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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Strong O 2p–Fe 3d Hybridization Observed in Solution-Grown Hematite Films by Soft X-ray Spectroscopies

Photoelectrochemical (PEC) water splitting holds the potential as a direct route for solar energy conversation and storage. The performance of a PEC device is strongly influenced by the electronic properties of the photonanode surface. It has been shown that the synthesis methods can have a profound impact on the electronic properties and PEC performance of various photoelectrode materials such as hematite. Soft X-ray spectroscopic techniques, including O K-edge XAS and Fe L-edge XAS/XES, have been employed to investigate how the synthesis methods impact the electronic structure of resulting hematite materials. It is found that the hematite samples via solution regrowth methods show dramatically increased 3d-4sp band ratios in O K-edge XAS spectra and decreased relative elastic peak intensities in Fe L-edge RIXS spectra compared with samples synthesized via ALD or solution grown. The difference observed in O-K and Fe-L spectra indicated that solution regrowth strategy alters the O 2p-Fe 3d hybridization and hence the electronic structure of the hematite films, which proves to be beneficial for PEC performance of the hematite photoanode. Our findings provided new insights and potentially useful strategies for enhancing the PEC performance of photoanode materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

C 1 Chemistry on Metal Carbide Nanoparticles: Boosting the Conversion of CO 2 and CH 4

The studies described in this Perspective show that transition metal carbide (TMC) nanoparticles can be very useful for the activation of three molecules located at the heart of C 1 chemistry: H 2 , CH 4 , and CO 2 . They also can play a major role in the trapping and conversion of two major greenhouse gases. A combination of experiment and theory has shed light on the physical and chemical properties of these systems, which can be very different from those of bulk carbides. Molecular clusters of these compounds, which can be inserted inside the cages of zeolites or carbon nanotubes, have unsaturated metal and carbon atoms that frequently work in a cooperative way when dealing with hard-to-activate molecules, such as CH 4 and CO 2 . These molecular clusters can evolve into nanoparticles of small to medium size (<15 nm) that have unique carbon/metal ratios and structures not seen in the bulk metal carbides. Even when their structures are cuts from bulk lattices, the TMC nanoparticles have corner or edge atoms that are active for the cleavage and conversion of C–H and C–O bonds. In this paper, we cover experimental and theoretical studies with well-defined metal carbide nanoparticles prepared by different methods, free and supported on diverse substrates. The Perspective ends with a discussion of current challenges and potential applications.

03 NATURAL GAS↗
DOE OSTI2016

Ligand-Free Noble Metal Nanocluster Catalysts on Carbon Supports via “Soft” Nitriding

We report a robust, universal "soft" nitriding method to grow in situ ligand-free ultrasmall noble metal nanocatalysts (UNMN; e.g., Au, Pd, and Pt) onto carbon. Using low-temperature urea pretreatment at 300 °C, soft nitriding enriches nitrogen-containing species on the surface of carbon supports and enhances the affinity of noble metal precursors onto these supports. We demonstrated sub-2-nm, ligand-free UNMNs grown in situ on seven different types of nitrided carbons with no organic ligands via chemical reduction or thermolysis. Ligand-free UNMNs supported on carbon showed superior electrocatalytic activity for methanol oxidation compared to counterparts with surface capping agents or larger nanocrystals on the same carbon supports. Our method is expected to provide guidelines for the preparation of ligand-free UNMNs on a variety of supports and, additionally, to broaden their applications in energy conversion and electrochemical catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Separation Process of Plant Fibers for Textile and Composite Application: A Review of Recent Advances

Plant fiber resources have gained significant attention for value-added utilization due to their renewability, sustainability, abundance, and widely acknowledged physical properties. The efficient and pragmatic separation of plant fibers is a critical process for their efficient utilization, yet a substantial gap persists between laboratory research advancements and their commercialization. To increase the possibility of research advancements for industrial application, this review summarizes the recent advances in different extraction methodologies of plant fiber research in textile and composite fields. It systematically outlines, compares, and contrasts physical (cryogenic, supercritical carbon dioxide, ultrasonic, steam explosion and microwave heating treatment), chemical (alkali, oxidation, organic solvents and deep eutectic solvents methods), and biological (natural retting, enzymatic and microorganism approaches) methods, addressing their respective mechanisms, strengths, limitations, research progress, and future prospects. In general, traditional chemical approaches have proven significantly effective but are accompanied by high pollution. Conversely, novel chemical treatments such as deep eutectic solvents and organic solvents offer a promising blend of efficiency and environmental friendliness but require deeper studies currently. Meanwhile, physical and biological treatments, though largely eco-friendly, tend to suffer from lower separation efficiencies. The research needs and future direction are also addressed to bridge the gap between scientific advancements and their widespread industrial application.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

