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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Anisotropic epitaxial stabilization of a low-symmetry ferroelectric with enhanced electromechanical response

Here piezoelectrics interconvert mechanical energy and electric charge and are widely used in actuators and sensors. The best performing materials are ferroelectrics at a morphotropic phase boundary, where several phases coexist. Switching between these phases by electric field produces a large electromechanical response. In ferroelectric BiFeO3, strain can create a morphotropic-phase-boundary-like phase mixture and thus generate large electric-field-dependent strains. However, this enhanced response occurs at localized, randomly positioned regions of the film. Here, we use epitaxial strain and orientation engineering in tandem-anisotropic epitaxy-to craft a low-symmetry phase of BiFeO3 that acts as a structural bridge between the rhombohedral-like and tetragonal-like polymorphs. Interferometric displacement sensor measurements reveal that this phase has an enhanced piezoelectric coefficient of x2.4 compared with typical rhombohedral-like BiFeO3. Band-excitation frequency response measurements and first-principles calculations provide evidence that this phase undergoes a transition to the tetragonal-like polymorph under electric field, generating an enhanced piezoelectric response throughout the film and associated field-induced reversible strains. These results offer a route to engineer thin-film piezoelectrics with improved functionalities, with broader perspectives for other functional oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Surface localized magnetism in transition metal doped alumina

Alumina is a structural ceramic that finds many uses in a broad range of applications. It is widely employed in the aerospace and biomedical sectors due to its stability at high temperatures and in harsh chemical environments. Here, we show that magnetism can be induced at alumina surfaces by doping with 3d transition metals. We analyze the electronic structure, spin magnetic moments, and spin density of α-Al 2 O 3 as a function of both dopant species (Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu) and depth using first principles calculations. Our results show that all dopants, with the exception of Sc, produce magnetic moments that are concentrated to the surface of alumina with varying degrees of delocalization. It is seen that all of the dopants are at least meta-stable on the surface and must overcome an energy barrier of 0.19–1.14 eV in order to diffuse from the surface into the bulk. As a result of judiciously doping with select 3$\textit{d}$ transition metals the surface of alumina can be made magnetic. This could lead to novel applications in data storage, catalysis, and biomedical engineering through an added surface functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Synergistic ruthenium single-atom and nanoparticles in nickel as cooperative catalysts for the alkaline hydrogen evolution reaction

Efficient hydrogen evolution reaction (HER) catalysts that reduce the use of noble metals and can be synthesized on a large scale are essential for advancing anion exchange membrane water electrolyzers (AEMWEs) toward commercialization. Herein, we present a composite catalyst in which Ru nanoparticles coexist with Ru single-atom alloys (SAAs) dispersed within Ni nanoparticles (Ru-SAA/Ni), creating a highly active HER electrocatalyst. Using a one-pot and scalable synthesis method, we can tune the material composition from SAA, i.e. materials containing atomically dispersed Ru atoms (with ≤0.4 at% Ru) to composite structures in which SAAs coexist with Ru NPs. Comprehensive characterization using XPS, XAS, and TEM confirms Ru-SAA formation at a low Ru content and composite structures at higher contents. Electrochemical evaluations conducted in a three-electrode setup reveal that Ru-SAA/Ni composites achieve HER performance on par with that of Pt/C. Computational insights suggest that water dissociation is significantly faster at the Ru/Ni interface compared with that on extended surfaces. These active sites are thermodynamically as active as basal planes, preventing the excessive accumulation of reaction intermediates (H*, OH*). All these results highlight the synergistic interaction between Ru SAAs and Ru nanoparticles and their potential for large-scale applications with minimal use of precious metals. Finally, the materials are processed and tested in AEMWEs, achieving 1.85 V at 0.5 A cm −2 with a total noble metal loading of only 0.1 mg cm −2 .

