Search NASA⌕ Search

SEARCH · Search NASA

Results for “Spinodal decomposition”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modulating the Mixing Gibbs Free Energy to Enhance Solid–Liquid Phase Separation for High–Performance Organic Solar Cells

Organic solar cells (OSC) feature a hierarchical structure with the electron donor/acceptor layer sandwiched by anode and cathode, which raises the importance of controlling the molecular crystal orientation, domain size, and vertical distribution to facilitate the charge collection at electrodes. However, the similar conjugated backbone of donor/acceptor material and fast film–formation kinetics have led to spinodal–decomposition–orientated phase separation that result in the film presenting an intimately mixed morphology and random molecular orientation. To solve the issue, the mixing Gibbs free energy–triggered solid–liquid phase separation during the film formation process is enhanced by solidifying one component and solvating the other based on a liquid additive. Following the liquid evaporation process, a favorable vertical distribution is obtained. Meanwhile, the prolonged solvation process enlarges the domain size and assists the molecules to diffuse and orient properly, enabling better exciton/charge dynamics during the power conversion processes. As a result, the fabricated devices exhibit a fill factor over 80% and an efficiency of 18.72%, which is one of the top efficiencies for binary OSCs. In conclusion, insights and a methodology is provided here to manipulate the organic donor/acceptor phase separation in terms of mixing Gibbs free energy.

14 SOLAR ENERGY↗
DOE OSTI2026

Random 3D Interpenetrating Electrode Design for Energy Storage Applications

We introduce the concept of random interpenetrating electrode structures, inspired by spinodal decomposition, as a transformative approach for energy storage applications. While ordered architectures, such as double gyroids and Kelvin cell structures, have long been favored for their structural uniformity and surface area utilization, we demonstrate that random structures offer distinct advantages including shorter diffusion pathways, higher packing density, and enhanced reaction kinetics, particularly at low temperatures. Using a combination of computational and electrochemical analysis, we show that random architecture outperforms their ordered counterparts in scenarios where diffusion dominates. This work represents the first systematic exploration of random structures in energy storage, highlighting their potential to overcome limitations of traditional designs. However, challenges such as structural reproducibility and scalability remain, necessitating further investigation into fabrication techniques and material selection. By establishing a framework to optimize random electrode architectures, we provide critical insights into the interplay between geometry, diffusion, and reaction kinetics. This study not only introduces a new design principle for 3D electrodes but also opens pathways for next-generation energy storage systems that demand both high performance and adaptability to a range of operating conditions.

Materials science↗
DOE OSTI2020

Phase Inversion in a Two-phase, BCC+B2, Refractory High Entropy Alloy

A phenomenon of "phase inversion", presumably the first ever experimental evidence in metallic alloys, is shown in a refractory high entropy alloy (RHEA), Al0.5NbTa0.8Ti1.5V0.2Zr. Phase inversion in crystalline solid systems is driven by the differences in elastic modulus of the two phases. Quenching from a high-temperature single phase field, the RHEA exhibits a co-continuous mixture of a disordered BCC and an ordered B2 phase, that upon isothermal annealing at 600°C develops via spinodal decomposition into a continuous B2 matrix with discrete cuboidal BCC precipitates aligned along the <001> directions. Longer term annealing at 600°C results in the development of necking constrictions along the B2 channels, eventually pinching-off these channels and making the BCC phase continuous with discrete B2 precipitates. This inversion the process can be related to the simultaneous operation of two processes:(i) spheroidization of the initially discrete cuboidal BCC precipitates driven by a reduction in the total interface energy and (ii) an increase in the stiffness of the B2 phase, relative to the BCC phase, due to chemical composition changes during annealing, forcing the B2 regions to become discrete driven by the reduction in the total elastic strain energy.