SnSe 2 thermal conductivity from optothermal Raman and Stokes/anti-Stokes thermometry

The optothermal Raman method is useful in determining the in-plane thermal conductivity of two-dimensional (2D) materials that are either suspended or supported on a substrate. We compare this method with the Stokes/anti-Stokes scattering thermometry method, which can play a role in both calibration of Raman peak positions as well as extraction of the local phonon temperature. This work demonstrates that the Stokes/anti-Stokes intensity ratio plays an important role in determining the in-plane thermal conductivity of 2D tin diselenide (SnSe 2 ) dry-transferred onto a polished copper (Cu) substrate. The statistically-averaged thermal conductivity of the 108 ± 24 nm-thick SnSe 2 yielded 5.4 ± 3.5 Wm −1 K −1 for the optothermal Raman method, and 2.40 ± 0.81 Wm −1 K −1 for the Stokes/anti-Stokes thermometry method, indicating that the Stokes/anti-Stokes thermometry method to calculate the thermal conductivity of a material can simultaneously increase both precision and accuracy. The uncertainty value was also lowered by a factor of 1.9 from the traditional optothermal Raman method to the Stokes/anti-Stokes thermometry method. The low in-plane thermal conductivity of 2D SnSe 2 , 1.3–2.9 times lower than bulk, is useful for applications in thermal and electrical energy conversion and thermoelectric devices.

2D materials↗
DOE OSTI2019

Large-Scale Structure of Chromatin: A Fractal Globule or a Logarithmic Fractal?

Two physical models are considered to describe the large-scale structure of chromatin in the nucleus of a biological cell in the interphase state: a fractal globule model and a logarithmic fractal model. Based on the classification of fractal objects developed by the small-angle neutron scattering (SANS) method, it is shown that the fractal globule model does not satisfy the experimental data on small-angle neutron scattering by the nuclei of biological cells. Conversely, the logarithmic fractal model well describes the experimental data on SANS and, hence, provides a good approximation to describe the large-scale structure of chromatin. The logarithmic fractal model predicts that the nuclear space is exactly half-filled with chromatin, and the second half consists of interchromatin voids filled with nucleoplasma in which various nuclear processes occur. Thus, two opposing trends are balanced in the structural organization of chromatin: an increase in the surface area of chromatin in the cell nucleus (accessibility to external agents) and a decrease in the volume occupied by chromatin (compactness of the nucleus).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Anchoring

This software provides methods and functions for training deep image classification models based on the principle of anchoring. It features a user-friendly PyTorch wrapper that facilitates the easy conversion of any model into an anchored model. The software supports various standard datasets and includes scripts for conducting evaluations. Developed with PyTorch, it is compatible with common neural network architectures used for image data. Additionally, it offers tools for computing evaluation metrics to assess model performance.

Narayanaswamy, Vivek Sivaraman↗
DOE OSTI2015

DiaMonD: An Integrated Multifaceted Approach to Mathematics at the Interfaces of Data, Models, and Decisions