Khalil, Gaëlle [Université de Paris (France)]↗
DOE OSTI2026

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

Dirichlet-to-Neumann maps enable the coupling of multiphysics simulations across computational subdomains by ensuring continuity of state variables and fluxes at artificial interfaces. We present a novel method for learning Dirichlet-to-Neumann maps on graphs using Gaussian processes, specifically for problems where the data obey a conservation law arising from an underlying partial differential equation. Our approach combines discrete exterior calculus and nonlinear optimal recovery to infer relationships between vertex and edge values. This framework yields data-driven predictions with uncertainty quantification across the entire graph, even when observations are limited to a subset of vertices and edges. By minimizing the reproducing kernel Hilbert space norm while penalizing kernel complexity through maximum likelihood estimation, our method ensures that the resulting surrogate strictly enforces conservation laws without overfitting. We demonstrate our method on two representative applications: subsurface flow in fracture networks and arterial blood flow. Finally, the results demonstrate that the method maintains high accuracy and well-calibrated uncertainty estimates even under severe data scarcity, highlighting its potential for scientific applications where limited data and reliable uncertainty quantification are critical.

Dirichlet-to-Neumann map↗
DOE OSTI2021

A software package for plasma facing component analysis and design: the Heat flux Engineering Analysis Toolkit (HEAT)

The engineering limits of plasma facing components (PFCs) constrain the allowable operational space of tokamaks. Poorly managed heat fluxes that push the PFCs beyond their limits not only degrade core plasma performance via elevated impurities, but can also result in PFC failure due to thermal stresses or melting. Simple axisymmetric assumptions fail to capture the complex interaction between 3D PFC geometry and 2D or 3D plasmas. This results in fusion systems that must either operate with increased risk or reduce PFC loads, potentially through lower core plasma performance, to maintain a nominal safety factor. High precision 3D heat flux predictions are necessary to accurately ascertain the state of a PFC given the evolution of the magnetic equilibrium. A new code, the Heat flux Engineering Analysis Toolkit (HEAT), has been developed to provide high precision 3D predictions and analysis for PFCs. HEAT couples many otherwise disparate computational tools together into a single open source python package. Magnetic equilibrium, engineering CAD, finite volume solvers, scrape off layer plasma physics, visualization, high performace computing, and more, are connected in a single web-based user interface. Linux users may use HEAT without any software prerequisites via an appImage. This manuscript introduces HEAT, discusses the software architecture, presents first HEAT results, and outlines physics modules in development.

divertor physics↗
DOE OSTI2022

PUFFIn

The PUFFIn software package is a graphical user interface that allows for photon and electron beam calculations using the PENELOPE computer code. It prepares the required input files and displays the resulting output data. It can be used by anyone interested in the interaction of photon or electron beams with matter

Schwarz, Randy↗
DOE OSTI2021

Coupling of regional geophysics and local soil-structure models in the EQSIM fault-to-structure earthquake simulation framework

Accurate understanding and quantification of the risk to critical infrastructure posed by future large earthquakes continues to be a very challenging problem. Earthquake phenomena are quite complex and traditional approaches to predicting ground motions for future earthquake events have historically been empirically based whereby measured ground motion data from historical earthquakes are homogenized into a common data set and the ground motions for future postulated earthquakes are probabilistically derived based on the historical observations. This procedure has recognized significant limitations, principally due to the fact that earthquake ground motions tend to be dictated by the particular earthquake fault rupture and geologic conditions at a given site and are thus very site-specific. Historical earthquakes recorded at different locations are often only marginally representative. There has been strong and increasing interest in utilizing large-scale, physics-based regional simulations to advance the ability to accurately predict ground motions and associated infrastructure response. However, the computational requirements for simulations at frequencies of engineering interest have proven a major barrier to employing regional scale simulations. In a U.S. Department of Energy Exascale Computing Initiative project, the EQSIM application development is underway to create a framework for fault-to-structure simulations. This framework is being prepared to exploit emerging exascale platforms in order to overcome computational limitations. This article presents the essential methodology and computational workflow employed in EQSIM to couple regional-scale geophysics models with local soil-structure models to achieve a fully integrated, complete fault-to-structure simulation framework. Here, the computational workflow, accuracy and performance of the coupling methodology are illustrated through example fault-to-structure simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation

Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

JPype

JPype is a Python module to provide full access to Java from within Python. It allows Python to make use of Java only libraries, exploring and visualization of Java structures, development and testing of Java libraries, scientific computing, and much more. By gaining the best of both worlds using Python for rapid prototyping and Java for strong typed production code, JPype provides a powerful environment for engineering and code development. This is achieved not through re-implementing Python, as Jython has done, but rather through interfacing at the native level in both virtual machines. This shared memory based approach achieves decent computing performance, while providing the access to the entirety of CPython and Java libraries.

