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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A scalable nonlinear fluid–structure interaction solver based on a Schwarz preconditioner with isogeometric unstructured coarse spaces in 3D

Nonlinear fluid-structure interaction (FSI) problems on unstructured meshes in 3D appear many applications in science and engineering, such as vibration analysis of aircrafts and patient-specific diagnosis of cardiovascular diseases. In this work, we develop a highly scalable, parallel algorithmic and software framework for FSI problems consisting of a nonlinear fluid system and a nonlinear solid system, that are coupled monolithically. The FSI system is discretized by a stabilized finite element method in space and a fully implicit backward difference scheme in time. To solve the large, sparse system of nonlinear algebraic equations at each time step, we propose an inexact Newton-Krylov method together with a multilevel, smoothed Schwarz preconditioner with isogeometric coarse meshes generated by a geometry preserving coarsening algorithm. Here ''geometry'' includes the boundary of the computational domain and the wet interface between the fluid and the solid. We show numerically that the proposed algorithm and implementation are highly scalable in terms of the number of linear and nonlinear iterations and the total compute time on a supercomputer with more than 10,000 processor cores for several problems with hundreds of millions of unknowns.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Scalable phononic metamaterials: Tunable bandgap design and multi-scale experimental validation

Phononic metamaterials offer unprecedented control over wave propagation, making them essential for applications such as vibration isolation, waveguiding, and acoustic filtering. However, achieving scalable and precisely tunable bandgap properties across different length scales remains challenging. This study presents a user-friendly design framework for phononic metamaterials, enabling ultra-wide bandgap tunability (B/ω c ratios up to 172 %) across multiple frequency ranges and scales. Using finite element simulations of a Yablonovite-inspired unit cell, we establish a comprehensive parametric design space that illustrates how geometric parameters, such as sphere size and beam diameter, controls bandgap width and frequency. The scalability and robustness of the framework are validated through experimental testing on additively manufactured structures at both macro (10 mm) and micro (80 µm) scales, fabricated using Stereolithography and Two-Photon Polymerization. Transmission loss measurements, conducted with piezoelectric transducers and laser vibrometry, closely match simulations in the kHz and MHz frequency ranges, confirming the reliability and consistency of the bandgap behavior across scales. This work bridges theory and experiments at multiple scales, offering a practical methodology for the rapid design of phononic metamaterials and expanding their potential for diverse applications across a broad range of frequencies.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Facile scalable synthesis of Co{sub 3}O{sub 4}/carbon nanotube hybrids as superior anode materials for lithium-ion batteries

Graphical abstract: Co{sub 3}O{sub 4}/MWCNT hybrids were synthesized via strong ultra-sonication assisted shaking processes. The resultant samples as anode electrode display enhanced cycling performance and rate capability compared with pure Co{sub 3}O{sub 4} particle. - Highlights: • Co{sub 3}O{sub 4}/MWCNT hybrids were synthesized via ultra-sonication assisted shaking process. • The resulting Co{sub 3}O{sub 4} nanoparticles are highly dispersed onto MWCNT network backbone. • Co{sub 3}O{sub 4}/MWCNT hybrid displays highly enhanced lithium storage properties. • The present synthetic approach is facile, controllable, and scalable. - Abstract: In this report, Co{sub 3}O{sub 4}/multiple-wall carbon nanotube (MWCNT) hybrid materials were synthesized via strong ultrasonication-assisted shaking and magnetic stirring processes. The prepared samples were well characterized by utilizing powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Raman spectroscopy techniques. Results indicated that the resulting Co{sub 3}O{sub 4} nanoparticles were highly dispersed in the MWCNT network backbone and further form Co{sub 3}O{sub 4}/MWCNT hybrid materials. The obtained Co{sub 3}O{sub 4}/MWCNT hybrids can be employed as anode electrode in Lithium-ion batteries and deliver as high as discharge capacity of 1250 mA h g{sup −1} at a current density of 0.2 C, additionally, 81% of the discharge capacity for sample 2 with 20 wt.% MWCNT loading could be retained after 70 cycles, which could be associated with the specific hybrid structure of the electrode as well as the addition of MWCNT. Most importantly, the present synthetic approach is facile, controllable, and scalable, which allowing it more easily adapted to prepare other hybrid materials with specific architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Scalable and template-free synthesis of nanostructured Na{sub 1.08}V{sub 6}O{sub 15} as high-performance cathode material for lithium-ion batteries

