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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Applications of Automation Methods for Nonlinear Fracture Test Analysis

Using automated and standardized computer tools to calculate the pertinent test result values has several advantages such as: 1. allowing high-fidelity solutions to complex nonlinear phenomena that would be impractical to express in written equation form, 2. eliminating errors associated with the interpretation and programing of analysis procedures from the text of test standards, 3. lessening the need for expertise in the areas of solid mechanics, fracture mechanics, numerical methods, and/or finite element modeling, to achieve sound results, 4. and providing one computer tool and/or one set of solutions for all users for a more "standardized" answer. In summary, this approach allows a non-expert with rudimentary training to get the best practical solution based on the latest understanding with minimum difficulty.Other existing ASTM standards that cover complicated phenomena use standard computer programs: 1. ASTM C1340/C1340M-10- Standard Practice for Estimation of Heat Gain or Loss Through Ceilings Under Attics Containing Radiant Barriers by Use of a Computer Program 2. ASTM F 2815 - Standard Practice for Chemical Permeation through Protective Clothing Materials: Testing Data Analysis by Use of a Computer Program 3. ASTM E2807 - Standard Specification for 3D Imaging Data Exchange, Version 1.0 The verification, validation, and round-robin processes required of a computer tool closely parallel the methods that are used to ensure the solution validity for equations included in test standard. The use of automated analysis tools allows the creation and practical implementation of advanced fracture mechanics test standards that capture the physics of a nonlinear fracture mechanics problem without adding undue burden or expense to the user. The presented approach forms a bridge between the equation-based fracture testing standards of today and the next generation of standards solving complex problems through analysis automation.

Allen, Phillip A.↗
DOE OSTI2020

Evolution of lithium ordering with (de)-lithiation in β-LiVOPO 4 : insights through solid-state NMR and first principles DFT calculations

The lithium-ion battery cathode material β-VOPO 4 is capable of intercalating more than one Li ion per transition metal ion due to the accessibility of both the V 5+ /V 4+ and V 4+ /V 3+ redox couples at ~4.5 V and ~2.3 V vs. Li, respectively, giving a theoretical capacity greater than ~300 mA h g -1 . The ability to perform full and reversible two Li-ion intercalation in this material, however, has been a matter of debate and the poor crystallinity of the fully lithiated phase has thus far precluded its complete structural characterisation by conventional diffraction-based methods. In this work, 7 Li and 31 P NMR spectroscopy, in combination with first principles DFT calculations, indicate that chemical lithiation results in a single phase β-Li 2 VOPO 4 exhibiting a complex Li ordering scheme with lithium ions occupying multiple disordered environments. 2D NMR 7 Li correlation experiments were used to deduce the most likely Li ordering for the β-Li 2 VOPO 4 phase from amongst several DFT optimised structures. In contrast, electrochemically lithiated β-Li 2- x VOPO 4 discharged to 1.6 V exhibits, in addition to β-Li 2 VOPO 4 , a β-Li 1.5 VOPO 4 phase. Additionally, the existence of β-Li 1.5 VOPO 4 is not reflected in the flat galvanostatic charge and discharge curves nor is evident from diffraction-based methods due to the very close structural similarity between the β-Li 1.5 VOPO 4 phase and β-Li 2 VOPO 4 phases. We demonstrate that solid state NMR spectroscopy, in combination with DFT results, provides a powerful tool for identifying intermediate states formed during charge/discharge of these complex phosphates as these phases can be distinguished from the end member phases primarily by the nature of the lithium ordering.

