Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Scalable”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Stable Thermotropic 3D and 2D Double Gyroid Nanostructures with Sub-2-nm Feature Size from Scalable Sugar–Polyolefin Conjugates

In this study, ultra-low molecular weight disaccharide–polyolefin conjugates with cellobiose, lactose and maltose head groups and atactic polypropene tails, such as 1, undergo a series of irreversible thermotropic order–order transitions with increasing temperature to provide nanostructured phases in the sequence: lamellar (L), hexagonal perforated lamellar (HPL), double gyroid (DG) and hexagonal cylindrical (C). The DG phase displays exceptional stability at ambient temperature and features two interpenetrating sugar domain networks having a sub-2-nm strut width and a lattice parameter, a DG , of 13.1 nm. The unique stability of this DG phase extends further within ultrathin films all the way down to the two-dimensional limit of 15 nm in which film thickness, l, is now less than the surface-oriented unit cell height, h DG . In addition to raising the fundamental question of what minimally constitutes a Schoen triply periodic minimal surface and DG lattice, these results serve to establish the class of sugar–polyolefin conjugates as a new material platform for nanoscience and nanotechnology.

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

Stable Thermotropic 3D and 2D Double Gyroid Nanostructures with Sub‐2‐nm Feature Size from Scalable Sugar–Polyolefin Conjugates

Abstract Ultra‐low molecular weight disaccharide–polyolefin conjugates with cellobiose, lactose and maltose head groups and atactic polypropene tails, such as 1 , undergo a series of irreversible thermotropic order–order transitions with increasing temperature to provide nanostructured phases in the sequence: lamellar ( L ), hexagonal perforated lamellar ( HPL ), double gyroid ( DG ) and hexagonal cylindrical ( C ). The DG phase displays exceptional stability at ambient temperature and features two interpenetrating sugar domain networks having a sub‐2‐nm strut width and a lattice parameter, a DG , of 13.1 nm. The unique stability of this DG phase extends further within ultrathin films all the way down to the two‐dimensional limit of 15 nm in which film thickness, l , is now less than the surface‐oriented unit cell height, h DG . In addition to raising the fundamental question of what minimally constitutes a Schoen triply periodic minimal surface and DG lattice, these results serve to establish the class of sugar–polyolefin conjugates as a new material platform for nanoscience and nanotechnology.

Nowak, Samantha R.↗
DOE OSTI2025

Scalable Hyperpolarized MRI Enabled by Ace‐SABRE of [1‐ 13 C]Pyruvate

Abstract Hyperpolarized (HP) MRI using [1– 13 C]pyruvate is emerging as a promising molecular imaging approach. Among hyperpolarization methods, Signal Amplification By Reversible Exchange (SABRE) is attractive because SABRE polarizes the substrates directly in room‐temperature solutions avoiding complex hardware. Most SABRE experiments have historically been performed in methanol, a relatively toxic and difficult‐to‐remove solvent. Here we demonstrate the use of a 80/20 acetone/water (A/W) solvent system (Ace‐SABRE) to provide hyperpolarized [1– 13 C]pyruvate with up to 17% polarization, then implement a solvent processing protocol to achieve injectable solutions retaining 74% of the initial polarization, and lastly we demonstrate HP in vivo spectroscopy and imaging using the Ace‐SABRE platform to showcase metabolic tracking in a hepatocellular carcinoma (HCC) tumor as well as HP‐MRI, both in direct comparison to dissolution dynamic nuclear polarization (d‐DNP) experiments. The Ace‐SABRE technique promises faster adoption of SABRE hyperpolarization in biological experiments, overall lowering the barriers to entry for HP‐NMR and HP‐MRI.

