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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

110th Anniversary: High-Molecular-Weight Chitin and Cellulose Hydrogels from Biomass in Ionic Liquids without Chemical Crosslinking

In this work, cellulose, chitin, and composite 3D hydrogels and membranes were fabricated without any chemical modification from high-molecular-weight chitin and cellulose-rich material (CRM) extracted from shrimp shell or pine wood, respectively, using the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([C 2 mim][OAc]). The hydrogels were prepared by redissolution of the extracted biopolymers in the same IL, or in a one-pot process directly from a solution of the biomass after extraction, followed by molding/gelation (“3D gels”) or casting (membranes), and then washing. For comparison, the preparation of gels was attempted using commercial microcrystalline cellulose or chitin. From all of the sources, the regenerated CRM or chitin required significantly lower load. Hydrogels were also converted to aerogels via transformation to alcogels and then Sc-CO 2 drying, giving materials of low density, high porosity, favorable compressibility, high water uptake, and moderate antioxidant activity. Air-dried membranes were dense, of high tensile strength, and exhibited high water-vapor transmission.

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

Concentration-Dependent Solvation Structure and Dynamics of Aqueous Sulfuric Acid Using Multinuclear NMR and DFT

Sulfuric acid is a ubiquitous compound for industrial processes and aqueous sulfate solutions also play a critical role in electrolytes for many prominent battery chemistries. While the thermodynamic literature for it is quite well-developed, comprehensive studies of the solvation structure, and particularly molecular-scale dynamical and transport properties, are less available. This study applies a multinuclear NMR approach to the elucidation of the solvation structure and dynamics over a wide temperature (-10 – 50?C) and concentration (0 – 18 M) range, combining 17O shift, linewidth, and T1 relaxation measurements, 33S shift and linewidth measurements, and 1H PFG-NMR measurements of the proton self-diffusivity. In conjunction, these results indicate a crossover between two regimes of solvation structure and dynamics, occurring above the concentration associated with the deep eutectic point (~ 4.5 M), with the high-concentration regime dominated by strong water-sulfate correlation. This description was borne out in detail by the activation energy trends with increasing concentration derived from the relaxation of both the H2O/H3O+ and H2SO4/HSO4-/SO42- 17O resonances and the 1H self-diffusivity. However, the 17O chemical shift difference between the H2O/H3O+ and H2SO4/HSO4-/SO42- resonances across the entire temperature range is nevertheless strikingly linear. A computational approach coupling MD simulations and DFT NMR shift calculations to reproduce this trend is presented, which will be the subject of further development. This combination of multinuclear, dynamical NMR and computational methods, and the results furnished by this study, will provide a platform for future studies on battery electrolytes where aqueous sulfate chemistry plays a central role in the solution structure.

Bazak, Jonathan D.↗
DOE OSTI2021

Effect of Graft Molecular Weight and Density on the Mechanical Properties of Polystyrene-Grafted Cellulose Nanocrystal Films

In this work, polymer-grafted nanoparticle (PGN) films were prepared from polystyrene (PS) grafted to rodlike cellulose nanocrystals (MxG-CNC-g-PS) with a controllable grafting density (0.03–0.25 chains/nm 2 ) and molecular weight (5–60 kg/mol). These nanorod-based PGNs are solution- and melt-processible, permitting access to one-component composite films with high nanofiller loadings (with up to 55 wt %). The impact of both grafted polymer density and molecular weight on the mechanical properties of the films was investigated and related to the polymer brush conformation: concentrated polymer brush (CPB), semidilute polymer brush (SDPB), or CPB core with SDPB corona (CPB/SDPB). The rubbery regime storage modulus (above $T_g$) showed 2 orders of magnitude increase, maximizing at a low degree of polymerization (N) and low grafting density (σ). Fracture toughness was maximized in samples with the grafted polymer in the SDPB or CPD/SDPB (higher N and relatively low σ) regime and showed enhancement relative to PS of molecular weight similar to the graft. In line with prior computation predictions, optimizing for both rubbery modulus and fracture toughness in such nanorod-based PGN films requires the polymers in the SDPB regime and CNC loading levels (ca. 50–60 wt %) that are difficult to attain in more traditional two-component CNC composites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A universal co-solvent dilution strategy enables facile and cost-effective fabrication of perovskite photovoltaics

