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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Lower length scale informed improvements to Bison U-Pu-Zr fuel swelling model

Due to renewed interest in metallic fuels from the U-(Pu)-Zr material system, significant improvements have recently been made to BISON's capability to simulate metallic fuel, particularly in the area of swelling. In this report, lower length scale simulations that have been conducted to inform the engineering-scale models in BISON during FY20 are described. For the high-temperature regions of the fuel that are dominated by the $\gamma$ phase of U-(Pu)-Zr, two new models for swelling have implemented in BISON. Phase-field simulations were conducted to calculate parameters for these and other BISON models that control when gaseous swelling ceases and fission gas release begins. For the low-temperature regions of the fuel dominated by the phase of uranium, microstructurally resolved simulations of pore growth and crystal deformation were performed to understand the effect of irradiation-generated crystal shape changes. Conformally meshed microstructures with pores were simulated with a crystal plasticity model and with a burnup eigenstrain model. Plastic deformation will not cause pore size to increase; burnup eigenstrain (irradiation-induced crystal shape changes) will increase the volume of existing porosity and cause it to become anisotropic in shape. Additional model development work for early-stage fission gas cluster/bubble formation in the $\gamma$ phase were performed, by coupling with defect clustering within cluster dynamics framework. Sensitivity analysis were conducted to identify the critical thermo-kinetic parameters needed for rigorous assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Machine learning assisted derivation of minimal low-energy models for metallic magnets

Abstract We consider the problem of extracting a low-energy spin Hamiltonian from a triangular Kondo Lattice Model (KLM). The non-analytic dependence of the effective spin-spin interactions on the Kondo exchange excludes the use of perturbation theory beyond the second order. We then introduce a Machine Learning (ML) assisted protocol to extract effective two- and four-spin interactions. The resulting spin model reproduces the phase diagram of the original KLM as a function of magnetic field and single-ion anisotropy and reveals the effective four-spin interactions that stabilize the field-induced skyrmion crystal phase. Moreover, this model enables the computation of static and dynamical properties with a much lower numerical cost relative to the original KLM. A comparison of the dynamical spin structure factor in the fully polarized phase computed with both models reveals a good agreement for the magnon dispersion even though this information was not included in the training data set.

Sharma, Vikram (ORCID:0000000189105519)↗
DOE OSTI2026

Quantum Filtering and Analysis of Multiplicities in Eigenvalue Spectra

Fine-grained spectral properties of quantum Hamiltonians, including both eigenvalues and their multiplicities, provide useful information for characterizing many-body quantum systems as well as for understanding phenomena such as topological order. Extracting such information with small additive error is #BQP-complete in the worst case. In this work, we introduce QFAMES (quantum filtering and analysis of multiplicities in eigenvalue spectra), a quantum algorithm that efficiently identifies clusters of closely spaced dominant eigenvalues and determines their multiplicities under physically motivated assumptions, which allows us to bypass worst-case complexity barriers. QFAMES also enables the estimation of observable expectation values within targeted energy clusters, providing a powerful tool for studying quantum phase transitions and other physical properties. We validate the effectiveness of QFAMES through numerical demonstrations, including its applications to characterizing quantum phases in the transverse-field Ising model and estimating the ground-state degeneracy of a topologically ordered phase in the two-dimensional toric code model. We also generalize QFAMES to the setting of mixed initial states. Our approach offers rigorous theoretical guarantees and significant advantages over existing subspace-based quantum spectral analysis methods, particularly in terms of the sample complexity and the ability to resolve degeneracies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2023