Chemistry↗
DOE OSTI2016

Scalable synthesis of palladium icosahedra in plug reactors for the production of oxygen reduction reaction catalysts

We have synthesized Pd icosahedra with uniform, controllable sizes in plug reactors separated by air. The oxygen contained in the air segments not only contributed to the generation of a reductant from diethylene glycol in situ, but also oxidized elemental Pd back to the ionic form by oxidative etching and thus slowed down the reduction kinetics. Compared to droplet reactors involving silicone oil or fluorocarbon, the use of air as a carrier phase could reduce the production cost by avoiding additional procedures for the separation of products from the oil. The average diameters of the Pd icosahedra could be readily controlled in the range of 12–20 nm. The Pd icosahedra were further employed as seeds for the production of Pd@Pt 2–3L core-shell icosahedra, which could serve as a catalyst toward the oxygen reduction reaction with greatly enhanced activity. As a result, we believe that the plug reactors could be extended to other types of noble-metal nanocrystals for their scale-up production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Interfacing HDF5 with a scalable object‐centric storage system on hierarchical storage

Summary Object storage technologies that take advantage of multitier storage on HPC systems are emerging. However, to use these technologies at present, applications have to be modified significantly from current I/O libraries. HDF5, a widely used I/O middleware on HPC systems, provides a virtual object layer (VOL) that allows applications to connect to different storage mechanisms transparently without requiring significant code modifications. We recently designed the proactive data containers (PDC) object‐centric storage system that provides the capabilities of transparent, asynchronous, and autonomous data movement taking advantage of multiple storage tiers—a decision that has so far been left upon the user on most current systems. To enable PDC's features through HDF5 without modifying application codes, we have developed an HDF5 VOL connector that interfaces with PDC. We present in this article the connector interface and evaluate its performance on Cori, a Cray XC40 supercomputer located at the National Energy Research Scientific Computing Center (NERSC). Our evaluation demonstrates up to an 8× improvement compared with HDF5 that has the most recent optimizations.

Mu, Jingqing↗
DOE OSTI2015

Scalable Preparation of Ternary Hierarchical Silicon Oxide-Nickel-Graphite Composites for Lithium-Ion Batteries

Silicon monoxide is a promising anode candidate because of its high theoretical capacity and good cycle performance. To solve the problems associated with this material, including large volume changes during charge-discharge processes, we report a ternary hierarchical silicon oxide–nickel–graphite composite prepared by a facile two-step ball-milling method. The composite consists of nano-Si dispersed silicon oxides embedded in nano-Ni/graphite matrices (Si@SiOx/Ni/graphite). In the composite, crystalline nano-Si particles are generated by the mechanochemical reduction of SiO by ball milling with Ni. These nano-Si dispersed oxides have abundant electrochemical activity and can provide high Li-ion storage capacity. Furthermore, the milled nano-Ni/graphite matrices stick well to active materials and interconnect to form a crosslinked framework, which functions as an electrical highway and a mechanical backbone so that all silicon oxide particles become electrochemically active. Owing to these advanced structural and electrochemical characteristics, the composite enhances the utilization efficiency of SiO, accommodates its large volume expansion upon cycling, and has good ionic and electronic conductivity. The composite electrodes thus exhibit substantial improvements in electrochemical performance. This ternary hierarchical Si@SiOx/Ni/graphite composite is a promising candidate anode material for high-energy lithium-ion batteries. Additionally, the mechanochemical ball-milling method is low cost and easy to reproduce, indicating potential for the commercial production of the composite materials.

25 ENERGY STORAGE↗
DOE OSTI2022

A scalable compressible volume of fluid solver using a stratified flow model

Here, in this paper, a Volume of Fluid method which uses a Stratified Flow model for flux calculation is proposed to solve a compressible multiphase flow in a way that has high parallel efficiency. The solver is part of an open-source computing tool to study fuel entrainment and combustion in the application of paraffin-based hybrid rocket motors. This paper focuses on the compressible Volume of Fluid solver for the liquid and gaseous phases in this environment. This solver uses perfect gas and stiffened gas models for equation of state, with the ability to easily add other models as desired. Additionally a comparison of a Riemann solver versus an AUSM+up scheme is conducted, showing improvement with the later in the solution of multiphase flows. This solver successfully reproduces shock tube cases with the expected accuracy, as well as simulating two-dimensional shear and gravity-driven flows. Results also show that the code is able to utilize a Stratified Flow model to evaluate shear flow without the need for interface reconstruction or gradient calculations. Finally, it is shown that the solver has near-ideal scaling under strong scaling tests as well as good performance in static scaling, giving improved performance over current options and implying future advancement of high-performance computing efficiency for multiphase flow solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Scalable Synthesis and Multi-Electron Transfer of Aniline/Fluorene Copolymer for Solution-Processable Battery Cathodes

