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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Physics-based Models, Machine Learning, and Experiment: Towards Understanding Complex Electrode Degradation

Degradation phenomena in Li-ion batteries are highly complex, coupled, and sensitive to use history and operating conditions. In this study, we show how tracking model parameters in continuum-level physics-based models, expedited by machine learning, can be useful in testing hypotheses for degradation mechanisms. An exemplary analysis using this approach is presented for a set of lithium trivanadate ( L i x V 3 O 8 ) cathodes cycled over a range of current rates. A simple cell revival process is combined with the parameter estimates over the course of cycling to extract valuable insights into cathode evolution and eliminate hypothesized degradation mechanisms for these cathodes. The presented approach is expected to be broadly applicable for degradation analysis of other electrodes.

25 ENERGY STORAGE↗
DOE OSTI2020

First-principles Modeling and Design of Solid-State Interfaces for the Protection and Use of Lithium Metal Anodes

Li-ion batteries are one of the most advanced energy storage technologies in use today. Li-ion batteries are used in a multitude of applications ranging from consumer electronics, medical devices, sensors and grid storage. However, improving the capacity and energy density delivered by current Li-ion technology requires advanced materials research into novel chemical systems. In this project we have focused particularly in the use of solid-state electrolytes with lithium metal electrodes. Research into all solid-state batteries (ASSB) with Li metal electrodes has significantly expanded in recent years, however most studies reported experimental findings, which left substantial room for theoretical and modeling work as a tool to understand and determine design principles allowing reliable and safe use of ASSBs with Li metal. Among the remaining obstacles preventing reliable use of ASSBs with a Li metal electrode, the stability of the interface between the solid electrolyte and Li metal, and the propagation/dendrite formation of Li metal and resulting mechanical degradation of the electrolyte are key phenomenon that are yet to be fully understood. In the current project we have addressed these two coupled phenomena using first principles calculations and mesoscale continuum modeling. We have obtained chemical and electrochemical stability windows for several solid electrolyte materials. Additionally, from mathematical and numerical modeling of Li protrusion and dendrite initiation during plating and stripping we have determined design criteria in terms of chemical, electrochemical, and mechanical properties and operating conditions for which stable deposition can occur. We also considered the effects of mixed electronic-ionic conduction in solid electrolytes, which has more recently been suggested as another important mechanism involved in ASSB failure. Throughout our work we have successfully addressed important questions necessary for the use of ASSB’s. We have determined guiding principles for materials properties and operating conditions necessary to operate ASSB’s. And have proposed novel solid electrolyte materials with predicted chemical stability an ionic conductivity. Although this represents significant progress in our understanding, open questions remain in order to fully develop reliable and safely operate ASSBs with Li metal. Future work, building on this project will require further experimental, theoretical and simulation efforts to address remaining questions.

25 ENERGY STORAGE↗
DOE OSTI2021

A data-driven peridynamic continuum model for upscaling molecular dynamics

Nonlocal models, including peridynamics, often use integral operators that embed lengthscales in their definition. However, the integrands in these operators are difficult to define from the data that are typically available for a given physical system, such as laboratory mechanical property tests. In contrast, molecular dynamics (MD) does not require these integrands, but it suffers from computational limitations in the length and time scales it can address. To combine the strengths of both methods and to obtain a coarse-grained, homogenized continuum model that efficiently and accurately captures materials’ behavior, we propose a learning framework to extract, from MD data, an optimal Linear Peridynamic Solid (LPS) model as a surrogate for MD displacements. To maximize the accuracy of the learnt model we allow the peridynamic influence function to be partially negative, while preserving the well-posedness of the resulting model. To achieve this, we provide sufficient well-posedness conditions for discretized LPS models with sign-changing influence functions and develop a constrained optimization algorithm that minimizes the equation residual while enforcing such solvability conditions. This framework guarantees that the resulting model is mathematically well-posed, physically consistent, and that it generalizes well to settings that are different from the ones used during training. We illustrate the efficacy of the proposed approach with several numerical tests for single layer graphene. Our two-dimensional tests show the robustness of the proposed algorithm on validation data sets that include thermal noise, different domain shapes and external loadings, and discretizations substantially different from the ones used for training.

homogenization↗
DOE OSTI2023

Eulerian finite element simulations of the drop weight impact test with a dislocation Density-based continuum model

