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At least 217 records · Page 12

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NASA NTRS2003

A Domain Decomposition Parallelization of the Fast Marching Method

In this paper, the first domain decomposition parallelization of the Fast Marching Method for level sets has been presented. Parallel speedup has been demonstrated in both the optimal and non-optimal domain decomposition case. The parallel performance of the proposed method is strongly dependent on load balancing separately the number of nodes on each side of the interface. A load imbalance of nodes on either side of the domain leads to an increase in communication and rollback operations. Furthermore, the amount of inter-domain communication can be reduced by aligning the inter-domain boundaries with the interface normal vectors. In the case of optimal load balancing and aligned inter-domain boundaries, the proposed parallel FMM algorithm is highly efficient, reaching efficiency factors of up to 0.98. Future work will focus on the extension of the proposed parallel algorithm to higher order accuracy. Also, to further enhance parallel performance, the coupling of the domain decomposition parallelization to the G(sub 0)-based parallelization will be investigated.

Herrmann, M.↗

NASA NTRS2008

Domain Decomposition By the Advancing-Partition Method

A new method of domain decomposition has been developed for generating unstructured grids in subdomains either sequentially or using multiple computers in parallel. Domain decomposition is a crucial and challenging step for parallel grid generation. Prior methods are generally based on auxiliary, complex, and computationally intensive operations for defining partition interfaces and usually produce grids of lower quality than those generated in single domains. The new technique, referred to as "Advancing Partition," is based on the Advancing-Front method, which partitions a domain as part of the volume mesh generation in a consistent and "natural" way. The benefits of this approach are: 1) the process of domain decomposition is highly automated, 2) partitioning of domain does not compromise the quality of the generated grids, and 3) the computational overhead for domain decomposition is minimal. The new method has been implemented in NASA's unstructured grid generation code VGRID.

Pirzadeh, Shahyar Z.↗

NASA NTRS2009

Domain Decomposition By the Advancing-Partition Method for Parallel Unstructured Grid Generation

Pirzadeh, Shahyar Z.↗

NASA NTRS2012

Domain decomposition by the advancing-partition method for parallel unstructured grid generation

In a method for domain decomposition for generating unstructured grids, a surface mesh is generated for a spatial domain. A location of a partition plane dividing the domain into two sections is determined. Triangular faces on the surface mesh that intersect the partition plane are identified. A partition grid of tetrahedral cells, dividing the domain into two sub-domains, is generated using a marching process in which a front comprises only faces of new cells which intersect the partition plane. The partition grid is generated until no active faces remain on the front. Triangular faces on each side of the partition plane are collected into two separate subsets. Each subset of triangular faces is renumbered locally and a local/global mapping is created for each sub-domain. A volume grid is generated for each sub-domain. The partition grid and volume grids are then merged using the local-global mapping.

Pirzadeh, Shahyar Z.↗

DOE OSTI2025

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗

DOE OSTI2026

HydroDCM: Hydrological Domain-Conditioned Modulation for Cross-Reservoir Inflow Prediction

Deep learning models have shown promise in reservoir inflow prediction, yet their performance often deteriorates when applied to different reservoirs due to distributional differences, referred to as the domain shift problem. Domain generalization (DG) solutions aim to address this issue by extracting domain-invariant representations that mitigate errors in unseen domains. However, in hydrological settings, each reservoir exhibits unique inflow patterns, while some metadata beyond observations like spatial information exerts indirect but significant influence. This mismatch limits the applicability of conventional DG techniques to many-domain hydrological systems. To overcome these challenges, we propose HydroDCM, a scalable DG framework for cross-reservoir inflow forecasting. Spatial metadata of reservoirs is used to construct pseudo-domain labels that guide adversarial learning of invariant temporal features. During inference, HydroDCM adapts these features through light-weight conditioning layers informed by the target reservoir’s metadata, reconciling DG’s invariance with location-specific adaptation. Experiment results on 30 real-world reservoirs in the Upper Colorado River Basin demonstrate that our method substantially outperforms state-of-the-art DG baselines under many-domain conditions and remains computationally efficient.

Hu, Pengfei [ORNL] (ORCID:0009000367130950)↗

DOE OSTI2021

Vortex Domain Walls in Ferroelectrics

Controlling the domain formation in ferroelectric materials at the nanoscale is a fertile ground to explore emergent phenomena and their technological prospects. For example, charged ferroelectric domain walls in BiFeO 3 and ErMnO 3 exhibit significantly enhanced conductivity which could serve as the foundation for next-generation circuits. In this work, we describe a concept in which polar vortices perform the same role as a ferroelectric domain wall in classical domain structures with the key difference being that the polar vortices can accommodate charged (i.e., head-to-head and tail-to-tail) domains, for example, in ferroelectric PbTiO 3 /dielectric SrTiO 3 superlattices. Such a vortex domain wall structure can be manipulated in a reversible fashion under an external applied field.