Highlights: • Nanostructured Na{sub 1.08}V{sub 6}O{sub 15} was synthesized through additive-free sol-gel process. • Prepared Na{sub 1.08}V{sub 6}O{sub 15} demonstrated high capacity and sufficient cycling stability. • The reaction temperature was optimized to allow scalable Na{sub 1.08}V{sub 6}O{sub 15} fabrication. - Abstract: Developing high-capacity cathode material with feasibility and scalability is still challenging for lithium-ion batteries (LIBs). In this study, a high-capacity ternary sodium vanadate compound, nanostructured NaV{sub 6}O{sub 15}, was template-free synthesized through sol-gel process with high producing efficiency. The as-prepared sample was systematically post-treated at different temperature and the post-annealing temperature was found to determine the cycling stability and capacity of NaV{sub 6}O{sub 15}. The well-crystallized one exhibited good electrochemical performance with a high specific capacity of 302 mAh g{sup −1} when cycled at current density of 0.03 mA g{sup −1}. Its relatively long-term cycling stability was characterized by the cell performance under the current density of 1 A g{sup −1}, delivering a reversible capacity of 118 mAh g{sup −1} after 300 cycles with 79% capacity retention and nearly 100% coulombic efficiency: all demonstrating its significant promise of proposed strategy for large-scale synthesis of NaV{sub 6}O{sub 15} as cathode with high-capacity and high energy density for LIBs.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Special Issue on Data-Intensive Scalable Computing Systems

Traditional high performance computing (HPC) systems were designed from a compute-centric perspective, with an emphasis on high floating point performance. As scientific and analytics applications become more data intensive, there is a need to rethink HPC system architectures, programming models, runtime systems, and tools with a focus on scalable data intensive computing. Industry approaches supporting data intensive applications have been highly successful, leading many in the HPC community to search for ways to adapt them to HPC hardware and software contexts. Conversely, industry looks to the HPC community for their expertise in designing, deploying, and using extremely large and high performance computing systems. This special issue contains seven articles, each of which is an extended version of a paper presented in the 2015 International Workshop on Data Intensive Scalable Computing Systems (DISCS-2015) held in Austin, Texas on November 15, 2015. The workshop program included papers that ranged from programming models to systems software to storage, each with a strong focus on data intensive computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Scalable line and plane relaxation in a parallel structured multigrid solver

The efficient solution of sparse, linear systems that arise through the discretization of partial differential equations remains a key challenge for a range of high performance scientific simulations. One approach for reducing data movement and improving performance is by exposing and exploiting structure in a problem through the use of robust structured multilevel solvers. By choosing coarsening that preserves the structure of the problem, these methods maintain efficient structured computation and communication throughout the multigrid hierarchy. However, when coarsening is not permitted to be dependent on the operator, anisotropy must be addressed by the smoother — producing error compatible for coarse-grid correction with structured coarsening. Here, the components required in a scalable parallel structured solver are described with a focus on memory and communication efficiency of robust smoothers. While the implementation of communication and memory reduction techniques in smoothers integrated in a complete 3D solver present a significant engineering challenge, a novel approach is proposed that addresses these challenges systematically through a change to the solver’s execution model. Enabled by user-level threading paired with a set of data and communication abstractions, this approach permits seamless aggregation of communication in plane smoothers — directly reusing code for a 2D distributed multilevel cycle. Results show an effective reduction in communication costs for coarse-grid problems, and result in a speedup of 8.7x in smoothing routines shown in Fig. 12 using this approach. This produces a significant improvement to strong scalability while maintaining favorable weak scaling behavior. Finally, a parallel scaling study using a series of refined meshes is included that demonstrates the effectiveness of this approach in an application of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Scalable Bottom-Up Synthesis of Nanoporous Hexagonal Boron Nitride ( h -BN) for Large-Area Atomically Thin Ceramic Membranes

Nanopores embedded within monolayer hexagonal boron nitride (h-BN) offer possibilities of creating atomically thin ceramic membranes with unique combinations of high permeance (atomic thinness), high selectivity (via molecular sieving), increased thermal stability, and superior chemical resistance. However, fabricating size-selective nanopores in monolayer h-BN via scalable top-down processes remains nontrivial due to its chemical inertness, and characterizing nanopore size distribution over a large area remains extremely challenging. Here, we demonstrate a facile and scalable approach of exploiting the chemical vapor deposition (CVD) process temperature to enable direct incorporation of subnanometer/nanoscale pores into the monolayer h-BN lattice, in combination with manufacturing compatible polymer casting to fabricate centimeter-scale nanoporous atomically thin ceramic membranes. We leverage diffusive transport of analytes including size-selective Ficoll sieving to characterize subnanometer-scale and nanoscale defects that manifest as pores in centimeter-scale h-BN membranes, overcoming previous limitations in large-area characterization of nanoscale defects in h-BN. Our approach opens a new frontier to advance atomically thin membranes to 2D ceramic materials, such as h-BN via facile and direct formation of nanopores, for size-selective separations.