Reports From EXPORTS Modeling and Data-Mining Activities

EXPORTS -EXport Processes in the Ocean from RemoTe Sensing is NASA’s large field campaign focusing on development of a predictive understanding of the export, fate and carbon cycle impacts of the global net primary production. This co-funded program (NSF, private funding1, and international participation) was conceived in 2013, with EXPORTS Science plan published in 2016 (Siegel et al 2016, EXPORTS Writing Team 2015) and its implementation plan finalized in 2016 (EXPORTS Science Definition Team 2016). More details are presented in Siegel et al (2021). EXPORTS campaign is structured as a multiyear effort (Figure 1). It started with “Pre-EXPORTS” modeling and data-mining activity followed by a first phase with two major field programs and a second synthesis and modeling phase. The “Pre-EXPORTS” projects, total of 6 of them (Table 1), funded under A.3 Ocean Biology and Biogeochemistry 2015 call, helped to plan the field campaign (Resplandy et al 2019, Rousseaux & Gregg 2017), and supporting further global synthesis with datasets mined from the literature (e.g. Bisson et al (2020), Bisson et al (2018), Kramer and Siegel (2019)), directly responding to objectives outlined in Science Plan (see section 6 in Team (2015)) and Implementation team (see Figure 1 in Team (2016)). This document presents a compilation of the final reports of the Pre-EXPORTS funded projects, in hope of synthesizing the outcomes, and insuring the legacy of this program. Each of these reports contains a list of published papers, and reader should refer to them to see results in details.

Brandi J. McCarty↗
DOE OSTI2022

Competition of magnetocrystalline anisotropy of uranium layers and zigzag chains in UNi 0.34 Ge 2 single crystals

Structural and thermodynamic properties of single-crystalline UNi 1-x Ge 2 with x = 0.66 have been investigated by measuring magnetization, specific heat, and thermal expansion over a wide range of temperatures and magnetic fields. The measurements revealed the emergence of a long-range antiferromagnetic ordering of uranium magnetic moments below the Néel temperature T N = 45.5 (1) K and the existence of two easy axes in the studied compound, namely b and c, which correspond to the planes of the uranium zig-zag chains. A magnetic field applied along these two crystallographic directions induces in the system a first-order metamagnetic phase transition (from antiferromagnetic to field-polarized paramagnetism), and the width of the magnetic hysteresis associated with that transition reaches as much as 40 kOe at the lowest temperatures. A magnetic phase diagram developed from the experimental data showed that the metastable region associated with that magnetic hysteresis forms a funnel that narrows toward the N´eel point in a zero magnetic field. The four-layer Ising model has successfully predicted the colinear antiferromagnetic structure in UNi 0.34 Ge 2 (known from earlier reports), its magnetic phase diagram, and temperature and field variations of its magnetization. Moreover, it suggests that the first-order phase transition extends down to zero magnetic field, although it is barely detectable in the experiments performed in low magnetic fields. According to this model, the second-order phase transition occurs in the compound only in zero field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Recent progress in the phase-field dislocation dynamics method

The phase-field dislocation dynamics (PFDD) method, originated in 2002, is a continuum dislocation model that uses order parameters to describe dislocation slips in crystalline materials. In the past two decades, and especially since it was last reviewed in 2016, PFDD was advanced significantly in terms of the mathematical formulation, numerical implementation, and applicability. The main purpose of this short review is to summarize recent progress made to improve the energy functional formulation and numerical techniques of PFDD as well as its recent applications. Additionally, some recommendations for future work to further extend the PFDD method are presented.

36 MATERIALS SCIENCE↗
NASA NTRS2002

High-Fidelity Generalization Method of Cells for Inelastic Periodic Multiphase Materials

An extension of a recently-developed linear thermoelastic theory for multiphase periodic materials is presented which admits inelastic behavior of the constituent phases. The extended theory is capable of accurately estimating both the effective inelastic response of a periodic multiphase composite and the local stress and strain fields in the individual phases. The model is presently limited to materials characterized by constituent phases that are continuous in one direction, but arbitrarily distributed within the repeating unit cell which characterizes the material's periodic microstructure. The model's analytical framework is based on the homogenization technique for periodic media, but the method of solution for the local displacement and stress fields borrows concepts previously employed by the authors in constructing the higher-order theory for functionally graded materials, in contrast with the standard finite-element solution method typically used in conjunction with the homogenization technique. The present approach produces a closed-form macroscopic constitutive equation for a periodic multiphase material valid for both uniaxial and multiaxial loading. The model's predictive accuracy in generating both the effective inelastic stress-strain response and the local stress said inelastic strain fields is demonstrated by comparison with the results of an analytical inelastic solution for the axisymmetric and axial shear response of a unidirectional composite based on the concentric cylinder model, and with finite-element results for transverse loading.