Cost management and toxic waste generation are two key issues that must be addressed before the commercialization of perovskite optoelectronic devices. We report a groundbreaking strategy for eco-friendly and cost-effective fabrication of highly efficient perovskite solar cells. This strategy involves the usage of a high volatility co-solvent, which dilutes perovskite precursors to a lower concentration (<0.5 M) while retaining similar film quality and device performance as a high concentration (>1.4 M) solution. More than 70% of toxic waste and material cost can be reduced. Mechanistic insights reveal ultra-rapid evaporation of the co-solvent together with beneficial alteration of the precursor colloidal chemistry upon dilution with co-solvent, which in-situ studies and theoretical simulations confirm. The co-solvent tuned precursor colloidal properties also contribute to the enhancement of the stability of precursor solution, which extends its processing window thus minimizing the waste. This strategy is universally successful across different perovskite compositions, and scales from small devices to large-scale modules using industrial spin-coating, potentially easing the lab-to-fab translation of perovskite technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tunable angle-dependent electrochemistry at twisted bilayer graphene with moiré flat bands

Tailoring electron transfer dynamics across solid–liquid interfaces is fundamental to the interconversion of electrical and chemical energy. Stacking atomically thin layers with a small azimuthal misorientation to produce moiré superlattices enables the controlled engineering of electronic band structures and the formation of extremely flat electronic bands. Here, we report a strong twist-angle dependence of heterogeneous charge transfer kinetics at twisted bilayer graphene electrodes with the greatest enhancement observed near the ‘magic angle’ (~1.1°). Furthermore, this effect is driven by the angle-dependent tuning of moiré-derived flat bands that modulate electron transfer processes with the solution-phase redox couple. Combined experimental and computational analysis reveals that the variation in electrochemical activity with moiré angle is controlled by a structural relaxation of the moiré superlattice at twist angles of <2°, and ‘topological defect’ AA stacking regions, where flat bands are localized, produce a large anomalous local electrochemical enhancement that cannot be accounted for by the elevated local density of states alone.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding hydrogen electrocatalysis by probing the hydrogen-bond network of water at the electrified Pt–solution interface

Rational construction of the electrode–solution interface where electrochemical processes occur is of paramount importance in electrochemistry. Efforts to gain better control and understanding of the interface have been hindered by lack of probing methods. Here, in this study, we show that the hydrogen evolution and oxidation reactions (HER/HOR) catalysed by platinum in base can be promoted by introduction of N-methylimidazoles at the platinum–water interface. In situ spectroscopic characterization together with simulations indicate that the N-methylimidazoles facilitate diffusion of hydroxides across the interface by holding the second layer of water close to platinum surfaces, thereby promoting the HER/HOR. We thus propose that the HER/HOR kinetics of platinum in acid and base is governed by diffusion of protons and hydroxides, respectively, through the hydrogen-bond network of interfacial water by the Grotthuss mechanism. Moreover, we demonstrate a 40% performance improvement of an anion exchange membrane electrolyser by adding 1,2-dimethylimidazole into the alkali fed into its platinum cathode.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks

We employ and adapt the image-to-image translation concept based on conditional generative adversarial networks (cGAN) for learning a forward and an inverse solution operator of partial differential equations (PDEs). We focus on steady-state solutions of coupled hydromechanical processes in heterogeneous porous media and present the parameterization of the spatially heterogeneous coefficients, which is exceedingly difficult using standard reduced-order modeling techniques. We show that our framework provides a speed-up of at least 2,000 times compared to a finite-element solver and achieves a relative root-mean-square error (r.m.s.e.) of less than 2% for forward modeling. For inverse modeling, the framework estimates the heterogeneous coefficients, given an input of pressure and/or displacement fields, with a relative r.m.s.e. of less than 7%, even for cases where the input data are incomplete and contaminated by noise. The framework also provides a speed-up of 120,000 times compared to a Gaussian prior-based inverse modeling approach while also delivering more accurate results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Improving the astrometric solution of the Hyper Suprime-Cam with anisotropic Gaussian processes