Soni, Vishal↗
DOE OSTI2022

The effect of elastic anisotropy on the symmetry selection of irradiation-induced void superlattices in cubic metals

We report self-organized microstructures and patterns have been widely observed in non-equilibrium physical systems. In particular, irradiation in metals creates far-from-equilibrium environments, in which the competing dynamics of defect production and annihilation can lead to unique self-organized superlattice structures, e.g., void and gas bubble superlattices. From a physical point of view, the superlattice structures are dictated by the intrinsic symmetry breaking in the metals, i.e., anisotropy caused by the breaking of continuous rotational symmetry. In the literature, two distinctive anisotropies, elastic anisotropy and diffusion anisotropy of interstitials, have been proposed to be the origins of superlattice formation. However, it is still unclear which anisotropy dominates the symmetry selection of superlattice structures. In this paper, we study elastic anisotropy and its effect on the symmetry of void superlattices. By using theoretical analyses and phase field simulations, we show that elastic anisotropy in cubic metals can lead to either face-centered cubic or simple cubic superlattices depending on the Zener anisotropy ratio. The superlattices formed under this elastic anisotropy mechanism must form under the influence of spinodal decomposition, as the mechanism requires perturbations in the vacancy concentration field to develop into spatially-static concentration waves. We compare to existing work on symmetry selection in superlattices via diffusion anisotropy and to experimental observations, and we suggest that concentration wave development under the influence of elastic anisotropy is not the mechanism for symmetry selection during the formation of irradiation-induced void superlattices, but that diffusion anisotropy could be the dominant mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A phase-field model for void and gas bubble superlattice formation in irradiated solids

A phase-field model to simulate the formation of both void and gas bubble superlattices is derived from a grand potential functional, assuming 1D diffusion of self-interstitial atoms. The model is capable of accounting for superlattice formation by either a nucleation and growth or spinodal decomposition mechanism; in this work, we focus on the nucleation and growth mechanism, using a discrete nucleation approach in the phase-field model. In simulations of void formation, short aligned rows of voids were initially formed, followed by growth in the size of the aligned rows, and finally leading to superlattice formation, consistent with experimental observations. Void superlattice spacing as a function of model parameters was quantified. Increased nucleation rates led to smaller superlattice spacing, while increased vacancy diffusivity led to larger superlattice spacing. In simulations of gas bubble superlattice formation, superlattice spacing decreased with increasing gas atom flux, consistent with experimental observations. Here, simulations with increasing ratio of gas atom flux to vacancy-interstitial pair production led to increased superlattice spacing, which is inconsistent with experimental observations at high gas atom flux rates; this discrepancy is attributed to the fact that the model does not account for bound gas atom-vacancy pairs that may dominate at high gas flux rates.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In situ monitoring of microstructure evolution during thermal processing of uranium-zirconium alloys using laser-generated ultrasound

In this study, laser-generated ultrasound was used to monitor microstructure evolution during thermal processing of as-cast, polycrystalline binary uranium-zirconium metallic fuel alloys with compositions of U-20wt.%Zr (U-20Zr), U-50wt.%Zr (U-50Zr) and U-80wt.%Zr (U-80Zr). Ultrasonic waveforms were recorded during heating and cooling the samples from room temperature to >973 K and back. A phase transition temperature for all three compositions was estimated from the temperature at which an abrupt and rapid reduction in ultrasonic velocities was observed. Microstructural features on the length scale of tens of micrometers were inferred from the observation of scattering of ultrasonic waves by elastic heterogeneities above ~823 K in U-20Zr, while a hysteresis in the ultrasonic velocities of U-80Zr upon cooling was attributed to a partial retention of the high temperature phase following thermal annealing. The U-50Zr alloy exhibited a reversible viscoelastic response above 933 K, as evidenced by the observation of high frequency attenuation of the shear component of the waveforms at high temperature. Ultrasonic measurements were supplemented by in situ transmission electron microscopy (TEM). The TEM images revealed that the δ-U-Zr matrix in the three compositions underwent a spinodal decomposition above ~823 K into nanoscale regions. The ultrasonic measurements revealed larger, micron-scale structure evolution in the U-20Zr alloy at the same temperature. This large-scale structure is associated with heterogeneous regions having different Zr content. Our findings show the potential heating rate dependence of microstructural evolution in U-Zr alloys and highlight differences in the thermomechanical response and associated length scales during thermal annealing between single- and dual-phase compositions. These results demonstrate the utility of laser ultrasonics to rapidly and efficiently scan phase boundaries and monitor micrometer-scale structure evolution in metallic fuel alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Kinetics and mechanism of light-induced phase separation in a mixed-halide perovskite