25 ENERGY STORAGE↗
DOE OSTI2023

Photoelectrochemical materials for solar energy conversion

Research and development on semiconductors for applications in solar energy conversion has witnessed rapid growth over the past several decades. With the aim of producing chemical fuels from sunlight, intense research efforts have focused on the discovery of semiconductors with crystalline structures and chemical compositions that have the potential to satisfy the complex set of required photoelectrochemical properties. This chapter focuses on the foundational structure-property relationships of selected oxide and nitride semiconductors relevant to their uses as n-/p-type photoelectrodes and as photocatalysts. Their solid-state structures and compositions are described, with a special emphasis on strategies proven effective at targeting suitable band gaps with strong visible-light absorption, efficient charge separation and diffusion of charge carriers, and optimal band edge energies for driving surface redox reactions for water splitting.

O’Donnell, Shaun↗
DOE OSTI2023

Experimental validation of model predictive control for solid oxide fuel cells

Here, this paper presents implementation of a model predictive controller (MPC) for an experimental solid oxide fuel cell (SOFC) system. The MPC controller is based on a gain-scheduled predictor with block-oriented structure that can capture important non-linear effects while still keeping the computational complexity low enough to meet real time control requirements. Experimental results show the MPC is able to regulate the SOFC cathode outlet temperature in the face of startup transients and input perturbations.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Structure-guided utilization of lignocellulose for catalysis, energy, and biomaterials

As a complex composite of cellulose, hemicellulose, and lignin, plant lignocellulose has long served as a major resource for biomass conversion, materials engineering, and bio-based product development. High-resolution structural insights enabled by solid-state nuclear magnetic resonance (ssNMR) now allow the mapping of polymer interfaces, identification of functional group accessibility, and tracking of molecular organization during processing, all of which are critical factors for optimizing catalytic strategies. These insights could drive transformative progress in lignocellulose-based applications, including selective depolymerization, improved pretreatment design, and efficient upcycling of lignin into resins, plastics, and biomedical materials. In industry-relevant contexts, such as biofuel generation and renewable material manufacturing, understanding the hydration dynamics, cross-linking patterns, and structural heterogeneity is also essential. The ability to visualize these features in native biomass presents a unique opportunity to develop new strategies for sustainability and performance. As the structural toolbox continues to expand, it is becoming a central enabler for innovations in renewable energy, green chemistry, and advanced bioproducts.

bioproduct↗
DOE OSTI2025

d -Electron Heavy Fermion Behavior in a Near-Room-Temperature Polar Metallic Ferrimagnet: A Case of Mn 5 SiC

Polycrystalline Mn 5 SiC was synthesized by using a high-temperature solid-state method. Mn 5 SiC adopts a polar space group (Cmc2 1 ) with six crystallographic Mn sites confirmed by X-ray and neutron diffraction, transmission electron microscopy, and second harmonic generation experiments. The complex crystal structure features edge-sharing trigonal prisms and icosahedra, as well as face/edge-sharing pentagonal prisms. Magnetic measurements indicate ferrimagnetic ordering with a transition temperature of 284 K. The ferrimagnetic structure (magnetic space group Cm’c’2 1 ) was further identified by powder neutron diffraction, where collinear Mn spins align along the crystallographic c-axis. The refined magnetic moment for each crystallographic Mn site at 4 K is 1.8(2), −2.42(9), −1.72(8), 0.51(6), 0.50(4), and 1.7(2) μ B . Density functional theory calculations confirm both the metallic behavior and the ferrimagnetic structure observed experimentally and further provide insight into the observed Mn moment dependence across crystallographic sites. The resistivity and specific heat measurements and density functional theory calculations reveal a substantially large Kadowaki–Woods ratio of 5 × 10 –5 μΩ·cm/(mJ/mol) 2 and a many-body renormalization factor of 5.5, indicating the unusual heavy Fermion behavior in such an itinerant magnetic metal.