Aboudi, Jacob↗
NASA NTRS2014

An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice

Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng/g for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng/g for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng/g. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90degN) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W/sq m and 0.18 (0.06-0.28) W/sq m in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W/sq m for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.

carbon↗
DOE OSTI2023

Exponential acceleration of macroscopic quantum tunneling in a Floquet Ising model

The exponential suppression of macroscopic quantum tunneling (MQT) in the number of elements to be reconfigured is an essential element of broken symmetry phases. This suppression is also a core bottleneck in quantum algorithms, such as traversing an energy landscape in optimization, and adiabatic state preparation more generally. In this work, we demonstrate exponential acceleration of MQT through Floquet engineering with the application of a uniform, high frequency transverse drive field. Using the ferromagnetic phase of the transverse field Ising model in one and two dimensions as a prototypical example, we identify three phenomenological regimes as a function of drive strength. For weak drives, the system exhibits exponentially decaying tunneling rates but robust magnetic order; in the crossover regime at intermediate drive strength, we find polynomial decay of tunnelling alongside vanishing magnetic order; and at very strong drive strengths both the Rabi frequency and time-averaged magnetic order are approximately constant with increasing system size. We support these claims with extensive full wavefunction and tensor network numerical simulations, and theoretical analysis. An experimental test of these results presents a technologically important and novel scientific question accessible on NISQ-era quantum computers.

Grattan, George↗
DOE OSTI2020

Comparative modeling of the disregistry and Peierls stress for dissociated edge and screw dislocations in Al

Many elementary deformation processes in metals involve the motion of dislocations. The planes of glide and specific processes dislocations prefer depend heavily on their atomic core structures. Atomistic simulations are desirable for dislocation modeling but their application to even sub-micron scale problems is in general computationally costly. Accordingly, continuum-based approaches, such as the phase-field microelasticity, phase-field dislocation dynamics (PFDD), generalized Peierls–Nabarro (GPN) models, and the concurrent atomistic–continuum (CAC) method, have attracted increasing attention in the field of dislocation modeling because they well represent both short-range cores interactions and long-range stress fields of dislocations. To better understand their similarities and differences, it is useful to compare these methods in the context of benchmark simulations and predictions. In this paper, we apply the CAC method and different PFDD variants – one of them is equivalent to a GPN model – to simulate an extended (i.e., dissociated) dislocation in Al with initially pure edge or pure screw character in terms of the disregistry. CAC and discrete forms of PFDD are also employed to calculate the Peierls stress. By conducting comprehensive convergence studies, we quantify the dependence of these measures on time/grid resolution and simulation cell size. Several important but often overlooked differences between PFDD/GPN variants are clarified. In conclusion, our work sheds light on the advantages and limitations of each method, as well as the path towards enabling them to effectively model complex dislocation processes at larger length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Predicting fracture behavior in single crystal nickel using a coupled crystal plasticity phase field damage approach

Understanding the fracture behavior of single crystal metals is critical for predicting material performance under mechanical loading. Here, in this study, we investigate the fracture characteristics of single crystal nickel tensile bars using a crystal plasticity coupled phase field damage (CP-PFD) model. Experimental tensile tests were conducted on 15 specimens spanning five crystallographic orientations and three thickness variants per orientation. The results revealed two distinct fracture modes: brittle fractures with 45-degree angled surfaces and ductile fractures characterized by significant necking. The CP-PFD model successfully replicated these fracture behaviors, demonstrating strong agreement with experimental observations. The model effectively predicted the strain at which necking and fracture occurred, as well as the orientation-dependent fracture mechanisms. By comparing experimental and simulated fracture surfaces, we establish the CP-PFD model as a robust tool for predicting single crystal behavior and damage evolution. This work provides insight into the microstructural dependence of fracture behavior and establishes a predictive framework for modeling orientation-dependent damage evolution in single-crystal nickel.

