermodynamic parameters therefore must be included in studies of such complex systems to properly predict the turnover frequencies and kinetic trends. Thus, it becomes extremely important to accurately capture the strength of lateral interactions between neighboring species under realistic reaction conditions. In this Perspective, we discuss the various existing computational and experimental methods for determining adspecies coverage and configurational effects. The choice of the tools and methods employed in such studies depends on factors such as time, length scales, computational cost, the presence of solvents, and reaction conditions. The applications of each method and the respective challenges are also discussed here. As a result, we discuss the recent developments and future of the state-of-the-art for inclusion of surface coverage and configuration into a holistic picture for accurate predictions of catalytic behavior.

09 BIOMASS FUELS↗
DOE OSTI2020

Water Freezes at Near-Zero Temperatures Using Carbon Nanotube-Based Electrodes under Static Electric Fields

Although static electric fields have been effective in controlling ice nucleation, the highest freezing temperature ( T f ) of water that can be achieved in an electric field ( E ) is still uncertain. In this study, we performed a systematic study of the effect of an electric field on water freezing by varying the thickness of a dielectric layer and the voltage across it in an electrowetting system. Results show that T f first increases sharply with E and then reaches saturation at –3.5 °C after a critical value E of 6 × 10 6 V/m. Using classical heterogeneous nucleation theory, it is revealed that this behavior is due to saturation in the contact angle of the ice embryo with the underlying substrate. Finally, we show that it is possible to overcome this freezing saturation by controlling the uniformity of the electric field using carbon nanotubes. We achieve a T f of –0.6 °C using carbon nanotube-based electrodes with an E of 3 × 10 7 V/m. This work sheds new light on the control of ice nucleation and has the potential to impact many applications ranging from food freezing to ice production.

25 ENERGY STORAGE↗
DOE OSTI2020

Suppressing Cation Migration in Triple-Cation Lead Halide Perovskites

Ion migration represents an intrinsic instability of metal halide perovskite solar cells. In this work, we show that triple-cation FA x MA y Cs 1–x–y PbI 3 [FA + = (NH 2 ) 2 CH + , MA + = CH 3 NH 3 + ] active layers with mixed orthorhombic, post-perovskite (δ ortho -CsPbI 3 ), and cubic perovskite (α) phases (i.e., α/δ-phase FA x MA y Cs 1–x–y PbI 3 ) exhibit improved cation stability against applied bias relative to pure α-phase perovskites (i.e., FA 0.85 Cs 0.15 PbI 3 and FA 0.76 MA 0.15 Cs 0.09 PbI 3 ). Infrared photothermal heterodyne imaging and time-of-flight secondary ion mass spectrometry are used to visualize exclusive α-phase perovskite lateral device A + cation accumulation (depletion) at perovskite negative (positive) electrode interfaces. The resulting compositional heterogeneities lead to degradation. Operational stability testing of solar cells reveals similar degradation behavior; α/δ-phase FA x MA y Cs 1–x–y PbI 3 lateral devices/solar cells, by contrast, show improved stabilities. Enhanced α/δ-FA x MA y Cs 1–x–y PbI 3 stability is rationalized by δortho-phase inclusions, acting as barriers through which A + cations do not easily migrate. This study thus provides new insights into cation migration in FA x MAyCs 1–x–y PbI 3 perovskites and suggests a materials design strategy toward suppressing cation instabilities in hybrid perovskites.

14 SOLAR ENERGY↗
DOE OSTI2026

Algebraic Multigrid with Filtering: An Efficient Preconditioner for Interior Point Methods in Large-Scale Contact Mechanics Optimization

Large-scale contact mechanics simulations are crucial in many engineering fields such as structural design and manufacturing. In the frictionless case, contact can be modeled by minimizing an energy functional; however, these problems are often nonlinear, nonconvex, and increasingly difficult to solve as mesh resolution increases. In this work, we employ a Newton-based interior-point (IP) filter line-search method, an effective approach for large-scale constrained optimization. While this method converges rapidly, each iteration requires solving a large saddle-point linear system that becomes ill-conditioned as the optimization process converges, largely due to IP treatment of the contact constraints. Such ill-conditioning can hinder solver scalability and increase iteration counts with mesh refinement. Here, to address this, we introduce a novel preconditioner, algebraic multigrid with filtering (AMGF), tailored to the Schur complement of the saddle-point system. Building on the classical AMG solver, commonly used for elasticity, we augment it with a specialized subspace correction that filters near null space components introduced by contact interface constraints. Through theoretical analysis and numerical experiments on a range of linear and nonlinear contact problems, we demonstrate that the proposed solver achieves mesh independent convergence and maintains robustness against the ill-conditioning that notoriously plagues IP methods. These results indicate that AMGF makes contact mechanics simulations more tractable and broadens the applicability of Newton-based IP methods in challenging engineering scenarios. More broadly, AMGF is well suited for problems, optimization or otherwise, where solver performance is limited by a low-dimensional subspace, such as those arising from localized constraints, interface conditions, or model heterogeneities. This makes the method widely applicable beyond contact mechanics and constrained optimization.

Mathematics and Computing↗
NASA NTRS1996

Computer Modeling of Non-Isothermal Crystallization

A realistic computer model for simulating isothermal and non-isothermal phase transformations proceeding by homogeneous and heterogeneous nucleation and interface-limited growth is presented. A new treatment for particle size effects on the crystallization kinetics is developed and is incorporated into the numerical model. Time-dependent nucleation rates, size-dependent growth rates, and surface crystallization are also included. Model predictions are compared with experimental measurements of DSC/DTA peak parameters for the crystallization of lithium disilicate glass as a function of particle size, Pt doping levels, and water content. The quantitative agreement that is demonstrated indicates that the numerical model can be used to extract key kinetic data from easily obtained calorimetric data. The model can also be used to probe nucleation and growth behavior in regimes that are otherwise inaccessible. Based on a fit to data, an earlier prediction that the time-dependent nucleation rate in a DSC/DTA scan can rise above the steady-state value at a temperature higher than the peak in the steady-state rate is demonstrated.

Kelton, K. F.↗
DOE OSTI2025

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