During a drop weight impact test, the kinetic energy of the falling weight is transferred into the sample resting on the anvil. The plastic deformation in the sample is an important mechanism for the dissipation of the input kinetic energy. We use Eulerian finite element analysis to simulate the deformation and temperature evolution in a 1,3,5-trinitro-1,3,5-triazine (RDX) sample consisting of multiple crystals. In Eulerian finite element simulations, the mesh moves relative to the material. After every change of position between the mesh and the material, the state variables are interpolated to the new mesh position, i.e., advection. In an effort to reduce the advection errors, we use a rate form of a dislocation density-based continuum model by Luscher et al. Here, the simulations predict localization of plastic deformation, and plastic dissipation as a significant source of heat generation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Coordinated Multiscale Modeling and Synthesis of Novel Nanostructured Composite Membranes for Solar Fuels Generation (Final Report)

Generation of carbon-based liquid fuels from reduction of CO 2 using solar energy requires the development of improved membranes that provide good ionic conductivity and mechanical properties while minimizing the crossover of gases and reduction products. Using closely coordinated multiscale modeling, synthesis and characterization studies we propose to investigate and develop novel nanostructured composite membranes with applications to conversion of carbon dioxide to storable chemical fuels. The envisioned proton exchange membranes (PEMs) will be based on a support of self- assembling polymer-modified nanoparticles with controllable porosity and tortuosity. The use of a nanoparticle support will provide control of transport and mechanical properties of the membranes. Tuning the copolymer modification of nanoparticles (polymer architectures, brush grafting density) will allow to optimize the ion (proton) transport via the Grotthuss mechanism through narrow hydrated channels while minimizing crossover of gases and reaction products due to the high density of the grafted brush and use of a non-ionic conducting glassy polymers to fill spaces between polymer-grafted nanoparticles. In Phase I synthesis of the copolymers and their attachment to the nanoparticle support will be guided by multiscale simulations that include atomistic molecular dynamics and continuum-level transport simulations. The former will include reactive and non-reactive atomistic simulations that will provide key insight into nanoscale polymer morphology and ion/molecular transport mechanisms need to optimize the copolymer structure. The latter will provide insight into the role of nanoparticle self-assembly on the global transport of ionic and molecular species. The proton conduction and CO 2 /methanol permeability of the membranes will be experimentally characterized as well as simulated and will be correlated with morphology and polymer structure. Prototypes of optimal membranes will be fabricated and characterized at the end of the project. Successful development of improved nanostructured composite PEMs and demonstration of the simulation-guided materials-by-design paradigm will result in our ability to design and synthesize membranes for a wide variety of solar fuels generation and related electrochemical applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Metasurfaces with Multipolar Resonances and Enhanced Light–Matter Interaction

Metasurfaces, composed of engineered nanoantennas, enable unprecedented control over electromagnetic waves by leveraging multipolar resonances to tailor light–matter interactions. This review explores key physical mechanisms that govern their optical properties, including the role of multipolar resonances in shaping metasurface responses, the emergence of bound states in the continuum (BICs) that support high-quality factor modes, and the Purcell effect, which enhances spontaneous emission rates at the nanoscale. These effects collectively underpin the design of advanced photonic devices with tailored spectral, angular, and polarization-dependent properties. This review discusses recent advances in metasurfaces and applications based on them, highlighting research that employs full-wave numerical simulations, analytical and semi-analytic techniques, multipolar decomposition, nanofabrication, and experimental characterization to explore the interplay of multipolar resonances, bound and quasi-bound states, and enhanced light–matter interactions. A particular focus is given to metasurface-enhanced photodetectors, where structured nanoantennas improve light absorption, spectral selectivity, and quantum efficiency. By integrating metasurfaces with conventional photodetector architectures, it is possible to enhance responsivity, engineer photocarrier generation rates, and even enable functionalities such as polarization-sensitive detection. The interplay between multipolar resonances, BICs, and emission control mechanisms provides a unified framework for designing next-generation optoelectronic devices. This review consolidates recent progress in these areas, emphasizing the potential of metasurface-based approaches for high-performance sensing, imaging, and energy-harvesting applications.