Context. We study astrometric residuals from a simultaneous fit of Hyper Suprime-Cam images. Aims. We aim to characterize these residuals and study the extent to which they are dominated by atmospheric contributions for bright sources. Methods. We used Gaussian process interpolation with a correlation function (kernel) measured from the data to smooth and correct the observed astrometric residual field. Results. We find that a Gaussian process interpolation with a von Kármán kernel allows us to reduce the covariances of astrometric residuals for nearby sources by about one order of magnitude, from 30 mas 2 to 3 mas 2 at angular scales of ~1 arcmin. This also allows us to halve the rms residuals. Those reductions using Gaussian process interpolation are similar to recent result published with the Dark Energy Survey dataset. We are then able to detect the small static astrometric residuals due to the Hyper Suprime-Cam sensors effects. We discuss how the Gaussian process interpolation of astrometric residuals impacts galaxy shape measurements, particularly in the context of cosmic shear analyses at the Rubin Observatory Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Carbon nanotube thermoelectric devices by direct printing: Toward wearable energy converters

Thermoelectric devices convert thermal energy to electrical energy and are particularly well-suited for energy harvesting from waste heat. Even as the number of electronic devices used in daily life proliferates, technical advances diminish the average power such devices require to perform a given function. Here, localized thermal gradients that abound in our living environments, despite having modest energy densities, are therefore becoming increasingly viable and attractive to power such devices. With this motivation, we report the design, fabrication, and characterization of single-wall carbon nanotube thermoelectric devices (CNT-TDs) on flexible polyimide substrates as a basis for wearable energy converters. Our aqueous-solution-based film fabrication process could enable readily scalable, low-cost TDs; here, we demonstrate CNT-hydroxypropyl cellulose (HPC) composite thermoelectric films by aerosol jet printing. The electrical conductivity of the composite films is controlled through the number of CNT/HPC layers printed in combination with control of the annealing conditions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Flexible machine-learning interatomic potential for simulating structural disordering behavior of Li 7 La 3 Zr 2 O 12 solid electrolytes

Batteries based on solid-state electrolytes, including Li 7 La 3 Zr 2 O 12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. Here these examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.

25 ENERGY STORAGE↗
DOE OSTI2021

Cardinal: A Lower-Length-Scale Multiphysics Simulator for Pebble-Bed Reactors

This paper demonstrates a multiphysics solver for pebble-bed reactors, in particular, for Berkeley’s pebble-bed -fluoride-salt-cooled high-temperature reactor (PB-FHR) (Mark I design). The FHR is a class of advanced nuclear reactors that combines the robust coated particle fuel form from high-temperature gas-cooled reactors, the direct reactor auxiliary cooling system passive decay removal of liquid-metal fast reactors, and the transparent, high-volumetric heat capacitance liquid-fluoride salt working fluids (e.g., FLiBe) from molten salt reactors. This fuel and coolant combination enables FHRs to operate in a high-temperature, low-pressure design space that has beneficial safety and economic implications. The PB-FHR relies on a pebble-bed approach, and pebble-bed reactors are, in a sense, the poster child for multiscale analysis. Relying heavily on the MultiApp capability of the Multiphysics Object-Oriented Simulation Environment (MOOSE), we have developed Cardinal, a new platform for lower-length-scale simulation of pebble-bed cores. The lower-length-scale simulator comprises three physics: neutronics (OpenMC), thermal fluids (Nek5000/NekRS), and fuel performance (BISON). Cardinal tightly couples all three physics and leverages advances in MOOSE, such as the MultiApp system and the concept of MOOSE-wrapped applications. Moreover, Cardinal can utilize graphics processing units for accelerating solutions. In this paper, we discuss the development of Cardinal and the verification and validation and demonstration simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Cross-Layered Cyber-Physical Power System State Estimation towards a Secure Grid Operation