36 MATERIALS SCIENCE↗

NASA NTRS2015

A Persistent Feature of Multiple Scattering of Waves in the Time-Domain: A Tutorial

The equations for frequency-domain multiple scattering are derived for a scalar or electromagnetic plane wave incident on a collection of particles at known positions, and in the time-domain for a plane wave pulse incident on the same collection of particles. The calculation is carried out for five different combinations of wave types and particle types of increasing geometrical complexity. The results are used to illustrate and discuss a number of physical and mathematical characteristics of multiple scattering in the frequency- and time-domains. We argue that frequency-domain multiple scattering is a purely mathematical construct since there is no temporal sequencing information in the frequency-domain equations and since the multi-particle path information can be dispelled by writing the equations in another mathematical form. However, multiple scattering becomes a definite physical phenomenon in the time-domain when the collection of particles is illuminated by an appropriately short localized pulse.

particles↗

DOE OSTI2024

Observation of Antiferroelectric Domain Walls in a Uniaxial Hyperferroelectric

Abstract Ferroelectric domain walls are a rich source of emergent electronic properties and unusual polar order. Recent studies show that the configuration of ferroelectric walls can go well beyond the conventional Ising‐type structure. Néel‐, Bloch‐, and vortex‐like polar patterns have been observed, displaying strong similarities with the spin textures at magnetic domain walls. Here, the discovery of antiferroelectric domain walls in the uniaxial ferroelectric Pb 5 Ge 3 O 11 is reported. Highly mobile domain walls with an alternating displacement of Pb atoms are resolved, resulting in a cyclic 180° flip of dipole direction within the wall. Density functional theory calculations show that Pb 5 Ge 3 O 11 is hyperferroelectric, allowing the system to overcome the depolarization fields that usually suppress the antiparallel ordering of dipoles along the longitudinal direction. Interestingly, the antiferroelectric walls observed under the electron beam are energetically more costly than basic head‐to‐head or tail‐to‐tail walls. The results suggest a new type of excited domain‐wall state, expanding previous studies on ferroelectric domain walls into the realm of antiferroic phenomena.

36 MATERIALS SCIENCE↗

DOE OSTI2021

An adaptive adversarial domain adaptation approach for corn yield prediction

Recently, statistical machine learning and deep learning methods have been widely explored for corn yield prediction. Though successful, machine learning models generated within a specific spatial domain often lose their validity when directly applied to new regions. To address this issue, we designed an unsupervised adaptive domain adversarial neural network (ADANN). Specifically, through domain adversarial training, the ADANN model reduced the impact of domain shift by projecting data from different domains into the same subspace. Also, the ADANN model was designed to be trained in an adaptive way, which guaranteed the model can learn the domain-invariant features and perform accurate yield prediction simultaneously. Informative variables including time-series vegetation indices and sequential weather observations were first collected from multiple data sources and aggregated to the county level. Then, we trained the ADANN model with the extracted features and corresponding reported county-level corn yield from the U.S. Department of Agriculture (USDA). Finally, the trained model was evaluated in four testing years 2016–2019. The U.S. corn belt was used as the study area and counties under study were grouped into two diverse ecological regions. Overall, the experimental results showed that the developed ADANN model had better performance than three other state-of-the-art machine learning models in both local experiments (train and test in the same region) and transfer experiments (train and test in different regions). As the first study using adversarial learning for crop yield prediction, this research demonstrates a novel solution for improving model transferability on crop yield prediction.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Light-Induced Currents at Domain Walls in Multiferroic BiFeO3.

Multiferroic BiFeO3 (BFO) films with spontaneously formed periodic stripe domains can generate above-gap open circuit voltages under visible light illumination; nevertheless the underlying mechanism behind this intriguing optoelectronic response has not been understood to date. Here, we make contact-free measurements of light-induced currents in epitaxial BFO films via detecting terahertz radiation emanated by these currents, enabling a direct probe of the intrinsic charge separation mechanisms along with quantitative measurements of the current amplitudes and their directions. In the periodic stripe samples, we find that the net photocurrent is dominated by the charge separation across the domain walls, whereas in the monodomain samples the photovoltaic response arises from a bulk shift current associated with the non-centrosymmetry of the crystal. The peak current amplitude driven by the charge separation at the domain walls is found to be 2 orders of magnitude higher than the bulk shift current response, indicating the prominent role of domain walls acting as nanoscale junctions to efficiently separate photogenerated charges in the stripe domain BFO films. These findings show that domain-wall-engineered BFO thin films offer exciting prospects for ferroelectric-based optoelectronics, as well as bias-free strong terahertz emitters.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Probing Metastable Domain Dynamics via Automated Experimentation in Piezoresponse Force Microscopy

