Search NASA⌕ Search

SEARCH · Search NASA

Results for “domain dynamics”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Dynamic Nanoscale Spatial Heterogeneity in a Perovskite-to-Brownmillerite Topotactic Phase Transformation

Phase transitions are omnipresent in modern condensed matter physics and its applications. In solids, first-order phase transformations typically occur by nucleation and growth under nonequilibrium conditions. Under constant external conditions, e.g., constant annealing temperature and pressure, the nucleation and growth dynamics are often thought of as spatially and temporally independent. Here, in situ Bragg X-ray photon correlation spectroscopy (XPCS) reveals nanoscale spatial and dynamical heterogeneity in the perovskite-to-brownmillerite topotactic phase transformation in La 0.7 Sr 0.3 CoO 3 thin films annealed under constant reducing conditions over a time span of multiple hours. Specifically, a time scale associated with domain growth remains stable, with a corresponding domain wall speed of v d = 6 ± 0.5 × 10 –4 nm/s (2 ± 0.2 nm/h), while a slower time scale, associated with temperature-driven depinning of domains, leads to accelerating dynamics with time scales following an aging power law with exponent −2.2 ± 0.5. This experiment demonstrates that Bragg XPCS is a powerful tool to study nanoscale dynamics in structural phase transformations, with the ability to extract quantitative average values related to nanodomain motion in situ. Furthermore, the results are relevant for phase engineering of phase-change devices, as they show that nanoscale dynamics, linked to domain and domain-wall motion, can continuously evolve and speed up with time, even hours after the initiation of the phase transformation, with potential repercussions on electrical performance.

X-ray photon correlation spectroscopy↗
DOE OSTI2023

NMR study of Ni 50+x ⁢Ti 50-x strain glasses

Here, we studied Ni 50+x ⁢Ti 50-x with compositions up to x = 2, performing 47 Ti and 49 Ti nuclear magnetic resonance (NMR) measurements from 4 to 400 K. For large x in this system, a strain glass appears in which frozen ferroelastic nanodomains replace the displacive martensite structural transition. Here, we demonstrate that NMR can provide an extremely effective probe of the strain-glass freezing process, with large changes in NMR line shape due to the effects of random strains which become motionally narrowed at high temperatures. At the same time with high-resolution x-ray diffraction we confirm the lack of structural changes in x ≥ 1.2 samples, while we show that there is little change in the electronic behavior across the strain-glass freezing temperature. NMR spin-lattice relaxation time (T 1 ) measurements provide a further measure of the dynamics of the freezing process, and indicate a predominantly thermally activated behavior both above and below the strain-glass freezing temperature. We show that the strain-glass results are consistent with a very small density of critically divergent domains undergoing a Vogel-Fulcher-type freezing process, coexisting with domains exhibiting faster dynamics and stronger pinning.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Path sampling of recurrent neural networks by incorporating known physics

Recurrent neural networks have seen widespread use in modeling dynamical systems in varied domains such as weather prediction, text prediction and several others. Often one wishes to supplement the experimentally observed dynamics with prior knowledge or intuition about the system. While the recurrent nature of these networks allows them to model arbitrarily long memories in the time series used in training, it makes it harder to impose prior knowledge or intuition through generic constraints. In this work, we present a path sampling approach based on principle of Maximum Caliber that allows us to include generic thermodynamic or kinetic constraints into recurrent neural networks. We show the method here for a widely used type of recurrent neural network known as long short-term memory network in the context of supplementing time series collected from different application domains. These include classical Molecular Dynamics of a protein and Monte Carlo simulations of an open quantum system continuously losing photons to the environment and displaying Rabi oscillations. Our method can be easily generalized to other generative artificial intelligence models and to generic time series in different areas of physical and social sciences, where one wishes to supplement limited data with intuition or theory based corrections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Response of Sulfonated Polystyrene Melts to Nonlinear Elongation Flows

Ionizable polymers form dynamic networks with domains controlled by two distinct energy scales, ionic interactions and van der Waals forces; both evolve under elongational flows during their processing into viable materials. A molecular level insight of their nonlinear response, paramount to controlling their structure, is attained by fully atomistic molecular dynamics simulations of a model ionizable polymer, polystyrene sulfonate. As a function of increasing elongational flow rate, the systems display an initial elastic response, followed by an ionic fraction-dependent strain hardening, stress overshoot, and eventually strain-thinning. As the sulfonation fraction increases, the chain elongation becomes more heterogeneous. Finally, flow-driven ionic assembly dynamics that continuously break and reform control the response of the system.