Messegee, Zachary T. [George Mason University, Fai↗
DOE OSTI2021

Influences on Subsurface Plutonium and Americium Migration

Plutonium (Pu) has been released to the environment worldwide, including approximately 1.85 × 1015 Bq (200 kg) of Pu from process waste solutions to unconfined soil structures at the Hanford Site in Washington State. The subsurface mobility of Pu is influenced by complex interactions with sediments, groundwater, and any co-contaminants within the waste stream. Previous investigations at Hanford have shown that Pu exists as discrete PuO 2 particles forming before or after disposal, as secondary solid phases formed from waste interactions with sediments as adsorbed/incorporated species, and/or as dissolved species. In this research, new evidence is presented for the existence of PuO 2 , PuO 2 -Bi 2 O 3 composites, and particles from burnt Pu metal in near-surface sediments where Pu-laden acidic process waste was disposed to sediments. Pu and americium (Am) L3 X-ray absorption spectroscopy and density functional theory suggest that, in larger, more crystalline PuO 2 particles, Am formed from radioactive decay is retained in the Pu IV O 2 structure as Am IV . The Pu and Am that were disposed of in an acidic waste stream have since migrated deeper into the subsurface with detection to at least 37 meters below ground surface. In contrast, Pu deposited near the ground surface from neutral pH waste is found to be homogeneously distributed and relatively immobile. Groundwater extractions performed on contaminated sediments indicate that both Pu and Am are recalcitrant, with Am being fractionally less extractable than Pu on a molar basis. These results suggest that the more mobile fraction of Am has migrated from the near-surface and may be present in the deeper sediments as a different phase than Pu. From these results, it is suggested that Pu and Am deposited from acidic wastes were initially mobile and became significantly less mobile as wastes were neutralized within the soil profile.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Volumetric additive manufacturing of silica glass with microscale computed axial lithography

Glass is increasingly desired as a material for manufacturing complex microscopic geometries, from the micro-optics in compact consumer products to microfluidic systems for chemical synthesis and biological analyses. As the size, geometric, surface roughness, and mechanical strength requirements of glass evolve, conventional processing methods are challenged. We introduce microscale computed axial lithography (micro-CAL) of fused silica components, by tomographically illuminating a photopolymer-silica nanocomposite that is then sintered. We fabricated three-dimensional microfluidics with internal diameters of 150 micrometers, free-form micro-optical elements with a surface roughness of 6 nanometers, and complex high-strength trusses and lattice structures with minimum feature sizes of 50 micrometers. As a high-speed, layer-free digital light manufacturing process, micro-CAL can process nanocomposites with high solids content and high geometric freedom, enabling new device structures and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Techno-economic assessment for the production of algal fuels and value-added products: opportunities for high-protein microalgae conversion

Abstract Background Microalgae possess numerous advantages for use as a feedstock in producing renewable fuels and products, with techno-economic analysis (TEA) frequently used to highlight the economic potential and technical challenges of utilizing this biomass in a biorefinery context. However, many historical TEA studies have focused on the conversion of biomass with elevated levels of carbohydrates and lipids and lower levels of protein, incurring substantial burdens on the ability to achieve high cultivation productivity rates relative to nutrient-replete, high-protein biomass. Given a strong dependence of algal biomass production costs on cultivation productivity, further TEA assessment is needed to understand the economic potential for utilizing potentially lower-cost but lower-quality, high-protein microalgae for biorefinery conversion. Results In this work, we conduct rigorous TEA modeling to assess the economic viability of two conceptual technology pathways for processing proteinaceous algae into a suite of fuels and products. One approach, termed mild oxidative treatment and upgrading (MOTU), makes use of a series of thermo-catalytic operations to upgrade solubilized proteins and carbohydrates to hydrocarbon fuels, while another alternative focuses on the biological conversion of those substrates to oxygenated fuels in the form of mixed alcohols (MA). Both pathways rely on the production of polyurethanes from unsaturated fatty acids and valorization of unconverted solids for use as a material for synthesizing bioplastics. The assessment found similar, albeit slightly higher fuel yields and lower costs for the MA pathway, translating to a residual solids selling price of $899/ton for MA versus $1033/ton for MOTU as would be required to support a $2.50/gallon gasoline equivalent (GGE) fuel selling price. A variation of the MA pathway including subsequent upgrading of the mixed alcohols to hydrocarbon fuels (MAU) reflected a required solids selling price of $975/ton. Conclusion The slight advantages observed for the MA pathway are partially attributed to a boundary that stops at oxygenated fuels versus fungible drop-in hydrocarbon fuels through a more complex MOTU configuration, with more comparable results obtained for the MAU scenario. In either case, it was shown that an integrated algal biorefinery can be economical through optimal strategies to utilize and valorize all fractions of the biomass.

