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Results for “multicomponent”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pre–T cell receptors topologically sample self-ligands during thymocyte β-selection

Self-discrimination, a critical but ill-defined molecular process programmed during thymocyte development, requires myriad pre–T cell receptors (preTCRs) and αβTCRs. Using x-ray crystallography, we show how a preTCR applies the concave β-sheet surface of its single variable domain (Vβ) to “horizontally” grab the protruding MHC α2-helix. By contrast, αβTCRs purpose all six complementarity-determining region (CDR) loops of their paired VαVβ module to recognize peptides bound to major histocompatibility complex molecules (pMHCs) in “vertical” head-to-head binding. Additionally, the preTCR topological fit ensures that CDR3β reaches the peptide’s featured C-terminal segment for pMHC sampling, establishing the subsequent αβTCR canonical docking mode. “Horizontal” docking precludes germline CDR1β- and CDR2β-MHC binding to broaden β-chain repertoire diversification before αβTCR-mediated selection refinement. Thus, one subunit successively attunes the recognition logic of related multicomponent receptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Gradient cell–structured high-entropy alloy with exceptional strength and ductility

We report that similar to conventional materials, most multicomponent high-entropy alloys (HEAs) lose ductility as they gain strength. In this study, we controllably introduced gradient nanoscaled dislocation cell structures in a stable single-phase HEA with face-centered cubic structure, thus resulting in enhanced strength without apparent loss of ductility. Upon application of strain, the sample-level structural gradient induces progressive formation of a high density of tiny stacking faults (SFs) and twins, nucleating from abundant low-angle dislocation cells. Furthermore, the SF-induced plasticity and the resultant refined structures, coupled with intensively accumulated dislocations, contribute to plasticity, increased strength, and work hardening. These findings offer a promising paradigm for tailoring properties with gradient dislocation cells at the nanoscale and advance our fundamental understanding of the intrinsic deformation behavior of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Superconducting vortices carrying a temperature-dependent fraction of the flux quantum

Magnetic field penetrates type-II bulk superconductors by forming quantum vortices that enclose a magnetic flux equal to the magnetic flux quantum. The flux quantum is a universal quantity that depends only on fundamental constants. In this study, we investigated isolated vortices in the hole-overdoped Ba 1–x K x Fe 2 As 2 (x = 0.77) by using scanning superconducting quantum interference device (SQUID) magnetometry. In many locations, we observed objects that carried only part of a flux quantum, with a magnitude that varied continuously with temperature. Here, we demonstrated mobility and manipulability of these objects and interpreted them as quantum vortices with nonuniversally quantized (fractional) magnetic flux whose magnitude is determined by the temperature-dependent parameters of a multicomponent superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

High-field superconducting halo in UTe 2

The heavy fermion material UTe 2 is a candidate topological superconductor that exhibits multiple magnetic field–induced superconducting phases. One such phase exists only at fields greater than 40 tesla, a considerable scale given its critical temperature of only 2 K. Here, in this work, we extend measurements of this state with fields outside of the bc crystallographic plane and reveal its core structure: The superconducting phase wraps around the b axis in a halo-like fashion and appears to be stabilized by a field component perpendicular to the magnetic easy axis. This angle dependence points to a multicomponent spin-triplet order parameter with a finite angular momentum of the Cooper pairs. The pairing mechanism remains enigmatic, and UTe 2 ’s specific magnetophilic superconducting tendencies seem incompatible with existing models for field-enhanced superconductivity.

Lewin, Sylvia K. [National Inst. of Standards and ↗
DOE OSTI2023

On-Wafer Wide-Pore Anodic Aluminum Oxide

Anodized aluminum oxide (AAO) has been used as nanotemplates for nanomaterials and nanodevice fabrications. Microfabrication techniques are attracting attention for nanodevice synthesis. However, AAO requires a microfabrication-compatible substrate due to its brittleness. While there are studies that already show AAO on compatible substrates, the pore sizes may not be applicable for multicomponent nanodevices. In this study, wide pore AAOs with ohmic bottom contacts are fabricated on 76 mm Si wafers. Sputtering was used to deposit Al along with supporting layers to achieve this goal. A quiescent electropolishing technique was used to smooth the surface of Al. Standard photolithography was used to define the active area on the Al for anodization. Then 195 V two-step anodization was performed to fabricate wide pore AAOs with pore diameters ranging from 130 ± 32 nm to 400 ± 31 nm with interpore distance of 480 ± 47 nm. Furthermore, it also showed that the ordering of the pores depended on the current density over the more conventional anodization time.