36 MATERIALS SCIENCE↗
NASA NTRS1999

A Framework for Dynamic Constraint Reasoning Using Procedural Constraints

Many complex real-world decision and control problems contain an underlying constraint reasoning problem. This is particularly evident in a recently developed approach to planning, where almost all planning decisions are represented by constrained variables. This translates a significant part of the planning problem into a constraint network whose consistency determines the validity of the plan candidate. Since higher-level choices about control actions can add or remove variables and constraints, the underlying constraint network is invariably highly dynamic. Arbitrary domain-dependent constraints may be added to the constraint network and the constraint reasoning mechanism must be able to handle such constraints effectively. Additionally, real problems often require handling constraints over continuous variables. These requirements present a number of significant challenges for a constraint reasoning mechanism. In this paper, we introduce a general framework for handling dynamic constraint networks with real-valued variables, by using procedures to represent and effectively reason about general constraints. The framework is based on a sound theoretical foundation, and can be proven to be sound and complete under well-defined conditions. Furthermore, the framework provides hybrid reasoning capabilities, as alternative solution methods like mathematical programming can be incorporated into the framework, in the form of procedures.

Jonsson, Ari K.↗
DOE OSTI2021

Magnetic domains and domain wall pinning in atomically thin CrBr 3 revealed by nanoscale imaging

The emergence of atomically thin van der Waals magnets provides a new platform for the studies of two-dimensional magnetism and its applications. However, the widely used measurement methods in recent studies cannot provide quantitative information of the magnetization nor achieve nanoscale spatial resolution. These capabilities are essential to explore the rich properties of magnetic domains and spin textures. Here, we employ cryogenic scanning magnetometry using a single-electron spin of a nitrogen-vacancy center in a diamond probe to unambiguously prove the existence of magnetic domains and study their dynamics in atomically thin CrBr 3 . By controlling the magnetic domain evolution as a function of magnetic field, we find that the pinning effect is a dominant coercivity mechanism and determine the magnetization of a CrBr 3 bilayer to be about 26 Bohr magnetons per square nanometer. The high spatial resolution of this technique enables imaging of magnetic domains and allows to locate the sites of defects that pin the domain walls and nucleate the reverse domains. Our work highlights scanning nitrogen-vacancy center magnetometry as a quantitative probe to explore nanoscale features in two-dimensional magnets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modelling of edge plasma dynamics with active wall boundary conditions

A self-consistent 2D model is presented for transport in boundary plasma and plasma-facing material walls. Plasma dynamics in the domain is represented by a 2D collisional plasma fluid model in the edge-plasma code UEDGE, and transport of hydrogen and heat in the wall is represented by a system of reaction–diffusion equations in the 1D wall code FACE. To account for variation of parameters along the wall, in the coupled model multiple instances of the FACE code run in parallel. Here, the coupled model provides a tool for investigating a range of dynamic plasma–material interactions phenomena in 2D. For demonstration of its capability, one application of particular interest is the role of active wall in tokamak strike point sweeping proposed for mitigation of divertor heat loads. In the present study, the coupled calculations are applied to investigation of the impact of heat and hydrogen transport in the material wall on the divertor plasma and target heat load during sweeping of the target strike point for parameters of a high-power tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

Integration of domain and resource-based reasoning for real-time control in dynamic environments

A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.

Morgan, Keith↗
DOE OSTI2020

Asymmetric Composition of Ionic Aggregates and the Origin of High Correlated Transference Number in Water-in-Salt Electrolytes

"Water-in-salt" electrolytes open up exciting new avenues for expanding the electrochemical window of aqueous electrolytes. We investigated the solvation structure and dynamics of highly concentrated lithium bis(trifluoromethane)sulfonimide aqueous electrolyte using experimentally corroborated molecular dynamics simulations. The simulations revealed that the heterogeneous structure of the electrolyte comprises percolating networks of ion and water domains/aggregates. Interestingly, the ionic regions are composed of more TFSI - ions than Li + ions. The Li + -ion transport mechanism was further explored. Li + ions can hop along the coordinated TFSI- ions in the ionic aggregates. The calculated correlated transference number of the 20 m electrolyte is similar to 0.32, which is reasonably high for the high concentration due to a weak negative correlation between the motion of cations and anions within the heterogeneous microscopic domains. These molecular dynamics results connect the heterogeneous structure of the electrolyte to the correlated dynamics of the Li + ion and provide a new understanding of the Li + -ion transport mechanism in this novel electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Defective internal allosteric network imparts dysfunctional ATP/substrate-binding cooperativity in oncogenic chimera of protein kinase A

An aberrant fusion of the DNAJB1 and PRKACA genes generates a chimeric protein kinase (PKA-C DNAJB1 ) in which the J-domain of the heat shock protein 40 is fused to the catalytic α subunit of cAMP-dependent protein kinase A (PKA-C). Deceivingly, this chimeric construct appears to be fully functional, as it phosphorylates canonical substrates, forms holoenzymes, responds to cAMP activation, and recognizes the endogenous inhibitor PKI. Nonetheless, PKA-C DNAJB1 has been recognized as the primary driver of fibrolamellar hepatocellular carcinoma and is implicated in other neoplasms for which the molecular mechanisms remain elusive. Here we determined the chimera’s allosteric response to nucleotide and pseudo-substrate binding. We found that the fusion of the dynamic J-domain to PKA-C disrupts the internal allosteric network, causing dramatic attenuation of the nucleotide/PKI binding cooperativity. Our findings suggest that the reduced allosteric cooperativity exhibited by PKA-C DNAJB1 alters specific recognitions and interactions between substrates and regulatory partners contributing to dysregulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Domain-wall-mediated polarization switching in ferroelectric AlScN: Strain relief and field-dependent dynamics