09 BIOMASS FUELS↗
DOE OSTI2023

Kramers–Kronig relation in attosecond transient absorption spectroscopy

The Kramers–Kronig relation (KKR) has a wide range of applications in extreme ultraviolet (XUV) and x-ray spectroscopy. However, the validity of KKR for many of these applications has not been systematically studied, while it is known to require careful attention in nonlinear and pump–probe experiments in optical domain spectroscopy. Here, we study the validity of KKR in XUV attosecond transient absorption spectroscopy pump–probe measurements both experimentally and theoretically using argon Fano resonances as a case study. Experiments are enabled by a phase-resolved method dubbed Complex Attosecond Transient-absorption Spectroscopy (CATS). Although the estimations based on the rotating-wave approximation suggest that KKR violation could be expected in the studied case, our results validate KKR and provide a solid basis for its application in a broad range of attosecond spectroscopy experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2025

Microwave-Assisted Reforming of Tar Model Compound Using the Ni/La-CeO2 Catalyst

Gasification of solid feedstocks like coal, biomass and waste plastic produces syngas as a desired product. However, this process also produces an unwanted byproduct known as tar, which is a sticky compound consisting of a mixture of complex aromatic and polyaromatic hydrocarbons. The tar formed during the gasification process lowers the syngas yields and reduces the gasification efficiency by damaging the reactor. Therefore, it is essential to reduce the amount of tar formed during the gasification process. Catalytic reforming of tars is one way to mitigate tars. The goal of this research is to explore the possibility of microwave-assisted catalytic tar conversion to syngas. However, due to the complexity of the tar, toluene has been used as a model tar compound as it is stable and easy to handle. Ni-La/CeO2 was used as a catalyst for this study, which was synthesized by wet impregnation method. Fresh and spent catalysts were analyzed using various techniques to understand the reaction mechanism. The reaction was performed both under microwave (MW) and conventional (CV) reactor for comparison.

catalysis↗
DOE OSTI2025

Realizing the Materials-Designed-To-Environments Promise of Additive Manufacturing Through a Fundamentally Different Approach to Optimization of Nonlinear Solid Mechanics Structures

Additive Manufacturing (AM) is expected to play a large role in the labs-wide goals of accelerating innovation and leading in modern engineering. More specifically, AM is seen as a key enabling technology for increasing the agility of nuclear deterrence and other national security applications involving complex coupled environments. However, the impact of AM on these initiatives has not been as wide-ranging as hoped because – despite its unique qualities – the focus has mostly been on detailed qualification to force AM components into pre-existing performance envelopes. This paradigm fundamentally precludes the novel possibilities afforded by the geometric and material flexibility of AM. In particular, the engineering of small-scale features to undergo buckling and contact can cause large geometric and symmetry changes which provide responsiveness to different environments. Despite almost a decade of observing such behavior, there exists no way to systematically design for AM to exploit it. Our goal for this project was to connect material design to multi-environment component performance by reconceptualizing how to design for AM to exploit the buckling and contact of small-scale features.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

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

Enhanced Arsenic (III and V) Removal in Anoxic Environments by Hierarchically Structured Citrate/FeCO 3 Nanocomposites