For many problems in computational science and engineering, the so-called forward problem-solution of the underlying mathematical model to yield output quantities of interest, given input parameters--is difficult enough for frontier complex models, which are often characterized by coupled multiphysics and possibly stochastic behavior over a wide range of length and time scales. However, we face the need to move beyond the forward problem, to address what is often the ultimate goal of CS&E: decision-making. This requires us to tackle a spectrum of mathematical problems that subsume, and are thus even more difficult than, the forward problem. First, given experimental data, we wish to estimate unknown parameters characterizing a model of a natural or engineered system by solving an inverse problem. Second, we seek the optimal con figuration of the system (or experiments) by solving an optimal design problem. Third, the optimal operation of the system must be determined by solving an optimal control problem. And fourth, we must quantify uncertainties as they propagate through all of the preceding problems, from data to model inference to prediction and finally to optimal design and control. Optimal mathematical methods and algorithms for such end-to-end, data-to-decisions modeling and simulation of complex problems--requiring integrated solution of forward, inverse, optimization, and UQ problems for large, multiphysics, multiscale models--entails challenges of the highest order, while also presenting great opportunities for applied mathematics research. Unfortunately, research on forward, inverse, optimization, and UQ problems has all-too-often progressed in isolation. This has led to mathematical methods that perform well when considering the forward simulation in isolation, but are prohibitive or suboptimal or unstable when combined with other methods within the framework of inversion, optimization, or UQ. The reverse is also true: general-purpose methods developed within the inversion, optimization, and UQ fields often become prohibitive when applied to complex CS&E problems since they do not exploit their structure. DiaMonD is a multi-institutional DOE MMICC effort that aims to address the challenges of end-to-end, data-to-decisions modeling and simulation for complex CS&E problems in a unifi ed, systematic, and integrated fashion. Institutions involved are Colorado State, Florida State, Los Alamos, MIT, Oak Ridge, Stanford, and UT-Austin. The goals of DiaMonD are (1) to develop advanced mathematical methods and analysis for multimodel, multiphysics, multiscale model problems driven by frontier DOE applications, including those in subsurface energy and environmental flows, materials for energy storage and conversion, and ice sheet dynamics; (2) to create theory and algorithms for integrated inversion, optimization, and uncertainty quantification for these complex problems; and (3) to disseminate the philosophy of an integrated end-to-end, data-to-decisions approach to modeling and simulation of complex problems to the broader applied math and computational science communities through workshops and other outreach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

DiaMonD: An Integrated Multifaceted Approach to Mathematics at the Interfaces of Data, Models, and Decisions

DiaMonD is a multi-institutional DOE MMICC effort that aims to address the challenges of end-to-end, data-to-decisions modeling and simulation for complex computational science and engineering problems in a unified, systematic, and integrated fashion. Institutions involved are Colorado State, Florida State, Los Alamos, MIT, Oak Ridge, Stanford, and UT-Austin. The goals of DiaMonD are (1) to develop advanced mathematical methods and analysis for multimodel, multiphysics, multiscale model problems driven by frontier DOE applications, including those in subsurface energy and environmental flows, materials for energy storage and conversion, and ice sheet dynamics; (2) to create theory and algorithms for integrated inversion, optimization, and uncertainty quantification for these complex problems; and (3) to disseminate the philosophy of an integrated end-to-end, data-to-decisions approach to modeling and simulation of complex problems to the broader applied math and computational science communities through workshops and other outreach.

42 ENGINEERING↗
DOE OSTI2020

Influence of Time and Frequency Domain Wave Forcing on the Power Estimation of a Wave Energy Converter Array

Industry-specific tools for analyzing and optimizing the design of wave energy converters (WECs) and associated power systems are essential to advancing marine renewable energy. This study aims to quantify the influence of phase information on the device power output of a virtual WEC array. We run the phase-resolving wave model FUNWAVE-TVD (Total Variation Diminishing) to generate directional waves at the PacWave South site offshore from Newport, Oregon, where future WECs are expected to be installed for testing. The two broad cases presented correspond to mean wave climates during warm months (March–August) and cold months (September–February). FUNWAVE-TVD time series of sea-surface elevation are then used in WEC-Sim, a time domain numerical model, to simulate the hydrodynamic response of each device in the array and estimate their power output. For comparison, WEC-Sim is also run with wave energy spectra calculated from the FUNWAVE-TVD simulations, which do not retain phase information, and with wave spectra computed using the phase-averaged model Simulating WAves Nearshore (SWAN). The use of spectral data in WEC-Sim requires a conversion from frequency to time domain by means of random superposition of wave components, which are not necessarily consistent because of the linear assumption implicit in this method. Thus, power response is characterized by multiple realizations of the wave climates.