Halide ion phase separation is a barrier to the application of mixed-halide perovskites, whereby the presence of large populations of photo-generated or injected carriers causes undesirable changes in the local band gap. Here, we investigate the mechanism of phase separation in CsPbI x Br 3-x perovskite single crystals driven by light. The phase separation process and its dynamics are visualized at the nanometer scale at cryogenic temperatures using in-situ scanning transmission electron microscopy and cathodoluminescence. Combined with phase field modeling that accounts for the coupling between electronic and chemical driving forces, our observations point to a spinodal decomposition mechanism in which both the amplitude of composition fluctuation and the characteristic length scale grow non-linearly with time. Our findings provide microscopic insights that can assist in further engineering mixed-halide perovskites either for stability or for intentional programming of the local halide ion composition, opening pathways to a wide range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Highly permeable polyethersulfone substrates with bicontinuous structure for composite membranes in CO 2 /N 2 separation

Substrate morphology has a significant effect on the CO 2 transport performance of a thin-film composite (TFC) membrane. In this study, a new mixed solvent comprising 2-pyrrolidone (2-PD) and 2-methoxyethanol (2-ME) was used to prepare polyethersulfone (PES) substrates with bicontinuous structure by water vapor-induced phase separation, followed by immersion in water as nonsolvent. Here, compared with the commonly used solvent, N-methyl-2-pyrrolidone (NMP), the 2-PD/2-ME mixed solvent is more hydrophilic and can decrease the thermodynamic stability of the casting solution significantly. As a result, the phase separation was induced via the spinodal decomposition mechanism. The open morphology bestowed the optimized substrate with a very high CO 2 permeance of 133,226 ± 3,870 GPU (1 GPU = 10 –6 cm 3 (STP) s –1 cm –2 cmHg –1 = 3.3464 × 10 -9 kg-mol s –1 m –2 Pa –1 ), which was 5 times more permeable than the baseline substrate synthesized with NMP. By using this new substrate, the prepared TFC membrane containing amines showed an increased CO 2 permeance of 908 ± 8 GPU at 57°C, which was 48 GPU higher than that with the baseline substrate. Meanwhile, the CO 2 /N 2 selectivity was retained at 162 ± 4 at 57°C. In addition, the good scalability of the new PES substrate was demonstrated by roll-to-roll fabrication of a 50' long scale-up PES substrate with a width of 21".

2-Pyrrolidone↗
DOE OSTI2023

Measurement of G-phase volume fraction and number density in duplex stainless steels using transmission electron microscopy

Duplex stainless steels (DSS) have a high toughness and strength due the presence of both austenitic and ferritic phases. These alloys have had limited use in power production applications due to thermal embrittlement caused by spinodal decomposition and development of G-phase precipitates in the ferrite. Lean grade DSS alloys (e.g., 2101, 2003) may offer improved thermal stability due to the reduction of Cr- and Ni-equivalent elements when compared to standard grade compositions (e.g., 2205, 2209). The abundance of the G-phase was measured in five duplex stainless steels, three wrought alloys (2101, 2003, 2205) and their matching filler metals (2101-w, 2209-w), after aging at 427 °C for 1000 h and 10,000 h. The G-phase volume fraction, number density, size, and precipitate spacing were found using quantitative analysis of transmission electron microscopy dark field images and the composition of G-phase precipitates on other clusters were characterized with atom probe tomography (APT). In the welded alloys, the G-phase was found to develop rapidly, relative to the wrought material. A positive correlation was found between the nickel equivalent composition of the alloy and the G-phase volume fraction. The alloys 2205, 2209, and 2101-w, which are higher in Cr and Ni, all showed significant G-phase precipitation, further strengthening the hypothesis that lean grade DSS alloys are more thermally stable against precipitation in the ferrite. Electron diffraction showed a secondary phase present in the 2101 wrought alloy at 10,000 h, but it was not crystallographically consistent with the G-phase; APT showed the presence of nanoclusters rich in both nickel and copper for this alloy. In conclusion, no secondary phases or clusters were found in 2003 after 10,000 h of aging, so it may be a candidate alloy for applications that require long-life times at high operating temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Semiconducting High-Entropy Chalcogenide Alloys with Ambi-ionic Entropy Stabilization and Ambipolar Doping