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

Scalable Synthesis of Pt/SrTiO 3 Hydrogenolysis Catalysts in Pursuit of Manufacturing-Relevant Waste Plastic Solutions

Here, an improved hydrothermal synthesis for shape-controlled, size-controlled 60 nm SrTiO 3 nanocuboid (STO NC) supports, which facilitates the scalable creation of platinum nanoparticles catalyst supported on STO (Pt/STO) for the chemical conversion of waste polyolefins, is reported herein. This synthetic method: 1) produces STO NC supports with average sizes ranging from 25 – 80 nm with narrow size distributions 2) demonstrates how SrCO 3 formation and variation in solution pH prevent the formation of STO NCs, and 3) establishes that STO nucleation prior to the hydrothermal treatment favors nanocuboid formation. The updated hydrothermal synthesis was scaled-up and conducted in a 4L batch reactor, resulting in STO NCs of comparable size and morphology (m = 22.5 g, d avg = 58.6 ± 16.2 nm) to those synthesized under standard hydrothermal conditions in a lab-scale 125 mL autoclave reactor. Size-controlled STO NCs, ranging in roughly 10 nm increments from the 25 nm to 80 nm, were used to support Pt deposited through strong electrostatic adsorption (SEA), a practical and scalable solution-based method. Using SEA techniques and a STO support with an average size of 39.3 ± 6.3 nm, a Pt/STO catalyst with 3.6 wt% Pt was produced and used for high-density polyethylene hydrogenolysis under previously-reported conditions (170 psi H 2 , 300°C, 96h; final product: M w = 2400, Ð = 1.03). As a well-established model system for studying the behavior of heterogeneous catalysts and their supports in reactions, the Pt/STO system detailed in this work presents a unique opportunity to simultaneously convert waste plastic into commercially-viable products while gaining fundamental insight into the mechanism of polyethylene hydrogenolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Area-Scalable Zn 2 SnO 4 Electron Transport Layer for Highly Efficient and Stable Perovskite Solar Modules

The development of a scalable chemical bath deposition (CBD) process facilitates the realization of electron-transporting layers (ETLs) for large-area perovskite solar modules (PSMs). In this work, a method to prepare a uniform and scalable thick Zn 2 SnO 4 ETL by CBD, which yielded high-performance PSMs, is reported. This Zn 2 SnO 4 ETL exhibits excellent electrical properties and enhanced optical transmittance in the visible region. Moreover, the Zn 2 SnO 4 ETL influences the perovskite layer formation, yielding enhanced crystallinity, increased grain size, and a smoother surface, thus facilitating electron extraction and collection from the perovskite to the ETL. Zn 2 SnO 4 thereby yields PSMs with a remarkable photovoltaic performance, low hysteresis index, and high device reproducibility. The champion PSM exhibited a power conversion efficiency (PCE) of 22.59%, being among the highest values published so far. In addition, the CBD Zn 2 SnO 4 -based PSMs exhibit high stability, retaining more than 88% of initial efficiency over 1000 h under continuous illumination. This demonstrates that CBD Zn 2 SnO 4 is an appropriate ETL for high-efficiency PSMs and a viable new process for their industrialization.

17 WIND ENERGY↗
DOE OSTI2025

Scalable Solution-Processed Electrolyte Membranes with Optimized Microstructure for High-Performance Protonic Ceramic Electrochemical Cells