Crystal plasticity↗
NASA NTRS1995

Coupled Monte Carlo Probability Density Function/ SPRAY/CFD Code Developed for Modeling Gas-Turbine Combustor Flows

The success of any solution methodology for studying gas-turbine combustor flows depends a great deal on how well it can model various complex, rate-controlling processes associated with turbulent transport, mixing, chemical kinetics, evaporation and spreading rates of the spray, convective and radiative heat transfer, and other phenomena. These phenomena often strongly interact with each other at disparate time and length scales. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and evaporation in many practical combustion devices. Turbulence manifests its influence in a diffusion flame in several forms depending on how turbulence interacts with various flame scales. These forms range from the so-called wrinkled, or stretched, flamelets regime, to the distributed combustion regime. Conventional turbulence closure models have difficulty in treating highly nonlinear reaction rates. A solution procedure based on the joint composition probability density function (PDF) approach holds the promise of modeling various important combustion phenomena relevant to practical combustion devices such as extinction, blowoff limits, and emissions predictions because it can handle the nonlinear chemical reaction rates without any approximation. In this approach, mean and turbulence gas-phase velocity fields are determined from a standard turbulence model; the joint composition field of species and enthalpy are determined from the solution of a modeled PDF transport equation; and a Lagrangian-based dilute spray model is used for the liquid-phase representation with appropriate consideration of the exchanges of mass, momentum, and energy between the two phases. The PDF transport equation is solved by a Monte Carlo method, and existing state-of-the-art numerical representations are used to solve the mean gasphase velocity and turbulence fields together with the liquid-phase equations. The joint composition PDF approach was extended in our previous work to the study of compressible reacting flows. The application of this method to several supersonic diffusion flames associated with scramjet combustor flow fields provided favorable comparisons with the available experimental data. A further extension of this approach to spray flames, three-dimensional computations, and parallel computing was reported in a recent paper. The recently developed PDF/SPRAY/computational fluid dynamics (CFD) module combines the novelty of the joint composition PDF approach with the ability to run on parallel architectures. This algorithm was implemented on the NASA Lewis Research Center's Cray T3D, a massively parallel computer with an aggregate of 64 processor elements. The calculation procedure was applied to predict the flow properties of both open and confined swirl-stabilized spray flames.

Source record↗
DOE OSTI2024

Analysis of heat transfer and AuNPs-mediated photo-thermal inactivation of E. coli at varying laser powers using single-phase CFD modeling

In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and scientific progress. The intermediate aim of the work was to present the calibration of the model with respect to the gold nanorods experiment. The purpose of this work is to study the effect of initial concentration of E. coli bacteria, the design of the chamber and the laser power on heat transfer and inactivation of E. coli bacteria. Using the CFD simulation, the work combines three main concepts. 1. The conversion of laser light to heat has been described by a combination of three distinctive approximations: a- Discrete particle integration to take into account every nanoparticle within the system, b- Rayleigh-Drude approximation to determine the scattering and extinction coefficients and c- Lambert–Beer–Bourger law to describe the decrease in laser intensity across the AuNPs. 2. The contribution of the presence of E. coli bacteria to the thermal and fluid-dynamic fields in the microdevice was modeled by single-phase approach by determining the effective thermophysical properties of the water-bacteria mixture. 3. An approach based on a temperature threshold attained at which bacteria will be inactivated, has been used to predict bacterial response to temperature increases. The comparison of the thermal fields and temporal temperature changes obtained by the CFD simulation with those obtained experimentally confirms the accuracy of the light-heat conversion model derived from the aforementioned approximations. The results show a linear relationship between maximum temperature and variation in laser power over the range studied, which is in line with previous experimental results. It was also found that the temperature inside the microchamber can exceed 55 °C only when a laser power higher than 0.8 W is used, so bacterial inactivation begins. The experimental data allows to determinate the concentration of nanoparticles. This parameter is introduced into the mathematical model obtaining the same number of AuNPs. However, this assumption introduces a certain simplification, as in the mathematical model the distribution of nanoparticles is uniform. This work is directly connected to the use of gold nanoparticles for energy conversion, as well as the field of bacterial inactivation in microfluidic systems such as lab-on-a-chip. Presented mathematical and numerical models can be extended to the entire spectrum of wavelengths with particular use of white light in the inactivation of bacteria. This work represents a significant advancement in the field, as to the best of the authors’ knowledge, it is the first to employ a single-phase computational fluid dynamics (CFD) approach specifically combined with the thermal inactivation of bacteria. Moreover, this research pioneers the use of a numerical simulation to analyze the temperature threshold of photothermal inactivation of E. coli mediated by gold nanorods (AuNRs). The integration of these methodologies offers a new perspective on optimizing bacterial inactivation techniques, making this study a valuable contribution to both computational modeling and biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Anisotropic Cahn-Hilliard free energy and interfacial energies for binary alloys with pairwise interactions