The dynamics of complex topological defects in ferroelectric materials is explored using automated experimentation in piezoresponse force microscopy. Specifically, a complex trigger system (i.e., “FerroBot”) is employed to study metastable domain-wall dynamics in Pb 0.6 Sr 0.4 TiO 3 thin films. Several regimes of superdomain wall dynamics have been identified, including smooth domain-wall motion and significant reconfiguration of the domain structures. We have further demonstrated that microscopic mechanisms of the domain-wall dynamics can be identified; i.e., domain-wall bending can be separated from irreversible domain reconfiguration regimes. In conjunction, phase-field modeling was used to corroborate the observed mechanisms. As such, the observed superdomain dynamics can provide a model system for classical ferroelectric dynamics, much like how colloidal crystals provide a model system for atomic and molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Using Domain Insertion to Create Sulfite Reductases That Present Chemical-Dependent Activities

Domain insertion can be used to create oxidoreductases whose activities are dependent upon analyte binding. To date, most domain insertion studies have targeted relatively small oxidoreductases of known structure, so it remains unclear how to apply this protein engineering approach to large hetero-oligomeric proteins that require dynamic conformational changes for catalysis. To address this question, we studied the effects of peptide and domain insertions on the activity of NADPH-dependent sulfite reductase (SiR) from Escherichia coli, a dodecameric oxidoreductase containing four hemoprotein and eight flavoprotein subunits. SiR mutational tolerance was first evaluated using systematic octapeptide insertion and a cellular selection, which identified regions across the hemoprotein structure that retain parent-like activity following insertion. When a ligand-binding domain was inserted at backbone locations tolerant to peptide insertion, including sites proximal and distal from the intersubunit interfaces, ∼90% retained catalytic activity, and >50% presented activity that is regulated by an endocrine disruptor. With one domain insertion variant, the conditional production of sulfide could be monitored electrochemically from cells using a bioelectrochemical reactor. These results show how systematic peptide insertion can be used to inform domain insertion in a large heterooligomeric protein complex, and they illustrate how SiR can be engineered to convert chemical information in the environment into a redox-active metabolite that diffuses across the cell membrane.

bacteria↗

DOE OSTI2020

Allosteric regulation of thioesterase superfamily member 1 by lipid sensor domain binding fatty acids and lysophosphatidylcholine

Nonshivering thermogenesis occurs in brown adipose tissue to generate heat in response to cold ambient temperatures. Thioesterase superfamily member 1 (Them1) is transcriptionally up-regulated in brown adipose tissue upon exposure to the cold and suppresses thermogenesis in order to conserve energy reserves. It hydrolyzes long-chain fatty acyl-CoAs that are derived from lipid droplets, preventing their use as fuel for thermogenesis. In addition to its enzymatic domains, Them1 contains a C-terminal StAR-related lipid transfer (START) domain with unknown ligand or function. By complementary biophysical approaches, we show that the START domain binds to long-chain fatty acids, products of Them1’s enzymatic reaction, as well as lysophosphatidylcholine (LPC), lipids shown to activate thermogenesis in brown adipocytes. Certain fatty acids stabilize the START domain and allosterically enhance Them1 catalysis of acyl-CoA, whereas 18:1 LPC destabilizes and inhibits activity, which we verify in cell culture. Additionally, we demonstrate that the START domain functions to localize Them1 near lipid droplets. Overall, these findings define the role of the START domain as a lipid sensor that allosterically regulates Them1 activity and spatially localizes it in proximity to the lipid droplet.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Structure of domain walls in chiral spin liquids

The chiral spin liquid is a canonical state of quantum spins combining topological and symmetry-breaking order, and possible experimental realizations have attracted growing interest. We examine the physics at interfaces between chiral spin liquid domains of opposite chirality. We show that a self-consistent mean-field description of spinons remains possible in the vicinity of a domain wall and use this to formulate a Ginzburg–Landau theory of the domain wall. The bulk of a chiral spin liquid contains gapped spinon excitations and gauge fluctuations, set by a finite spinon mass and a nonzero spinon Chern number. A third class of excitations consists of amplitude fluctuations of the spinon hoppings, which admit a geometric interpretation in terms of effective vielbein fields. These fluctuations are usually neglected because they are irrelevant for a homogeneous chiral spin liquid and are suppressed in standard large- N treatments. Going beyond the purely topological Chern–Simons limit, we incorporate these fluctuations into an effective field theoretic framework and show that they generate momentum-dependent corrections, including Chern–Simons-like linear terms and higher-order contributions, beyond the universal topological limit. We then analyze nontopological properties, including domain wall tension and edge velocity, and explain how they modify observables relative to the uniform case. These results connect measurable, nonuniversal quantities such as domain wall width, domain wall tension, and edge velocity to microscopic parameters and provide concrete targets for experiments.