Here, the authors report the highly efficient, multigram-scale synthesis of an ester-functionalized, poly(aniline-co-fluorene) polymer. The excellent solubility and film-forming ability of this polymer facilitate its application as a reversible battery cathode. Electrochemical quartz crystal microbalance with dissipation monitoring confirms a multi-electron transfer process, resulting in a specific discharge capacity of 51 mAh g -1 and a high reversible doping level of 0.69. Galvanostatic cycling at 1 C demonstrates excellent electrode stability with a capacity retention of 95.2% after 100 cycles. Therefore, this work demonstrates a novel electroactive polymer that exemplifies how chemical functionality may be used to properly balance processability and electroactivity of macromolecular battery cathodes.

25 ENERGY STORAGE↗
DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗
DOE OSTI2018

Polymer Nanosheet Containing Star‐Like Copolymers: A Novel Scalable Controlled Release System

Abstract Poly(ε‐caprolactone) (PCL)‐based nanomaterials, such as nanoparticles and liposomes, have exhibited great potential as controlled release systems, but the difficulties in large‐scale fabrication limit their practical applications. Among the various methods being developed to fabricate polymer nanosheets (PNSs) for different applications, such as Langmuir–Blodgett technique and layer‐by‐layer assembly, are very effort consuming, and only a few PNSs can be obtained. In this paper, poly(ε‐caprolactone)‐based PNSs with adjustable thickness are obtained in large quantity by simple water exposure of multilayer polymer films, which are fabricated via a layer multiplying coextrusion method. The PNS is also demonstrated as a novel controlled guest release system, in which release kinetics are adjustable by the nanosheet thickness, pH values of the media, and the presence of protecting layers. Theoretical simulations, including Korsmeyer–Peppas model and Finite‐element analysis, are also employed to discern the observed guest‐release mechanisms.

Cao, Peng‐Fei↗
DOE OSTI2023

Integrated Micro‐Scale Concentrating Photovoltaics: A Scalable Path Toward High‐Efficiency, Low‐Cost Solar Power

The global energy market is seeing increases in the electricity demand of a couple of percentage points annually. The photovoltaic (PV) industry is also growing rapidly every year. One of the PV technologies is concentrator photovoltaics (CPV). CPV uses high‐efficiency multijunction solar cells and optics to concentrate sunlight, thereby significantly reducing the amount of semiconductor material needed. Yet, due to the high upfont manufacturing cost of CPV, it currently does not offer a competitive price against silicon PV. With this a new branch is introduced to the industry, micro‐CPV, which can be broadly explained as the miniaturization of the solar cells and optical components. The motivation for micro‐CPV is lowering the cost by decreasing the material volume and enabling new system architectures and high‐throughput manufacturing methods, while still maintaining high electrical efficiencies, taking advantage of a lower thermal load, shorter optical paths, lower resistive losses, and lower material volumes. Herein, a comprehensive review of the technological advances is presented, key synergies between micro‐CPV and other industries sharing similar challenges are identified, exemplified by micro‐light emitting diodes display manufacturing. New assembly process development in these industries will facilitate commercial adoption of micro‐CPV with continued miniaturization while driving down the cost.

Jost, Norman↗
DOE OSTI2021

Scalable statistical inference of photometric redshift via data subsampling

Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for bigger problems. But full probabilistic statistical models often outperform other models in quantifying uncertainties associated with model predictions. We develop a data-driven statistical modeling framework that combines the uncertainties from an ensemble of statistical models learned on smaller subsets of data carefully chosen to account for imbalances in the input space. We demonstrate this method on a photometric redshift estimation problem in cosmology, which seeks to infer a distribution of the redshift—the stretching effect in observing the light of far-away galaxies—given multivariate color information observed for an object in the sky. Our proposed method performs balanced partitioning, graph-based data subsampling across the partitions, and training of an ensemble of Gaussian process models.

data subsampling↗