Kerker effect↗
DOE OSTI2024

Fracture Dynamics in Silicon Anode Solid-State Batteries

Solid-state batteries (SSBs) with silicon anodes could enable improved safety and energy density compared to lithium-ion batteries. However, degradation arising from the massive volumetric changes of silicon anodes during cycling is not well understood in solid-state systems. Here, we use operando X-ray computed microtomography to reveal micro- to macro-scale chemo-mechanical degradation processes of silicon anodes in SSBs. Mud-type channel cracks driven by biaxial tensile stress form across the electrode during delithiation. We also find detrimental cracks at the silicon/ solid electrolyte interface that form due to local reaction competition between neighboring domains of different sizes. Continuum phase-field damage modeling quantifies stress-driven channel cracking and shows that the lithiated silicon stress state is critical for determining the extent of interfacial fracture. This work reveals the mechanisms that govern SSBs compared to conventional lithium-ion batteries and provides guidelines for engineering chemomechanically resilient electrodes for high-energy batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Mean-field control for efficient mixing of energy loads

In this work, we pose an engineering challenge of controlling an ensemble of energy devices via coordinated, implementation-light, and randomized on/off switching as a problem in nonequilibrium statistical mechanics. We show that mean-field control with nonlinear feedback on the cumulative consumption, assumed available to the aggregator via direct physical measurements of the energy flow, allows the ensemble to recover from its use in the demand response regime, i.e., transition to a statistical steady state, significantly faster than in the case of the fixed feedback. Moreover when the nonlinearity is sufficiently strong, one observes the phenomenon of “super-relaxation,” where the total instantaneous energy consumption of the ensemble transitions to the steady state much faster than the underlying probability distribution of the devices over their state space, while also leaving almost no devices outside of the comfort zone.

25 ENERGY STORAGE↗
DOE OSTI2022

A parallel discrete dislocation dynamics/kinetic Monte Carlo method to study non-conservative plastic processes

Non-conservative processes play a fundamental role in plasticity and are behind important macroscopic phenomena such as creep, dynamic strain aging, loop raft formation, etc. In the most general case, vacancy-induced dislocation climb is the operating unit mechanism. While dislocation/vacancy interactions have been modeled in the literature using a variety of methods, the approaches developed rely on continuum descriptions of both the vacancy population and its fluxes. However, there are numerous situations in physics where point defect populations display heterogeneous concentrations and/or non-smooth kinetics. Here, a kinetic Monte Carlo (kMC) approach for modeling vacancy transport in response to arbitrary stress fields is used. Vacancies are treated as point particles and are coupled to the dislocation substructure representing a deformed material via an advection term defined by the local stress gradients. The stress fields and the dislocation substructure are evolved using a discrete dislocation dynamics (DDD) module. To extend the coupled model to the treatment of large systems, we have implemented it in the massively-parallel DDD code ParaDiS. To avoid numerical incompatibilities associated with merging deterministic (DDD) and stochastic (kMC) integration algorithms, we cast the entire elasto-plastic-diffusive problem within a single stochastic framework, taking advantage of a parallel kMC algorithm to evolve the system as a single event-driven process. The large-scale implementation enables the study of the evolution of a variety of dislocation-defect scenarios governed by non-conservative transport kinetics. After carrying out an exhaustive numerical and computational analysis of our parallel algorithm, we show results that emphasize situations where inhomogeneous vacancy dynamics are of relevance, and compare discrete kinetics to continuum solutions for several cases.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Chemo‐Mechanical Coupling in Hydrogels: Dynamics in the Diffusion‐Limited Regime

Hydrogels are characterized by substantial volume changes in response to external stimuli, making them promising candidates for developing smart materials with enhanced adaptability and responsiveness. By integrating chemical reactions, hydrogels acquire dynamic and tunable responsiveness to external stimuli through chemo‐mechanical coupling, expanding their potential in emerging applications. However, capturing their transient behavior remains challenging due to the complex interplay of chemical reactions, solvent transport, and polymer network deformation. Classical theories capture equilibrium swelling but fail to describe time‐dependent phenomena. To address this, a time‐dependent continuum model is developed that explicitly couples these processes. Volume phase transition in hydrogels with homogeneous chemical reactions is investigated, then the effects of reaction kinetics on these transitions are analyzed. The coupling of these mechanisms is further explored through a study of transient mechanical instabilities. To illustrate the impact of distinct reaction and diffusion timescales, a photo‐active gripper is studied for robotic applications. Finally, a photo‐active microswimmer that exhibits non‐reciprocal motion is proposed to highlight the solvent diffusion for locomotion at the micro‐ and nano‐ scales. The work establishes that transient dynamics of chemo‐mechanical hydrogels generate functions not accessible by steady state models and provides a predictive platform for designing adaptive materials in emerging applications.