While scandium-doped aluminum nitride (AlScN) exhibits robust ferroelectricity and excellent thermal stability, its utility is limited by an exceptionally high coercive field (𝐸 𝑐 ) for polarization switching. Unraveling the atomistic switching dynamics is therefore critical for tailoring 𝐸 𝑐 . Here, in this study, we combine density functional theory and machine-learning molecular dynamics to elucidate the polarization switching mechanisms in AlScN over various Sc concentrations and applied electric fields. We find that excessive lattice strain strictly prohibits collective polarization switching, but the preexisting domain walls relieve strain and lead to a distinct switching dynamics—dictating a field-dependent switching mechanism. At low electric fields, switching occurs via gradual domain-wall propagation consistent with the Kolmogorov-Avrami-Ishibashi model. In contrast, high fields stimulate additional nucleation, driving a rapid, homogeneous reversal process described by the simultaneous nonlinear nucleation and growth model. These findings highlight the critical role of domain-wall dynamics and suggest domain engineering as a viable strategy to tailor coercive fields in AlScN and related ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Model-Free Dynamic Voltage Control of a Synchronous Generator-Based Microgrid

The main goal of this paper is to present a new dynamic voltage stability mechanism, based on model-free control (MFC), for effective control and coordination of synchronous generator (SG)-based reactive power resources in a microgrid setting. MFC has shown successful operation in various domains, and this paper presents its first use in the voltage stability of a power system. It is utilized as an online controller to achieve the dynamic voltage stability of a microgrid system under different disturbances and fault conditions. A 21-bus microgrid system fed by SG-based distributed energy resources (DERs) is considered as a use case study. The overall dynamic voltage stability of the microgrid system is investigated using time-domain dynamic simulations during emergency, hazard, and disaster events. Simulation results show that there are significant improvements and enhancements on the dynamic load bus voltage profiles of the microgrid system by the effective model-free control and coordination of the reactive power reserves of the SG-based DERs.

Hatipoglu, Kenan↗
DOE OSTI2021

A unifying modeling abstraction for infinite-dimensional optimization

Infinite-dimensional optimization (InfiniteOpt) problems involve modeling components (variables, objectives, and constraints) that are functions defined over infinite-dimensional domains. Examples include continuous-time dynamic optimization (time is an infinite domain and components are functions of time), PDE optimization problems (space and time are infinite domains and components are functions of space-time), as well as stochastic and semi-infinite optimization (random space is an infinite domain and components are a function of such random space). InfiniteOpt problems also arise from combinations of these problem classes (e.g., stochastic PDE optimization). Given the infinite-dimensional nature of objectives and constraints, one often needs to define appropriate quantities (measures) to properly pose the problem. Moreover, InfiniteOpt problems often need to be transformed into a finite dimensional representation so that they can be solved numerically. Here in this work, we present a unifying abstraction that facilitates the modeling, analysis, and solution of InfiniteOpt problems. The proposed abstraction enables a general treatment of infinite-dimensional domains and provides a measure-centric paradigm to handle associated variables, objectives, and constraints. This abstraction allows us to transfer techniques across disciplines and with this identify new, interesting, and useful modeling paradigms (e.g., event constraints and risk measures defined over time domains). Our abstraction serves as the backbone of an intuitive Julia-based modeling package that we call InfiniteOpt.jl. We demonstrate the developments using diverse case studies arising in engineering.

42 ENGINEERING↗
DOE OSTI2021

Ferroelectric and Charge Transport Properties in Strain-Engineered Two-Dimensional Lead Iodide Perovskites

Transitions from three-dimensional (3D) hybrid organic–inorganic perovskite (HOIP) structures to lower dimensions including 2D and quasi-2D structures open a new range of functional properties in these materials systems. Yet, the performance of solar cells made from 2D HOIP is below that of the 3D compositions due to the higher band-gap energy, low carrier concentration, and anisotropy in charge transport. Controlling ferroelectricity in 2D HOIPs is considered to be a powerful strategy to drive the spatial separation of photogenerated charge carriers to improve the photovoltaic action in this class of HOIPs. Here, we explore the strain-dependent ferroelectricity and charge carrier properties in strain-engineered 2D-layered HOIPs utilizing advanced scanning probe microscopy (SPM) techniques. Band excitation-piezoresponse force microscopy (BE-PFM) and contact Kelvin probe force microscopy (cKPFM) reveal ferroelectric domains and switchable dynamics with significantly low switching voltages in the low-strain film. Photoluminescence (PL) spectroscopy shows strain-dependent optical properties and a noncentrosymmetric structure with strong second-harmonic generation (SHG) peaks in the low-strain film. In addition, KPFM results demonstrate a higher surface potential in the low-strain films, while the photovoltage and local current are the highest on the high-strain film. Furthermore, our study demonstrates the critical role of strain engineering on the electromechanical and charge carrier dynamics in 2D HOIPs, which is important for development of 2D HOIP devices.

36 MATERIALS SCIENCE↗