Nelson, KarlE.↗
DOE OSTI2024

teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Time-Resolved Evolution of the 3D Nanoporous Structure of Sintered Ag by X-Ray Nanotomography: Role of the Interface with a Copper Substrate

Here, the evolution of the nanoporous structure of cylindrical sintered silver samples during high temperature aging, ranging from 200 to 350 °C for 350 min, is studied through in situ computed X-ray tomography. Investigations are carried out for two types of specimens: pure sintered silver and specimens containing a silver-copper interface. It is shown that the overall pore evolution is driven by the evolution of very few large ones. The smaller pores, although being more numerous, do not really evolve before being absorbed by the few bigger ones. In pure silver, pore evolution is driven by diffusion (Ostwald ripening) but the presence of an interface promotes faster growth kinetics until the aging time reaches a threshold value, after which a deviation from Ostwald ripening occurs. The transition is a function of the aging temperature. This behavior is associated with the competition between elastic relaxation and surface energy minimization.

42 ENGINEERING↗
DOE OSTI2021

Multichannel Analysis of Surface Waves Accelerated (MASWAccelerated): Software for efficient surface wave inversion using MPI and GPUs

Multichannel Analysis of Surface Waves (MASW) is a technique frequently used in geotechnical engineering and engineering geophysics to infer 1D layered models of seismic shear wave velocities in the top tens to hundreds of meters of the subsurface. We aim to accelerate MASW calculations by capitalizing on modern computer hardware available in the workstations of most engineers: multiple cores and graphics processing units (GPUs). We propose new parallel and GPU accelerated algorithms for computing 1D MASW inversion, and provide software implementations in C using Message Passing Interface (MPI) and CUDA. These algorithms take advantage of sparsity that arises in the problem, and the work balance between processes considers typical data trends. We compare our methods to an existing open source Matlab MASW tool. Our serial C implementation achieves a 2x speedup over the Matlab software, and we continue to see improvements by parallelizing the problem with MPI. Here we see nearly perfect strong and weak scaling for uniform data, and improve strong scaling for realistic data by repartitioning the problem to process mapping. By utilizing GPUs available on most modern workstations, we observe an additional 1.3x speedup over the serial C implementation on the first use of the method. We typically repeatedly evaluate theoretical dispersion curves as part of an optimization procedure, and on the GPU the kernel can be cached for faster reuse on later runs. We observe a 3.2x speedup on the cached GPU runs compared to the serial C runs. This work is the first open-source parallel or GPU-accelerated software tool for MASW imaging, and should enable geotechnical engineers to fully utilize all computer hardware at their disposal.

58 GEOSCIENCES↗
DOE OSTI2024

SOURCES4D

SOURCES is a code for computing neutron source rates and spectra from spontaneous fission (including delayed neutrons) and (alpha,n) reactions in homogeneous materials and (alpha,n) reactions in single-interface and two-interface geometries. SOURCES is a Los Alamos National Laboratory (LANL) code that is written in FORTRAN and distributed through the Radiation Safety Information Computation Center (RSICC). LANL’s last release of SOURCES to RSICC was SOURCES4C in 2002. This disclosure covers the latest version of SOURCES, SOURCES4D. This version adds sensitivity capabilities for (alpha,n) sources in homogeneous materials. Specifically, SOURCES4D writes new output that can be used to calculate, in post-processing, first and second derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide densities in a homogeneous material and first derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide stopping powers and (alpha,n) cross sections (nuclear data). These derivatives are useful for uncertainty quantification, predictive modeling, and other applications in neutron transport problems.

Favorite, Jeffrey A.↗
DOE OSTI2023

Nanoscale Surface Structure of Nanometer-Thick Ferroelectric BaTiO 3 Films Revealed by Synchrotron X-ray Scanning Tunneling Microscopy: Implications for Catalytic Adsorption Reactions