Proton-conducting electrochemical cells (PCECs) are promising for efficient hydrogen production, but achieving dense, uniform, thin electrolyte layers remains a key challenge, particularly for scalable fabrication. Here, we present a solution-processed deposition approach with a mechanistically optimized slurry for uniform electrolyte formation. By tailoring particle size distribution, solid loading, and solvent/additive balance, we regulated wetting behavior and evaporation kinetics of the electrolyte slurry to promote homogeneous electrolyte particle packing. These features facilitate tight grain boundary contact and early stage neck growth during sintering, eliminating residual porosity, and improving mechanical integrity. The resulting ∼15 μm thick electrolyte shows high density, strong electrode adhesion, and stable interfaces outperforming the previously reported spray-based fabricated electrolyte by about 31% at 600 °C in FC mode. Single cells deliver 0.962 W cm –2 at 600 °C in fuel cell mode and 1.31 A cm –2 at 1.3 V in electrolysis mode, maintaining robust performance over 100 h with negligible degradation (≤0.02% h –1 ) in each mode. Scale-up to 2.5 cm diameter substrates confirmed reproducible densification and geometric stability. This work demonstrates a cost-effective, scalable route where control over particle-fluid interactions and drying dynamics enables a superior electrolyte microstructure and high PCEC performance.

dense microstructure↗
DOE OSTI2019

Scalable Light-Printing of Substrate-Engraved Free-Form Metasurfaces

A key challenge for metasurface research is locally controlling at will the nanoscale geometric features on meter-scale apertures. Such a technology is expected to enable large aperture meta-optics and revolutionize fields such as long-range imaging, lasers, laser detection and ranging (LADAR), and optical communications. Furthermore, these applications are often more sensitive to light-induced and environmental degradation, which constrains the possible materials and fabrication process. Here, we present a relatively simple and scalable method to fabricate a substrate-engraved metasurface with locally printed index determined by induced illumination, which, therefore, addresses both the challenges of scalability and durability. In this process, a thin metal film is deposited onto a substrate and transformed into a mask via local laser-induced dewetting into nanoparticles. The substrate is then dry-etched through this mask, and selective mask removal finally reveals the metasurface. We show that masking by the local nanoparticle distribution, and, therefore, the local index, is dependent on the local light-induced dewetting temperature. Here, we demonstrate printing of a free-form pattern engraved into a fused silica glass substrate using a laser raster scan. Large-scale spatially controlled engraving of metasurfaces has implications on other technological fields beyond optics, such as surface fluidics, acoustics, and thermomechanics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalable Polymeric Few-Nanometer Organosilica Membranes with Hydrothermal Stability for Selective Hydrogen Separation

Nanoporous silica membranes exhibit excellent H 2 /CO 2 separation properties for sustainable H 2 production and CO 2 capture but are prepared via complicated thermal processes above 400 °C, which prevent their scalable production at a low cost. Here, we demonstrate the rapid fabrication (within 2 min) of ultrathin silica-like membranes (~3 nm) via an oxygen plasma treatment of polydimethylsiloxane-based thin-film composite membranes at 20 °C. The resulting organosilica membranes unexpectedly exhibit H2 permeance of 280-930 GPU (1 GPU = 3.347 x 10 -10 mol m -2 s -1 Pa -1 ) and H2/CO2 selectivity of 93-32 at 200 °C, far surpassing state-of-the-art membranes and Robeson’s upper bound for H 2 /CO 2 separation. When challenged with a 3 d simulated syngas test containing water vapor at 200 °C and a 340 d stability test, the membrane shows durable separation performance and excellent hydrothermal stability. The robust H 2 /CO 2 separation properties coupled with excellent scalability demonstrate the great potential of these organosilica membranes for economic H 2 production with minimal carbon emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Highly Selective Heterogeneous Ethylene Dimerization with a Scalable and Chemically Robust MOF Catalyst

Metal–organic frameworks (MOFs) hold great promise as structurally tunable catalysts capable of high selectivity in the solid state, yet their comparatively high cost and often limited stability remain significant concerns for their commercialization as heterogeneous catalysts. In this paper, we report detailed X-ray absorption spectroscopy studies of Co- and Ni-MFU-4$l$, a class of highly selective MOF catalysts for olefin upgrading, and reveal mechanisms that lead to their deactivation. We further show that Ni-CFA-1, a more scalable and economical alternative to Ni-MFU-4l, reproduces both the local coordination structure and the high selectivity of the latter in ethylene dimerization catalysis. Under optimal conditions, Ni-CFA-1 activated by MMAO-12 achieves a turnover frequency of 37100 per hour and a selectivity of 87.1% for 1-butene, a combination of activity, selectivity, and affordability that is unmatched among heterogeneous ethylene dimerization catalysts. Ni-CFA-1 retains its high activity for at least 12 h in a one-liter semibatch reactor, offering a strategy toward robust and scalable MOFs for industrial catalysis.