25 ENERGY STORAGE↗
DOE OSTI2023

Electrochemical Measurement of Water Transport Numbers in Anion-Exchange Membranes

Anion-exchange membranes (AEMs) are a possible replacement for perfluorosulfonic-acid membranes in energy-conversion devices, primarily due to the hydroxide mobile ion allowing the devices to operate in alkaline conditions with less expensive electrocatalysts. However, the transport properties of AEMs remain understudied, especially electro-osmosis. In this work, an electrochemical technique, where the open-circuit voltage is measured between two ends of a membrane maintained at different relative humidities, is used to determine the water transport number of various ionomers, including Versogen and Sustainion AEMs and Nafion cation-exchange membrane (CEM), as a function of water content and temperature. In addition, the CEMs and AEMs are examined in differing single-ion forms, specifically proton and sodium (CEM) and hydroxide and carbonate (AEM). Carbonate-form AEMs have the highest transport number (∼11), followed by sodium-form CEMs (∼8), hydroxide-form AEMs (∼6), and proton-form CEMs (∼3). Finally, a multicomponent transport model based on the Stefan-Maxwell-Onsager framework of binary interactions is used to develop a link between water transport number and water-transport properties, extracting a range for the unmeasured membrane water permeability of Versogen as a function of water content.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

toughio v1.2.2

TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few. `toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. Currently, to the best of our knowledge, only PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments).

Luu, Keurfon↗
DOE OSTI2023

PFLOTRAN 5

PFLOTRAN leverages massively parallel, high performance computing to simulate large-scale non-isothermal multiphase flow, multicomponent reactive transport and electrical resistivity tomography (ERT) problems in the subsurface environment. Researchers have employed PFLOTRAN to simulate these Earth system processes on leadership class supercomputers for over two decades. The code is designed to predict the future estate of environmental systems and better inform stakeholders in the regulatory decision making process (e.g., fate of contaminants, long-term stewardship for nuclear waste, impact of climate change, etc.). A diverse team of scientists oversees PFLOTRAN development and maintenance under an open-source licensing agreement and manages contributions from an international community of researchers.

Hammond, Glenn↗
DOE OSTI2026

LBM3RT

Lattice Boltzmann Methods for Multiphase Multicomponent Reactive Transport

Kang, Qinjun↗
DOE OSTI2023

Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

Abstract MF-LOGP, a new method for determining a single component octanol–water partition coefficients ( $$LogP$$ LogP ) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make $$LogP$$ LogP predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average $$RMSE$$ RMSE = 0.77 ± 0.007, $$MAE$$ MAE = 0.52 ± 0.003, and $${R}^{2}$$ R 2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ( $$RMSE$$ RMSE = 0.42–1.54, $$MAE$$ MAE = 0.09–1.07, and $${R}^{2}$$ R 2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures. Graphical Abstract

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

Vector elastic deconvolution migration with dual wavefield decomposition

Here, we report elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

58 GEOSCIENCES↗
DOE OSTI2026

Model Data Archive Associated with Manuscript "Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon"

This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.

ATS↗
DOE OSTI2020

Microstructural characterization of phase-separated co-deposited Cu–Ta immiscible alloy thin films

Elevated temperature co-sputtering of immiscible elements ends in a variety of self-organized morphologies due to phase separation. Cu–Ta is used as a model system to understand the evolution of phase-separated microstructural morphologies by co-sputtering thin films with nominal 50–50 at.% composition at four temperatures: 25, 400, 600, and 800 °C. Scanning/transmission electron microscopy of the film cross sections showed the microstructure morphology varied from nanocrystalline Cu–Ta at 25 °C to a wavy ribbon-like structure at 400 °C, to Cu-rich agglomerates surrounded by Ta-rich veins at 600 and 800 °C. In the agglomerate-vein morphology, microstructural features were present on two length scales, from a few nanometers to a few tens of nanometers, thus making the structures hierarchical. On the nanoscale, the Cu-rich agglomerates contained Ta precipitates, whereas the Ta-rich veins had embedded Cu nanocrystals. The various microstructures can be attributed to the highly disparate constituent element interdiffusion at the deposition temperatures with the Cu having orders of magnitude higher mobility than Ta at the deposition temperatures. This research of processing–microstructure relationship will be useful in guiding the design of hierarchical multiphase microstructures in binary or multicomponent thin films with tailored mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Thermodynamics of grain-boundary phases