The original Cahn-Hilliard derivation of the contribution of compositional inhomogeneity to the free energy of a binary alloy with pairwise interactions is extended to include higher-order inhomogeneity terms. For alloys on a cubic lattice, the coefficient of the first inhomogeneity is a second-rank tensor and reduces to a scalar, but it is shown that the second order and the third order inhomogeneity terms are weighted by fourth-rank and sixth-rank tensors, thus resulting in anisotropic contributions. Furthermore, each interaction shell generates a unique set of inhomogeneity coefficients that is determined by the set of vectors connecting an atom to its neighbors on that shell. These coefficients are calculated for fcc and bcc alloys with interactions up fourth nearest neighbors. Phase field simulations based on these extended Cahn-Hilliard free energies are performed to measure interface free energies along specific crystallographic directions as a function of temperature, and to obtain the equilibrium shape of precipitates. Interface free energies, and the resulting anisotropies, are compared to those obtained by discrete models and Monte Carlo simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Flux-Closure Domain Structures in Ferroelectric K 0.5 Na 0.5 NbO 3 Thin Films

Topological domain structures in ferroelectric materials have garnered increasing attention due to their intriguing physical properties and promising applications. While most existing topological structures in ferroelectric perovskite oxides originate from tetragonal or rhombohedral bulk phases, much less is understood about their counterparts in orthorhombic ferroelectrics. Here, in this work, we employ ferroelectric K 0.5 Na 0.5 NbO 3 (KNN) thin films as a model system and leverage phase-field simulations to theoretically predict the static structures and dynamic behaviors of three types of flux-closure domain configurations: in-plane (Type-I), out-of-plane (Type-II), and superdomain (Type-III) flux-closure structures. We systematically investigate the effects of finite size, misfit strains, and electrical boundary conditions on the formation and switching of these topological structures. For the Type-I structure, size reduction or small misfit strain facilitates a transition of the flux-closure pattern to polar vortices. Type-II structures emerge under open-circuit electrical boundary conditions of the film, forming at the junctions of specific domain walls with the film surface or the film–substrate interface. The formation mechanisms of these two flux-closure structures are rationalized from an energy perspective. We demonstrated switching capabilities of Type-II and Type-III structures by obtaining polarization–electric field hysteresis loops. Our simulations also reveal a reversible electric-field-induced transition between the orthorhombic and rhombohedral ferroelectric phases with a checkerboard domain pattern, during which the integrity of the flux-closure structure is preserved. These findings provide theoretical insights and practical guidance for identifying and manipulating topological structures in low-symmetry ferroelectrics, paving the way for developing energy-efficient microelectronic devices based on topological structures.

P-E loop↗
DOE OSTI2021

C-FOG: Life of Coastal Fog

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp . An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

58 GEOSCIENCES↗
DOE OSTI2019

Electrochemically-Driven Phase Transformations in Battery Compounds (Final Technical Report)

Ion-insertion compounds for advanced batteries frequently exhibit phase transformations as the concentration of the working ion varies. Under the large electrochemical driving forces inherent to practical use, systems are often driven far from equilibrium and exhibit phase transition behavior not seen in other materials. An improved understanding of phase transformation pathways in electrode materials upon cycling will lead to new materials design concepts and electrochemical duty cycle management strategies that improve capacity utilization at high charge/discharge rates, reduce voltage and capacity hysteresis, and extend battery life. The main goal of this project is to develop a predictive understanding of the phase transition behavior of battery compounds when electrochemically driven far from equilibrium through a combined experimental- theoretical approach. Research focuses on elucidating how the phase transition behaviors in a diverse group of selected model systems (olivines, lithium metal, etc.) are regulated by various factors including transformation strains, plasticity, metastable transformation pathways, electrode microstructure, surface reaction and ion diffusion kinetics, and what are the unique features of phase transitions in battery compounds. To this end, operando X-ray-based characterization techniques are applied to interrogate the structure and composition evolution of electrode materials and interfaces at nano- and meso-scales. Mesoscale modeling techniques such as phase-field simulation are employed to shed light on the experimental observations and establish a unified framework for describing phase transition behaviors in battery compounds.

25 ENERGY STORAGE↗