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

A Scalable Semi-Implicit Barotropic Mode Solver for the MPAS-Ocean

A scalable semi-implicit barotropic mode solver for the ocean component of the model for prediction across scales has been implemented as a competitor to an existing explicit-subcycling scheme to allow faster and more stable simulations while not sacrificing accuracy. The semi-implicit solver adopts the pipelined preconditioned bi-conjugate gradient stabilization algorithm as an iterative solver in conjunction with the restricted additive Schwarz preconditioner that accelerates the convergence rate of the iterative solver. The preconditioner is constructed from a linearized barotropic system that also reorders the system for optimal performance, while the semi-implicit solver deals with the fully nonlinear barotropic system that requires reassembly of the coefficient matrix for every time step. Several numerical experiments, from simple one-dimensional tests to three-dimensional real-world tests, demonstrate that the semi-implicit solver has almost the same accuracy and better parallel scalability compared with the existing scheme while allowing faster and more stable simulations. Furthermore, the semi-implicit solver accelerates the barotropic mode up to 2.9 times faster than the existing scheme on 16,320 processors, leading to an overall runtime speedup of 1.9.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Scalable fabrication of perovskite solar cells

Perovskite materials use earth-abundant elements, have low formation energies for deposition and are compatible with roll-to-roll and other high-volume manufacturing techniques. These features make perovskite solar cells (PSCs) suitable for terawatt-scale energy production with low production costs and low capital expenditure. Demonstrations of performance comparable to that of other thin-film photovoltaics (PVs) and improvements in laboratory-scale cell stability have recently made scale up of this PV technology an intense area of research focus. Here, we review recent progress and challenges in scaling up PSCs and related efforts to enable the terawatt-scale manufacturing and deployment of this PV technology. We discuss common device and module architectures, scalable deposition methods and progress in the scalable deposition of perovskite and charge-transport layers. We also provide an overview of device and module stability, module-level characterization techniques and techno-economic analyses of perovskite PV modules.

14 SOLAR ENERGY↗
DOE OSTI2026

BiG-SCAPE 2.0 and BiG-SLiCE 2.0: scalable, accurate and interactive sequence clustering of metabolic gene clusters

Microbial metabolic gene clusters encode the biosynthesis or catabolism of metabolites that facilitate ecological specialization, mediate microbiome interactions and constitute a major source of medicines and crop protection agents. Here, we present BiG-SCAPE and BiG-SLiCE 2.0, next-generation methods that facilitate scalable, accurate and interactive gene cluster analyses. BiG-SCAPE 2.0 updates its classification, alignment methods, and visualizations, enabling more accurate analysis, up to 8x faster runtimes and halved memory requirements. BiG-SLiCE 2.0 updates its distance metric, pHMM database, and classification logic, resulting in increased sensitivity nearing that of BiG-SCAPE. Analysis of 260,630 biosynthetic gene clusters from publicly available genomes reveals that both tools generate concurring estimates of gene cluster diversity, thus providing significantly extended methodological support for recent evidence indicating that the vast majority of natural product diversity remains unexplored. Together, these updates will facilitate global genome mining efforts for natural product discovery and microbiome analyses scalable with current data sizes.

Draisma, Arjan [Wageningen University & Research (↗
DOE OSTI2018

Scalable energy-efficient magnetoelectric spin–orbit logic

Since the early 1980s, most electronics have relied on the use of complementary metal–oxide–semiconductor (CMOS) transistors. However, the principles of CMOS operation, involving a switchable semiconductor conductance controlled by an insulating gate, have remained largely unchanged, even as transistors are miniaturized to sizes of 10 nanometres. We investigated what dimensionally scalable logic technology beyond CMOS could provide improvements in efficiency and performance for von Neumann architectures and enable growth in emerging computing such as artifical intelligence. Such a computing technology needs to allow progressive miniaturization, reduce switching energy, improve device interconnection and provide a complete logic and memory family. Here we propose a scalable spintronic logic device that operates via spin–orbit transduction (the coupling of an electron’s angular momentum with its linear momentum) combined with magnetoelectric switching. The device uses advanced quantum materials, especially correlated oxides and topological states of matter, for collective switching and detection. We describe progress in magnetoelectric switching and spin–orbit detection of state, and show that in comparison with CMOS technology our device has superior switching energy (by a factor of 10 to 30), lower switching voltage (by a factor of 5) and enhanced logic density (by a factor of 5). Additionally, its non-volatility enables ultralow standby power, which is critical to modern computing. The properties of our device indicate that the proposed technology could enable the development of multi-generational computing.

42 ENGINEERING↗