Entropy stabilization is a novel materials-design paradigm to realize new compounds with widely tunable properties. However, almost all entropy-stabilized materials so far are either conducting metals or insulating ceramics, with a clear dearth in the semiconducting regime. Here, a new class of the multi-cationic and -anionic entropy-stabilized chalcogenide alloys based on the (Ge,Sn,Pb)(S,Se,Te) formula are synthesized and characterized experimentally. The con-figurational entropy from the disorder of both the anion and the cation sublattices reaches a record value of ~2.2 R mol -1 for the equimolar composition and stabilizes the single-phase solid solution. Theoretical calculations and experiments both show that the synthesized alloys are thermodynamically stable at the growth temperature and kinetically metastable at room temperature, segregating by spinodal decomposition at moderate temperatures. In conclusion, doping and electronic transport measurements verify that the synthesized materials are ambipolarly dopable semiconductors, which paves the way for the wider adoption of entropy-stabilized chalcogenide alloys in functional applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Unraveling the Early-Stage Ordering of Krypton Solid Bubbles in Molybdenum: A Multimodal Study

Self-organization of defects such as fission gas bubbles in materials can lead to high inventory capacity for fission gas storage and help mitigate swelling caused by fission gases in nuclear fuel materials under radiation in nuclear reactors. Here, we report the physical mechanism of self-organization of krypton (Kr) gas bubbles in molybdenum (Mo) under ion implantation. The ion fluence and temperature-dependent formation of Kr solid bubble superlattice (SBS) in Mo were investigated by using both synchrotron-based small-angle X-ray scattering (SAXS) and transmission electron microscopy (TEM). Early stage self-organization of gas bubbles is observed at a fluence of 2.5 × 10 16 ions/cm 2 at temperatures of 300–400 °C. The bubble lattice constant increases with increasing implantation temperature from 300 to 400 °C. Both experiments and atomic kinetic Monte Carlo modeling indicate that the Kr solid bubbles are weakly ordered in comparison to previously studied helium (He) gas bubble superlattice (GBS) while the lattice constant are relatively smaller for Kr SBS compared to that of He GBS. The irradiation conditions suggest that spinodal decomposition, which is a form of phase separation, probably precedes gas bubble ordering in Mo. Altogether, our work sheds light on the formation mechanism of noble gas superlattice toward the development of radiation-tolerant materials which are important for the design of advanced nuclear reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mechanisms of Asymmetric Membrane Formation in Nonsolvent-Induced Phase Separation

We report the first simulations of nonsolvent-induced phase separation (NIPS) that predict membrane microstructures with graded asymmetric pore size distribution. In NIPS, a polymer solution film is immersed in a nonsolvent bath, enriching the film in nonsolvent, and leading to phase separation that forms a solid polymer-rich membrane matrix and polymer-poor membrane pores. We demonstrate how mass-transfer-induced spinodal decomposition, thermal fluctuations, and glass-transition dynamics implemented with mobility contrast between the polymer-rich and polymer-poor phases are essential to the formation of asymmetric membrane microstructures. Specifically, we show that the competition between the propagation of the phase-separation and glass-transition fronts determines the degree of pore-size asymmetry. In conclusion, we also explore the sensitivity of these microstructures to the initial film composition, and compare their formation in 2D and 3D.

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

Polymer-Based Thermally Stable Chemiresistive Sensor for Real-Time Monitoring of NO 2 Gas Emission

Here, we present a thermally stable, mechanically compliant, and sensitive polymer-based NO 2 gas sensor design. Interconnected nanoscale morphology driven from spinodal decomposition between conjugated polymers tethered with polar side chains and thermally stable matrix polymers offers judicious design of NO 2 -sensitive and thermally tolerant thin films. The resulting chemiresitive sensors exhibit stable NO 2 sensing even at 170 °C over 6 h. Controlling the density of polar side chains along conjugated polymer backbone enables optimal design for coupling high NO 2 sensitivity, selectivity, and thermal stability of polymer sensors. Lastly, thermally stable films are used to implement chemiresistive sensors onto flexible and heat-resistant substrates and demonstrate a reliable gas sensing response even after 500 bending cycles at 170 °C. Such unprecedented sensor performance as well as environmental stability are promising for real-time monitoring of gas emission from vehicles and industrial chemical processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Low-index mesoscopic surface reconstructions of Au surfaces using Bayesian force fields

Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-‘Herringbone,’ Au(110)-(1 × 2)-‘Missing-Row,’ and Au(100)-‘Quasi-Hexagonal’ reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully reproduce previous experimental observations of reconstructions on pristine surfaces and provide quantitative predictions of the emergence of spinodal decomposition and localized reconstruction in response to strain at non-ideal stoichiometries. A unified mechanistic explanation is presented of the kinetic and thermodynamic factors driving surface reconstruction. Furthermore, we study surface reconstructions on Au nanoparticles, where characteristic (111) and (100) reconstructions spontaneously appear on a variety of high-symmetry particle morphologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2020

PRISMS-PF: A general framework for phase-field modeling with a matrix-free finite element method

Abstract A new phase-field modeling framework with an emphasis on performance, flexibility, and ease of use is presented. Foremost among the strategies employed to fulfill these objectives are the use of a matrix-free finite element method and a modular, application-centric code structure. This approach is implemented in the new open-source PRISMS-PF framework. Its performance is enabled by the combination of a matrix-free variant of the finite element method with adaptive mesh refinement, explicit time integration, and multilevel parallelism. Benchmark testing with a particle growth problem shows PRISMS-PF with adaptive mesh refinement and higher-order elements to be up to 12 times faster than a finite difference code employing a second-order-accurate spatial discretization and first-order-accurate explicit time integration. Furthermore, for a two-dimensional solidification benchmark problem, the performance of PRISMS-PF meets or exceeds that of phase-field frameworks that focus on implicit/semi-implicit time stepping, even though the benchmark problem’s small computational size reduces the scalability advantage of explicit time-integration schemes. PRISMS-PF supports an arbitrary number of coupled governing equations. The code structure simplifies the modification of these governing equations by separating their definition from the implementation of the numerical methods used to solve them. As part of its modular design, the framework includes functionality for nucleation and polycrystalline systems available in any application to further broaden the phenomena that can be used to study. The versatility of this approach is demonstrated with examples from several common types of phase-field simulations, including coarsening subsequent to spinodal decomposition, solidification, precipitation, grain growth, and corrosion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Inferring topological transitions in pattern-forming processes with self-supervised learning

Abstract The identification of transitions in pattern-forming processes are critical to understand and fabricate microstructurally precise materials in many application domains. While supervised methods can be useful to identify transition regimes, they need labels, which require prior knowledge of order parameters or relevant microstructures describing these transitions. Instead, we develop a self-supervised, neural-network-based approach that does not require predefined labels about microstructure classes to predict process parameters from observed microstructures. We show that assessing the difficulty of solving this inverse problem can be used to uncover microstructural transitions. We demonstrate our approach by automatically discovering microstructural transitions in two distinct pattern-forming processes: the spinodal decomposition of a two-phase mixture and the formation of binary-alloy microstructures during physical vapor deposition of thin films. This approach opens a path forward for discovering unseen or hard-to-discern transitions and ultimately controlling complex pattern-forming processes.

Abram, Marcin↗
DOE OSTI2022

Rheology and dynamics of a solvent segregation driven gel (SeedGel)

Bicontinuous structures promise applications in a broad range of research fields, such as energy storage, membrane science, and biomaterials. Kinetically arrested spinodal decomposition is found responsible for stabilizing such structures in different types of materials. A recently developed solvent segregation driven gel (SeedGel) is demonstrated to realize bicontinuous channels thermoreversibly with tunable domain sizes by trapping nanoparticles in a particle domain. As the mechanical properties of SeedGel are very important for its future applications, a model system is characterized by temperature-dependent rheology. The storage modulus shows excellent thermo-reproducibility and interesting temperature dependence with the maximum storage modulus observed at an intermediate temperature range (around 28 °C). SANS measurements are conducted at different temperatures to identify the macroscopic solvent phase separation during the gelation transition, and solvent exchange between solvent and particle domains that is responsible for this behavior. Further, the long-time dynamics of the gel is further studied by X-ray Photon Correlation Spectroscopy (XPCS). The results indicate that particles in the particle domain are in a glassy state and their long-time dynamics are strongly correlated with the temperature dependence of the storage modulus.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