The past decade has seen a significant increase in research efforts aimed at understanding the thermodynamics of low-dimensional phases existing in many materials systems, ranging from two-dimensional materials to core regions of extended defects in crystalline solids. We review the current status of theoretical, computational, and experimental research on the “defect phases,” focusing on grain boundaries (GBs) in elemental and multicomponent polycrystalline materials. After reviewing the generalized concept of a phase of any dimensionality, we discuss recent progress in atomistic computer simulations of GB phase transformations and phase coexistences, including the observation of one-dimensional defects separating GB phases (defects in defects). Computational predictions compare well with experimental observations of multiple GB phases and segregation-induced phase transformations. An intriguing open question of GB thermodynamics is whether the GB free energy can be driven to a zero value by increasing solute segregation. We review recent efforts to understand this ultimate thermodynamic stabilization of GB phases and the possible polycrystalline microstructures that may arise. An outlook for future research in the field is discussed.

Materials science↗
DOE OSTI2023

Theoretical Multinary Perovskite Oxides Dataset

Perovskite oxides (ternary chemical formula ABO3) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, the AA'BB'O6 compositions were generated in the a-b+a- Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with DFT using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔHf) and decomposition enthalpies (ΔHd) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated AA'BB'O6 perovskite structures using MP-compatible DFT calculations

Bare, Zachary↗
DOE OSTI2020

A Pilot-Scale Evaluation of Natural Gas-Based Foam at Elevated Pressure and Temperature Conditions

Abstract Nitrogen (N2) and Carbon Dioxide (CO2) foams have been used as hydraulic fracturing fluids for several decades to reduce water usage and minimize damage in water-sensitive reservoirs. These foam treatments require gases to be liquefied and transported to site. An alternative approach would be to use natural gas (NG) that is readily available from nearby wells, pipelines, and processing facilities as the internal, gaseous phase to create a NG-based foam. Hydraulic fracturing with NG foam is a relatively inexpensive option, makes use of an abundant and often wasted resource, and may even provide production benefits in certain reservoirs. As part of an ongoing development project sponsored by the Department of Energy (DOE), the surface process to create NG foam is being developed and the properties of NG foam are being explored. This paper presents recent results from a rigorous pilot-scale demonstration of NG foam over a range of operating scenarios relevant to surface and bottomhole conditions with a variety of base-fluid mixtures. The Pilot-scale Foam Test Facility (PFTF) used in these investigations is first described. The PFTF is capable of generating foamed fluids at pressures up to 7,500 psig and at temperatures in excess of 300°F. Then, results from several investigations aimed at proving NG foam at conditions relevant to the field are presented. NG foam was characterized using rheology measurements and flow visualization techniques. Experiments were performed to investigate the texture and stability of NG foam generated by two different mixing methods: one using a custom designed tee to match mixing velocities in the field where the gas phase is jetted into the aqueous stream, and another to ensure comprehensive mixing for laboratory analysis. Parametric studies were conducted to explore the effects of flow rate, foam quality, and temperature on the stability of NG foam. Moreover, different fluid preparations were used to investigate the effect of base fluid and additive concentrations on the stability of NG foams. Additional laboratory studies that investigated foam stability with produced water and multicomponent NG mixtures are also reported. The NG foams explored in these investigations exhibited typical, shear-thinning behavior observed in rheological studies of N2- and CO2-based foams. The measured viscosity and observed stability indicate that NG foams are well suited for fracturing applications. Like other foams, NG foam exhibits sensitivity to operating temperature characterized by a decrease in apparent viscosity as temperature increases. Rapid foam breakdown was observed at significantly elevated temperatures exceeding 290°F. In addition to fluid characterization, these investigations also yielded several key lessons that should be applied to future field demonstrations of NG foam.

Beck, Griffin↗