In the Smart Grid paradigm, this critical infrastructure operation is increasingly exposed to cyber-threats due to the increased dependency on communication networks. An adversary can launch an attack on a power grid operation through False Data Injection into system measurements and/or through attacks on the communication network, such as flooding the communication channels with unnecessary data or intercepting messages. A cross-layered strategy that combines power grid data, communication grid monitoring and Machine Learning based processing is a promising solution for detecting cyberthreats. In this paper, an implementation of an integrated solution of a cross-layer framework is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection of anomalies in the operation of power grid. IEEE 118-bus system is built in Simulink to provide a power grid testing environment and communication network data is emulated using SimComponents. The performance of the framework is investigated under various FDI and communication attacks.

cyber security, network security, cyber-physical s↗
DOE OSTI2023

Empowering Scientific Discovery Through Computing at the Advanced Photon Source

This paper explores the challenges and solutions for managing and processing the vast amount of data generated by the Advanced Photon Source (APS), a synchrotron light source facility producing ultra-bright x-rays for diverse scientific domains. With 68 experimental beamlines covering materials research, biology, and more, the APS serves a wide user base across academia, government, and industry. The ongoing upgrade of the APS storage ring and installation of new instruments will amplify data generation and processing demands. This paper discusses the approach to address these demands through automated data processing using standardized workflows that produce faster scientific insights. The APS Data Management System coordinates various data related tasks to manage storage, data transfer, metadata cataloging, data processing, and interfaces with tools provided by Globus. Through integration with the Argonne Leadership Computing Facility (ALCF), APS users can efficiently access high-performance computing resources. Standardized workflows have led to reduced computational burdens on scientists and greater accessibility of high performance computing resources. We demonstrate how standardization and collaboration enable scientists to rapidly convert raw data into meaningful scientific results, establishing a streamlined path from data collection to analysis and ultimately to publication.

Parraga, Hannah↗
DOE OSTI2019

Topology Reconfiguration and distributed Volt Var Control (TR-dVVC) v1

Topology Reconfiguation is a simple algorithm to choose a network configuration with the least losses in a system with high penetration of renewable energy. It uses a linearized optimal power flow algorithm to identify the optimal setpoints of PV in a system, then performs an exhaustive search of switch configurations to find the loss minimizing solution, it repeats this process until convergence. At the end, the operator has a switch schedule for a 24 hour period that should minimize losses. VVC is a distributed algorithm in which PV units drive voltage at points within the network to 1 per unit through reactive power control. The VVC algorithm relies on extremum seeking control to provide the control. The software package is a simulation of VVC on a standard IEEE 34 bus three phase network.

MacDonald, Jason↗
DOE OSTI2024

The ECP ALPINE project: In situ and post hoc visualization infrastructure and analysis capabilities for exascale

A significant challenge on an exascale computer is the speed at which we compute results exceeds by many orders of magnitude the speed at which we save these results. Therefore the Exascale Computing Project (ECP) ALPINE project focuses on providing exascale-ready visualization solutions including in situ processing. In situ visualization and analysis runs as the simulation is run, on simulations results are they are generated avoiding the need to save entire simulations to storage for later analysis. The ALPINE project made post hoc visualization tools, ParaView and VisIt, exascale ready and developed in situ algorithms and infrastructures. The suite of ALPINE algorithms developed under ECP includes novel approaches to enable automated data analysis and visualization to focus on the most important aspects of the simulation. Many of the algorithms also provide data reduction benefits to meet the I/O challenges at exascale. ALPINE developed a new lightweight in situ infrastructure, Ascent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Design and Manufacturing Challenges of the SSR1 Current Leads for PIP-II