Novel citrate/FeCO 3 nanocomposites (CF-NCs) were synthesized for effective arsenic (III and V) sorption with constant addition of Fe2+ into HCO 3 - solution in the presence of citrate. This paper is the first report on the formation of CF-NCs, and in this study we investigate the mechanisms of arsenic uptake by the sorbent under anoxic conditions through various solid- and liquid-phase spectroscopic methods, including X-ray absorption spectroscopy. In CF-NCs, citrate was found to be incorporated into the structure of siderite (up to 17.94%) through (Fe 2+ citrate) - complexes. The crystal morphology of rhombohedral siderite was changed into hierarchically nanostructured spherical aggregates composed of several sheet-like crystals, which improved the surface reactivity in the presence of sufficient citrate. Compared to pure siderite (15.2%), enhanced removal of As(III) in the range of 19.3% to 88.2% was observed, depending on the amount of incorporated citrate. The maximum sorption capacities of CF-NCs for As(III) and As(V) were 188.97 and 290.22 mg/g, respectively, which are much higher than those of previously reported siderite-based adsorbents. It was found that arsenic (III and V) sorption on CF-NCs occurred via bidentate corner-sharing surface complexation, predominantly without changes in the arsenic oxidation states. These results suggest that arsenic (III and V) can be attenuated by siderite in anoxic environments, and this attenuation can be even more effective when siderite is modified by incorporation of organic compounds such as citrate.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Study of fuel cell thermal control systems for advanced missions.

This study evaluated many heat rejection and thermal control concepts which could be applied to fuel cells for long term (600 hours) orbital and lunar surface missions. The concepts considered several types of radiators which utilized pumped gas, liquid and two phase working fluids and incorporated solid conduction fins as well as heat pipe (vapor chamber) fins. The comparison of the concepts was based on weight, area and other factors such as standby power, ability to accommodate heat load variation, control complexity, and meteoroid survival capability. A design selection matrix was established and an optimum (primary) and an alternate (secondary) heat rejection concept was chosen. Heat rejection techniques utilizing self-controlled heat pipe radiators dominate the results.

Caputo, R. S.↗
NASA NTRS1999

Study of Magnetic Damping Effect on Convection and Solidification Under G-Jitter Conditions

As shown by NASA resources dedicated to measuring residual gravity (SAMS and OARE systems), g-jitter is a critical issue affecting space experiments on solidification processing of materials. This study aims to provide, through extensive numerical simulations and ground based experiments, an assessment of the use of magnetic fields in combination with microgravity to reduce the g-jitter induced convective flows in space processing systems. We have so far completed asymptotic analyses based on the analytical solutions for g-jitter driven flow and magnetic field damping effects for a simple one-dimensional parallel plate configuration, and developed both 2-D and 3-D numerical models for g-jitter driven flows in simple solidification systems with and without presence of an applied magnetic field. Numerical models have been checked with the analytical solutions and have been applied to simulate the convective flows and mass transfer using both synthetic g-jitter functions and the g-jitter data taken from space flight. Some useful findings have been obtained from the analyses and the modeling results. Some key points may be summarized as follows: (1) the amplitude of the oscillating velocity decreases at a rate inversely proportional to the g-jitter frequency and with an increase in the applied magnetic field; (2) the induced flow approximately oscillates at the same frequency as the affecting g-jitter, but out of a phase angle; (3) the phase angle is a complicated function of geometry, applied magnetic field, temperature gradient and frequency; (4) g-jitter driven flows exhibit a complex fluid flow pattern evolving in time; (5) the damping effect is more effective for low frequency flows; and (6) the applied magnetic field helps to reduce the variation of solutal distribution along the solid-liquid interface. Work in progress includes numerical simulations and ground-based measurements. Both 2-D and 3-D numerical simulations are being continued to obtain further information on g-jitter driven flows and magnetic field effects. A physical model for ground-based measurements is completed and some measurements of the oscillating convection are being taken on the physical model. The comparison of the measurements with numerical simulations is in progress. Additional work planned in the project will also involve extending the 2-D numerical model to include the solidification phenomena with the presence of both g-jitter and magnetic fields.

Li, Ben Q.↗