chemo-mechanical coupling↗
DOE OSTI2022

Discovery of multimechanisms of screw dislocation interaction in bcc iron from open-ended saddle point searches

Dislocation motion and interactions determine mechanical properties in body-centered cubic (bcc) metallic materials. However, studying mechanisms for the screw dislocation interaction is fundamentally challenging since many underlying processes involve mesotimescales and atomistic resolution, currently inaccessible by either experimental techniques or continuum theoretical methods. Here, in this paper, we develop a computational capability based on self-evolving atomistic kinetic Monte Carlo (SEAKMC) to sample the critical events and saddle point energies related to screw dislocations and their junctions. The method is first validated by calculating the stress dependence of Peierls barriers and formation energies of kink pairs and cross-slip kink pairs on a single screw dislocation in bcc iron. Then the method is applied to a binary junction of a pair of intersecting screw dislocations, the structure of which is crucial for low-temperature plastic deformation. We identify three important mechanisms: coplanar cross-slipping, jog-pinning, and a previously unknown unzipping mechanism during the evolution of the binary junction. The mechanisms are then further validated using classical molecular dynamics simulations. The computational capability developed in this paper provides an effective tool to evaluate screw dislocation related thermally activated events in complex stress conditions. The mechanisms discovered in this paper provide critical insights into temperature dependence of the anomalous slip, a breakdown of the Schmidt law, during the plastic deformation in bcc iron and can be generalized to other bcc metals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bandgap analysis and carrier localization in cation-disordered ZnGeN 2

The bandgap of ZnGeN 2 changes with the degree of cation site disorder and is sought in light emitting diodes for emission at green to amber wavelengths. By combining the perspectives of carrier localization and defect states, we analyze the impact of different degrees of disorder on electronic properties in ZnGeN 2 , addressing a gap in current studies, which largely focus on dilute or fully disordered systems. The present study demonstrates changes in the density of states and localization of carriers in ZnGeN 2 calculated using bandgap-corrected density functional theory and hybrid calculations on partially disordered supercells generated using the Monte Carlo method. We use localization and density of states to discuss the ill-defined nature of a bandgap in a disordered material and identify site disorder and its impact on the structure as a mechanism controlling electronic properties and potential device performance. Decreasing the order parameter results in a large reduction of the bandgap. The reduction in bandgap is due, in part, to isolated, localized states that form above the valence band continuum associated with nitrogen coordinated by more zinc than germanium. The prevalence of defect states in all but the perfectly ordered structure creates challenges for incorporating disordered ZnGeN 2 into optical devices, but the localization associated with these defects provides insight into the mechanisms of electron/hole recombination in the material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantum Magnetic Properties and Metal‐to‐Insulator Transition in Chemically Doped Calcium Ruthenate Perovskite

Ruthenates provide a comprehensive platform to study a plethora of novel properties, such as quantum magnetism, superconductivity, and magnetic fluctuation mediated metal–insulator transition (MIT). Herein, an overview of quantum mechanical phenomenology in calcium ruthenium oxide with varying compositions is provided. While the stoichiometric composition of exhibits non‐fermi liquid (FL) behavior with quasi‐criticality, chemically doped compounds depict prominent signatures of quantum magnetic fluctuations at low temperature that in some cases are argued to mediate in metal–insulator transition. In the case of cobalt‐doped , an unusual continuum fluctuation is found to persist deep inside the glassy phase of the material. These observations reflect the richness of the ruthenate research platform in the study of quantum magnetic phenomena of fundamental importance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The roles of three-nucleon force and continuum coupling in mirror symmetry breaking of oxygen mass region

With both three-nucleon force and continuum coupling included, we have developed a self-consistent ab initio Gamow shell model within the Gamow Hartree-Fock (GHF) basis obtained by the realistic interaction itself. With the chiral two-nucleon N 3 LO and three-nucleon N 2 LO interactions, the Gamow shell model has been applied to the mirror systems of Z = 8 neutron-rich isotopes and N = 8 proton-rich isotones, giving good agreements with data in binding energies, dripline positions and excitation spectra. The GHF calculated that the 0 ds/2 , 1 S1/2 and 1 p3/2 orbitals are resonances. The resonance states and their interplay with nonresonant continua play a crucial role in the descriptions of nuclei around driplines. Excitation spectra and Thomas-Ehrman shifts observed can be better described when both three-nucleon force and continuum coupling are considered in calculations. The three-nucleon force and continuum coupling produce a combined effect on the Thomas-Ehrman shift, e.g., for the 1/2 + resonance level of 19Na. The calculations help the understandings of related nuclear astrophysical processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Critique on “A Revisit of Navier-Stokes Equation”