Ferroelectric nanomaterials are of interest in catalysis, non-volatile memory, and neuromorphic computing among other applications because of their switchable structure that can alter electronic and interface properties of a single material. The investigation of the role of polarization on the surface structure and chemistry of ferroelectric nanomaterials is a longstanding challenge, as it ideally requires a combination of both nanoscale imaging and chemical spectroscopy. In this work we study a model ferroelectric BaTiO 3 thin film by synchrotron X-ray scanning tunneling microscopy (SX-STM), a unique method which integrates nanoscale surface imaging and chemically sensitive spectroscopy. We find that polarization switching from downward to upward in (001)single crystalline BaTiO 3 thin films increases the intensity of X-ray absorption across Ba M, Ti L and O K edges. Chemical mapping of nanometer sized domains further demonstrates the modulation of surface structures upon polarization switching, as well as confirming the trends observed in single point experiments across the surface. Here, we complement these measurements with ab-initio computational absorption spectroscopy to elucidate the effect of polarization switching on the core-hole excitations using the Bethe-Salpeter equation approach. Our experimental and theoretical results thus confirm a stronger binding strength for the upward polarized surface with molecular O 2 as a model reactant, offering mechanistic evidence that supports previous reports. This work advances the understanding of the surface chemistry and electronic structure of ferroelectrics, which can ultimately aid strategies to design interfaces with tailored properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Foundational Science to Accelerate Nuclear Energy Innovation [Brochure]

The foundational science gaps inhibiting the advancement of nuclear energy technologies are identified and tackled in five priority research opportunities. These opportunities pave the way to accelerate the development and ultimately the adoption of new nuclear energy systems. They include the fundamental aspects of ion-electron interactions; novel properties of next-generation coolants and solvents; interfacial dynamics, not only in solids, but in other aspects of nuclear reactors; novel operando and in-situ monitoring and sensing; and artificial intelligence to accelerate condensed phases discovery. Building on the foundation established by previous BES workshops, these opportunities encompass recent advances in fundamental knowledge and focus on the experimental and computational methods needed to resolve major technical challenges for nuclear energy technologies. Through developing fundamental scientific insight as well as pushing the frontiers of modeling complex systems and probing the operation of materials and chemical systems in extreme environments, research motivated by the priorities identified here will further develop the promise, potential, and utilization of nuclear energy for a clean energy future. The PROs are as follows: (1) Master complex electronic structures to tailor thermochemical reactivity, transport, and microstructural evolution; (2) Interrogate and direct the physics and chemistry underpinning next-generation coolants and solvents; (3) Elucidate and control the underlying physics and chemistry of interfaces in complex nuclear environments; (4) Bridge multi-fidelity multi-resolution experiments, computational modeling, and data science to control dynamic behavior; and (5) Harness artificial intelligence to design inherently resilient condensed phases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

High order explicit local time stepping methods for hyperbolic conservation laws

In this paper we present and analyze a general framework for constructing high order explicit local time stepping (LTS) methods for hyperbolic conservation laws. In particular, we consider the model problem discretized by Runge-Kutta discontinuous Galerkin (RK-DG) methods and design LTS algorithms based on the strong stability preserving Runge-Kutta (SSP-RK) schemes, that allow spatially variable time step sizes to be used for time integration in different regions of the computational domain. The proposed algorithms are of predictor-corrector type, in which the interface information along the time direction is first predicted based on the SSP-RK approximations and Taylor expansions, and then the fluxes over the region of the interface are corrected to conserve mass exactly at each time step. Following the proposed framework, we detail the corresponding LTS schemes with accuracy up to the fourth order, and prove their conservation property and nonlinear stability for the scalar conservation laws. Numerical experiments are also presented to demonstrate excellent performance of the proposed LTS algorithms.

58 GEOSCIENCES↗
DOE OSTI2023

EDX Spatial: Leveraging cloud and hybrid data management resources for spatial data

In the last few years, the National Energy Technology Laboratory has started leveraging cloud-hosted services for hosting spatial data collections published on the Energy Data eXchange (EDX). Using cloud-hosted storage and compute options offers multiple benefits for visualization and tool development through utilization of spatial data resources. The transition from on-premises services to cloud-hosted services has enabled a few key features: increased accessibility of large derivative datasets, dynamic integration of external authoritative data resources directly from outside entities through representational state transfer application programming interfaces (REST API), and the ability to produce complex mapping applications, dashboards, and online maps. As a result of the shift, NETL has launched EDX Spatial, a platform that leverages on-premises resources combined with cloud compute capabilities to enable enhanced online mapping interfaces and optimize data access. In addition, a unified workflow for handling the public release of spatial data products through EDX has been developed, including standardization of data hosting practices, metadata, symbology, and application elements. This poster reviews the opportunity of leveraging cloud-hosted and hybrid data management solutions for spatial data, and discusses the benefits and lessons learned while leveraging these services through the data repository EDX.

Morkner, Paige↗