13 HYDRO ENERGY↗
DOE OSTI2015

Method for the electro-addressable functionalization of electrode arrays

A method for preparing an electrochemical biosensor uses bias-assisted assembly of unreactive -onium molecules on an electrode array followed by post-assembly electro-addressable conversion of the unreactive group to a chemical or biological recognition group. Electro-addressable functionalization of electrode arrays enables the multi-target electrochemical sensing of biological and chemical analytes.

42 ENGINEERING↗
DOE OSTI2016

Nanocomposite anode materials for sodium-ion batteries

The disclosure relates to an anode material for a sodium-ion battery having the general formula AO.sub.x--C or AC.sub.x--C, where A is aluminum (Al), magnesium (Mg), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), zirconium (Zr), molybdenum (Mo), tungsten (W), niobium (Nb), tantalum (Ta), silicon (Si), or any combinations thereof. The anode material also contains an electrochemically active nanoparticles within the matrix. The nanoparticle may react with sodium ion (Na.sup.+) when placed in the anode of a sodium-ion battery. In more specific embodiments, the anode material may have the general formula M.sub.ySb-M'O.sub.x--C, Sb-MO.sub.x--C, M.sub.ySn-M'C.sub.x--C, or Sn-MC.sub.x--C. The disclosure also relates to rechargeable sodium-ion batteries containing these materials and methods of making these materials.

25 ENERGY STORAGE↗
DOE OSTI2017

Electric Motor Thermal Management

Thermal management enables more efficient and cost-effective motors. This Annual Merit Review presentation describes the technical accomplishments and progress in electric motor thermal management R&D over the last year. This project supports a broad industry demand for data, analysis methods, and experimental techniques to improve and better understand motor thermal management.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Catalytic membrane reactor, methods of making the same and methods of using the same for dehydrogenation reactions

A catalytic membrane reactor and methods of operating and producing the same are provided that efficiently produces highly pure hydrogen (H2) from ammonia (NH3) as well as operates according to other chemical conversion processes. In one embodiment, a tubular ceramic support made from porous yttria-stabilized zirconia has an outer surface that is impregnated with a metal catalyst such as ruthenium and then plated with a hydrogen permeable membrane such as palladium. An inner surface of the ceramic support is impregnated with cesium to promote conversion of ammonia to hydrogen and nitrogen (N2). The resulting catalytic membrane reactor produces highly pure hydrogen at low temperatures and with less catalytic loading. Therefore, ammonia can be used to effectively transport hydrogen for use in, for example, fuel cells in a vehicle.

Way, James Douglas↗
DOE OSTI2024

Solar Photovoltaic and Storage Supply Chains and Technology and Market Opportunities

This talk will highlight the most recent efforts from the National Renewable Energy Laboratory (NREL) to track solar photovoltaic (PV) and storage supply and demand in the United States and globally, as well as bottom-up calculations of manufacturing costs for facilities across the globe. We will begin with an overview of the global solar PV supply chain and 2022 benchmark input data used for NREL's bottom-up crystalline silicon (c-Si) and thin film PV module manufacturing cost models. For the polysilicon, wafer, cell conversion, and module assembly steps of the c-Si supply chain, and for thin film modules, we will review the industry-collected input data and methods used for calculating the costs of goods sold (COGS); research and development (R&D) expenses; and sales, general, and business administration (S, G, and A) expenses. This 2022 benchmark analysis is compiled for state-of-the-art c-Si and thin film PV module manufacturing in several countries and regions; and will also include a quantified summary of the impacts of the manufacturing incentives and tax credits that are available for solar manufacturing and installations within the United States. Next generation technologies that lower PV manufacturing and installation costs, reduce operations and maintenance (O&M) expenses, and improve system energy yield will also be highlighted. We will conclude with projections of solar market penetration to 2050 from NREL's Solar Futures Study and Annual Technology Baseline (ATB) model, which includes solar coupled with lower-cost storage scenarios as well as the range of future cost scenarios for other power generation sources. We look forward to sharing NREL's extensive work in these areas and discussing ideas for future directions.

economics↗
DOE OSTI2017

On-the-Fly Generation of Differential Resonance Scattering Probability Distribution Functions for Monte Carlo Codes