The SSR1 cryomodule contains eight 325 MHz superconducting single spoke cavities and four solenoid-based focusing lenses operating at 2 K. The focusing lens for SSR1 cryomodule, is a superconducting magnet surrounded by a helium box which will be filled with liquid helium. The magnet assembly is composed of one solenoid with operating current 70 A and 2 quadrupoles correctors with operating current 45 A. The conduction cooled current leads will be used to power magnets. The details of current leads design, fabrication and room temperature qualification will be presented. Main emphasis will be put on the design and production process challenges and possible solutions to fulfilled operation requirement under low temperature conditions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Controllable 3D Manufacturing System

Next generation Small Modular Reactor (SMR) requires new and improved techniques, instrumentations and strategies to deal with the anticipated high radiation and high temperature environment (esp. in reactors). Component manufacturing technologies will be required that take full advantage of the new 3-D printing methods employed by additive manufacturing technologies. These manufacturing methods must be capable of producing components or sub components on a limited production basis and with nuclear quality. Based on our success in developing a variety of award-winning high energy and high power ultrafast fiber lasers and our pioneered work in fs laser 3D manufacturing (US patents, 9643361 and 9770760), PolarOnyx proposes to use tunable fiber lasers to develop smart AM & SM system to make nuclear quality components for SMR. In Phase I, we have achieved critical milestones and experimentally demonstrated the most critical functions of the proposed controllable laser AM: • Developed and investigated a series of NDI sensing technologies. Combination of IR thermal image and high resolution visible camera provides a powerful tool to characterize thermal distribution and defects. • Built an in-line laser induced breakdown spectroscopy (LIBS) to real time detect compositions of powder and parts, and melting temperature of the melting pool. It proves the LIBS is a very powerful tool to precisely guide the process. • Filed a patent (Application number 16378485) for integrating IR and visible images and LIBS for intelligent AM system. • Developed control algorithm and proved it works well for overhang experiment. • Achieved high density (>99%) and excellent mechanical properties. • Succeeded in developing a working and reliable calibration method to extract true temperature distribution during AM process. • Demonstrated spatial and temporal pulse shaping methods, and impact on microstructures. • Filed one utility patent • Laid out a solid path for phase II to work on controllable 3D manufacturing system development and optimization and to make components with nuclear quality. Our proprietary fs fiber laser based AM processing offers an ultimate solution for manufacturing high temperature components with high strength for nuclear systems. The 3D AM system in conjunction with the intelligent sensing and control is energy efficient and cost effective for the growing nuclear industries. Successful development of the proposed AM technology will provide a vital tool to solve existing and potential issues. This technology will be directly applied in the 3D printing area with combined market share of $10(s) of billions. The achievement in this research will have significant and wide social, scientific, and economic impacts by providing affordable low cost intelligent AM/SM systems, laser micromachining systems, improving energy efficiency, and reducing fabrication and operational cost. Having demonstrated the proof of concept in Phase I, we will prototype the controllable AM/SM system and investigate the efficiency and qualification of fabricating various nuclear quality components in Phase II.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Developing a Roadmap for Total Nuclear Plant Transformation

Commercial nuclear power plants (NPPs) provide emission free, always-on electricity that must be part of the energy mix if U.S. industry and business are to remain competitive while enjoying the benefits of a clean environment. Most U.S. NPPs in operation today were licensed using state-of-the-art analog technology of the 1970’s. While these systems are well proven and designed with multiple redundant channels, they required extensive manual surveillance and testing procedures to demonstrate their continued functioning. All of this adds up to increasing labor costs as the only means to increase plant availability. The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program is performing a study to determine how an NPP can fully modernize, improve safety, and improve efficiency enough to make nuclear power competitive with current and future market conditions. The study is a process improvement analysis whereby current operational processes are evaluated to identify where efficiencies and cost-savings can be realized. This report will describe a process that will provide each utility with the tools to evaluate their present state, set goals for where they want to be regarding Operation and Maintenance (O&M) costs, while offering transformative pathways to achieve these improvements. The transformative changes will be divided into 1) work process improvements, 2) technology solutions, and 3) regulatory reform. By applying these pathways in combination, NPPs can achieve the dramatic O&M savings needed to sustain safe and economic operation into the future.

99 GENERAL AND MISCELLANEOUS↗