In a recently published work (Sheng, 2020), Sheng identified inconsistencies in the concepts and principles leading to the Navier–Stokes equations and proposed a new asymmetric “friction tensor” to resolve these inconsistencies. We show that this friction tensor can be interpreted as the non-isotropic part of a vorticity-influenced viscous stress tensor following the analysis in Berdahl and Strang (1986). The asymmetric stress tensor however violates the principles of mechanical equilibrium in fluid flows that are free of external or body couples and is therefore non-physical in classical continuum hydrodynamics. We refute the arguments in favour of the asymmetric stress tensor in Sheng (2020) whilst also demonstrating that the friction tensor leads to the incorrect form of the Navier–Stokes equations in non-Cartesian co-ordinates and its ability to recover the correct governing equations in Cartesian co-ordinates is fortuitous.

asymmetric↗
DOE OSTI2025

Machine learning-enabled multiscale modeling of mechanical deformation of aluminum and Al-SiC nanocomposites

A machine learning-enabled multiscale framework is developed for modeling the mechanical response of both pure metal and nanoparticle-reinforced metal matrix nanocomposites (MMNCs). Using aluminum–silicon carbide (Al-SiC) as an example MMNC, atomistic simulations reveal three distinct deformation mechanisms (i.e., defect-free, dislocation-based, and interface separation) governed by the interfaces between the Al matrix and SiC nanoparticles. As compared with single crystal Al, the lattice undergoes a more abrupt failure once the dislocation network becomes extensive and void nucleation initiates, whereas in Al-SiC, nanoparticle interfaces enable a more gradual progression of damage. These mechanisms are captured through a combined classification-regression neural network surrogate model that bridges atomic-scale insights with continuum-scale finite element analysis. Machine learning-enabled multiscale modeling of pure Al accurately predicted strain localization and confirmed by in-situ scanning electron microscopic tensile testing on perforated Al specimens. This study underscores the promise of integrating physics-informed machine learning with hierarchical modeling to capture the interface dominated phenomena and guide the design of advanced MMNCs.

Al-SiC↗
DOE OSTI2022

Coalescence dynamics of prismatic dislocation loops due to vacancy supersaturation

Recovery processes in metals with a high defect concentration are at the heart of a structural alloy's usability in engineering applications. However, such processes take place via nonconservative mechanisms mediated by point defect diffusion and are governed by their interactions with the underlying microstructure. Indeed, one of the main challenges in studying recovery processes is their intrinsic multiscale complexity, which often negates the direct use of experimental techniques. Here, in this Research Letter, we study the mechanism of dislocation loop coalescence in metals by simulating the interaction dynamics between vacancies and prismatic loops using a stochastic framework that seamlessly bridges point defect kinetics with dislocation mechanics. Our simulations reveal two fundamental discoveries: first, that climb processes are governed by local fluctuations that are not captured by continuum elastodiffusion models, and, second, that prismatic loops create internal traps for vacancies, leading to the formation of rings around the perimeter of the loops that affect how coalescence takes place. Our results show an excellent agreement with in situ experimental observations of loop coalescence in Fe under irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

SU(n) and Quantum SU(n) Symmetries in Physical Systems [Slides]

Presence of SU(n) or other Lie group symmetry in a physical system is its powerful, usually underutilized property. In many cases it allows for finding analytical solutions to nonlinear differential equations describing this system. Power of the method is presented on diversified examples from mathematical physics: Lie-group symmetries in finding solutions of generalized, multidimensional theory of gravity; analytical Dirac–equation solutions for description of conducting polymers; stability of qubit states in quantum computers; spatial defects in condensed matter; reconstruction of 3D object from its 2D tomographic image; significant improvement of numerical solutions stability for Euler equations. The next question after obtaining such Lie group symmetric solution is: does a generalized solution with appropriate quantum group symmetry exists for the given physical system, and if yes what is the physical meaning of the deformation parameter q introduced by such solution. In many cases it can be identified. Any SU(n) solution is by its nature singular, assuming a perfect symmetry of the physical system discussed. Such solution gives a powerful insight to theoretical physics, yet the assumption may be too demanding for experimental applications. Deformation parameter q from a quantum group symmetry allows for a continuum of solutions, more applicable to experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