Current Monte Carlo codes use one of three models: (1) the asymptotic scattering model, (2) the free gas scattering model, or (3) the S(α,β) model, depending on the neutron energy and the specific Monte Carlo code. This thesis addresses the consequences of using the free gas scattering model, which assumes that the neutron interacts with atoms in thermal motion in a monatomic gas in thermal equilibrium at material temperature, T. Most importantly, the free gas model assumes the scattering cross section is constant over the neutron energy range, which is usually a good approximation for light nuclei, but not for heavy nuclei where the scattering cross section may have several resonances in the epithermal region. Several researchers in the field have shown that the exact resonance scattering model is temperaturedependent, and neglecting the resonances in the lower epithermal range can under-predict resonance absorption due to the upscattering phenomenon mentioned above, leading to an over-prediction of keff by several hundred pcm. Existing methods to address this issue involve changing the neutron weights or implementing an extra rejection scheme in the free gas sampling scheme, and these all involve performing the collision analysis in the center-of-mass frame, followed by a conversion back to the laboratory frame to continue the random walk of the neutron. The goal of this paper was to develop a sampling methodology that (1) accounted for the energydependent scattering cross sections in the collision analysis and (2) was performed in the laboratory frame,avoiding the conversion to the center-of-mass frame. The energy dependence of the scattering cross section was modeled with even-ordered polynomials (2nd and 4th order) to approximate the scattering cross section in Blackshaw’s equations for the moments of the differential scattering PDFs. These moments were used to sample the outgoing neutron speed and angle in the laboratory frame on-the-fly during the random walk of the neutron. Results for criticality studies on fuel pin and fuel assembly calculations using methods developed in this dissertation showed very close comparison to results using the reference Dopplerbroadened rejection correction (DBRC) scheme.

42 ENGINEERING↗
DOE OSTI2020

Low Energy Implantation into Transition-Metal Dichalcogenide Monolayers to Form Janus Structures

Atomically-thin two-dimensional (2D) materials face significant energy barriers for synthesis and processing into functional metastable phases such as Janus structures. Here, in this study, the controllable implantation of hyperthermal species from pulsed laser deposition (PLD) plasmas is introduced as a top-down method to compositionally engineer 2D monolayers. The kinetic energies of Se clusters impinging on suspended monolayer WS 2 crystals were controlled in the <10 eV/atom range with in situ plasma diagnostics to determine the thresholds for selective top layer replacement of sulfur by selenium for the formation of high quality WSSe Janus monolayers at low (300 °C) temperatures, and bottom layer replacement for complete conversion to WSe 2 . Atomic-resolution electron microscopy and spectroscopy in tilted geometry confirm the WSSe Janus monolayer. Molecular dynamics simulations reveal that Se clusters implant to form disordered metastable alloy regions, which then recrystallize to form highly ordered structures, opening the door for low-energy implantation by PLD as a novel method to explore the synthesis of 2D Janus layers and alloys of variable composition.

2D materials↗
DOE OSTI2018

Pristine or Highly Defective? Understanding the Role of Graphene Structure for Stable Lithium Metal Plating

The role of graphene host structure/chemistry in plating–stripping in lithium metal anodes employed for lithium metal batteries is first examined in this study. Structural and chemical defects are bad, since highly defective graphene promotes unstable solid electrolyte interphase (SEI) growth. This consumes the fluoroethylene carbonate (FEC) additive in the carbonate electrolyte and is correlated with rapid decay in Coulombic efficiency (CE) and formation of filament-like Li dendrites. A unique flow-aided sonication exfoliation method is employed to synthesize “defect-free” graphene (df-G), allowing for a direct performance comparison with conventional reduced graphene oxide (r-GO). At cycle 1, the r-GO is better electrochemically wetted by Li than df-G, indicating that initially it is more lithiophilic. With cycling, the nucleation overpotential with r-GO becomes higher than with df-G, indicating less facile plating reactions. The df-G yields state-of-the-art electrochemical performance, with the post cycled metal surface being relatively smooth and dendrite-free. Conversely, r-GO templates have CE rapidly degrade from the onset, with extensive dendrites after cycling. Severe SEI growth and associated FEC depletion with r-GO are further confirmed by electrochemical impedance analysis and surface science methods. Finally, a new design rule is provided for Li metal templates: An ideal host must be noncatalytic toward SEI formation.

36 MATERIALS SCIENCE↗