domain walls↗

DOE OSTI2025

Symmetry breaking during low-temperature domain formation in micron-sized magnetite crystals

We report the results of synchrotron Bragg Coherent x-ray Diffraction Imaging (BCDI) experiments to investigate domain formation in a micron-sized magnetite crystal undergoing the Verwey transition at low temperature. A strong splitting of the measured 311 Bragg reflection was observed in the low-temperature phase, indicating the formation of domains. BCDI revealed pronounced strain distributions, characterized by a clear layered stripe domain structure in real-space. Stripes were seen only along the [001] crystallographic direction, normal to the substrate surface direction, breaking the symmetry of the cubic high-temperature phase. It is argued that other domain directions were suppressed by the sample mounting orientation. More surprisingly, only a single domain orientation was observed, suggesting an additional symmetry-breaking influence originating from the shape of the crystal. Gaining insight into how thermal effects induce the formation of layered or striped phases offers a valuable framework for understanding the development of mesoscopic domains and strain patterns in functional materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Ferroelectric switching pathways and domain structure of SrBi 2 ⁢(Ta,Nb) 2 ⁢O 9 from first principles

Several families of layered perovskite oxide ferroelectrics exhibit a coupling between polarization and structural order parameters, such as octahedral rotation distortions. This coupling provides opportunities for novel electric field-based manipulation of material properties, and it also stabilizes complex domain patterns and domain-wall vortices. Among layered perovskites with such coupled orders, the Aurivillius-phase oxides SrBi 2 ⁢B 2 ⁢O 9 (B = Ta,Nb) are well-known for their excellent room-temperature ferroelectric performance. This work combines group theoretic analysis with density functional theory calculations to examine the ferroelectric switching processes of SrBi2⁢B2⁢O9. Low-energy two-step ferroelectric switching paths are identified, with polarization reversal facilitated by structural order-parameter rotations. Analysis of the domain structure reveals how the relative energetics of the coupled order parameters translates into a network of several distinct domain-wall types linked by domain-wall vortex structures. Comparisons are made between the ferroelectric switching and domain structure of SrBi 2 ⁢B 2 ⁢O 9 and those of the layered n = 2 Ruddlesden-Popper hybrid improper ferroelectrics. The results provide insight into how ferroelectric properties may be optimized by engineering the complex crystal structures of Aurivillius-phase oxides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Mesoscopic structure of mixed type domain walls in multiaxial ferroelectrics

The structure of a 180° uncharged rotational domain wall in a multiaxial ferroelectric film is studied in the framework of an analytical Landau-Ginzburg-Devonshire (LGD) approach. Finite element modeling (FEM) is used to solve numerically the system of the coupled nonlinear Euler-Lagrange (EL) second-order differential equations for two components of polarization. We show that the structure of the domain wall and corresponding metastable or stable phase of the film are controlled by a single parameter—the dimensionless ferroelectric anisotropy factor μ. We fitted the static profile of a solitary domain wall, calculated by FEM, with kinklike functions for polarization components, and extracted the five μ-dependent parameters from the fitting to FEM curves. The surprisingly high accuracy of the fitting results for two polarization components in the entire μ range allows us to conclude that the analytical functions, which are trial functions in the direct variational method, can be treated as a high-accuracy variational solution of the static EL equations. We further derive exact two-component analytical solutions of the static EL equations for a polydomain 180° domain structure in a multiaxial ferroelectric film. Using these, we derive analytical expressions for the system free energy and analyze its dependence on the film thickness and boundary conditions at the film surfaces. The single-domain state is ground for zero polarization derivative at the surfaces, while the polydomain states minimize the system energy for zero polarization at the surfaces. Counterintuitively, the energy of the polydomain states split into two levels, “0” and “1,” for zero polarization at the surfaces, and each of the levels contains a large number of close-energy sublevels, whose structure is characterized by a different number and type of domain walls. The analytical solutions can become a useful tool for Bayesian analysis of high-resolution scanning transmission electron microscopy images in ferroelectric films.

36 MATERIALS SCIENCE↗