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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Valorisation of technical lignin in rigid polyurethane foam: A critical evaluation on trends, guidelines and future perspectives

Lignin is one of the most abundant aromatic natural polymers. Produced as a by-product from the biomass refinery industries, lignin remains largely underutilised in high-value industrial applications. The incorporation of lignin in rigid polyurethane foam (RPUF) has been the focus of much research, due to its potential to replace fossil fuel-based components of RPUF. However, the overall sustainability of RPUF depends on numerous factors including processability, cost-effectiveness, and retention of performance throughout the service life. To date, the incorporation of lignin has been explored either as filler particles (through direct incorporation) or as a blendable liquid polyol introduced after chemical modifications (such as oxyalkylation, functionalisation, or depolymerisation). However, the production of lignin incorporated foam with high performance through cost-effective processing is still an ongoing challenge. Herein, this review critically appraises the progress on the effective incorporation of lignin in RPUF. Firstly, this review briefly covers the essential raw materials, formulation, important properties, and sustainability aspects of RPUF for industrial applications. Secondly, it provides insights on the key parameters of lignin of relevance to incorporation into RPUF. Thirdly, it benchmarks the reported studies on incorporation of lignin in RPUF systems by evaluating their important properties and proposes potential strategies for addressing the key challenges in the incorporation of lignin in RPUF. By bridging the gaps that exist in the literature on the utilisation of lignin in RPUF this account will serve as a resource for both beginners and professionals in the polyurethane and biorefinery industries towards the successful development of lignin incorporated RPUF for industrial applications

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modeling Framework for the Assessment of a Sustainable Hydrogen Production and Supply Chain Network in California

The cost-effective and sustainable deployment of hydrogen supply and demand networks, especially in large economic regions like California, can be challenging considering the spatial-temporal availability and variability of the different actors across the network such as production processes, distribution modes, and end-users. In this presentation, we will provide an overview and demonstration of a modeling framework used to assess the environmental, economic, and human health impacts of plausible hydrogen production and supply chain networks in California. Scenarios focus on green hydrogen production pathways using water electrolysis and biomass gasification. End-use applications included in the model are transit, medium and heavy-duty trucking, port authorities, and power and aviation companies that currently consume natural gas, diesel, and aviation fuel for their day-to-day operation. Representative locations for hydrogen production and end-use are based on recent projections of the hydrogen economy in California. All mass and energy flows, as well as estimated emissions, are based on H2A process model designs and projections of technology performance, literature review, and LBNL process, economic and life cycle modeling, and not on company data for the sake of this presentation. Human health impacts are included following methodologies developed for the University of California Irvine HyDeal project. Life cycle phases associated with hydrogen production include feedstock preparation (water and biomass), energy production and consumption (renewable, grid, and combination of renewable and grid electricity), maintenance (chemical utilization in electrolysis and natural gas combustion in gasification), carbon sequestration, hydrogen storage (compression and liquefaction), and distribution (truck and pipeline). We apply the framework utilizing California specific emission factors, financial data, and human health damages and explore the impact of network characteristics on results. Example variations include: the inclusion of policy incentives or not, different representations of the electricity grid and source, electrolysis versus gasification versus combinations of both for production, liquefaction versus compression based on producer capacity cutoffs, transportation truck versus pipeline based on existing infrastructure, and ultimate end use. Comparison of these different scenarios can help inform future projects by demonstrating the trade-offs among environmental, economic, and human health impacts. This model, automated in R, is a starting platform upon which new analysis, modeling capabilities, locations, and emission factors can be rapidly tested and integrated.

Zaki, Mohammed Tamim↗
DOE OSTI2022

In-Field Alpha Spectrometer Development FY2022 Mid-Year Report

In response to needs identified by the International Atomic Energy Agency (IAEA), Idaho National Laboratory (INL) has developed an In-Field Alpha Spectrometer (IFAS) to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF 6 ) at processing facilities, to perform field assessments to verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, developed at Pacific Northwest National Laboratory (PNNL), which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (as a dihydrate, UO 2 F 2 ·2H 2 O). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the course of this project INL, PNNL, Oak Ridge National Laboratory worked to optimize the SUDA sample design for alpha spectrometry, to optimize processes for manufacturing, loading, and shipping SUDA samples, and to allow the measurement of loaded SUDA samples. In fiscal year (FY) 2022 INL has bene investigating the reproducibility and measurement precision of IFAS measurements and the associated determination of uranium enrichment.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS1989

Optical Processing With Photorefractive Semiconductors

Experimental phase-conjugate four-wave-mixing apparatus used to demonstrate capabilities of GaAs (and potentially of other photorefractive semiconductors like InP and CdTe) for optical processing of information. With modifications, performs any of three basic image-processing functions: transfer to different light beam, enhancement of edges, and autocorrelation. Includes crystal of GaAs of 5 by 9 by 9 mm with cubic crystalline axes. Advantages include high speed and compatibilty with other semiconductor devices.

Cheng, Li-Jen↗
NASA NTRS1989

Image processing software for providing radiometric inputs to land surface climatology models

During the First International Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), 80 gigabytes of image data were generated from a variety of satellite and airborne sensors in a multidisciplinary attempt to study energy and mass exchange between the land surface and the atmosphere. To make these data readily available to researchers with a range of image data handling experience and capabilities, unique image-processing software was designed to perform a variety of nonstandard image-processing manipulations and to derive a set of standard-format image products. The nonconventional features of the software include: (1) adding new layers of geographic coordinates, and solar and viewing conditions to existing data; (2) providing image polygon extraction and calibration of data to at-sensor radiances; and, (3) generating standard-format derived image products that can be easily incorporated into radiometric or climatology models. The derived image products consist of easily handled ASCII descriptor files, byte image data files, and additional per-pixel integer data files (e.g., geographic coordinates, and sun and viewing conditions). Details of the solutions to the image-processing problems, the conventions adopted for handling a variety of satellite and aircraft image data, and the applicability of the output products to quantitative modeling are presented. They should be of general interest to future experiment and data-handling design considerations.

Newcomer, Jeffrey A.↗
DOE OSTI2021

Methods and devices for preventing computationally explosive calculations in a computer for model parameters distributed on a hierarchy of geometric simplices

A computer-implemented method of preventing computationally explosive calculations. The method includes obtaining, by a processor of the computer, measured data of one of a physical process or a physical object; performing hierarchical numerical modeling of a physical process inclusive of an Earth model containing at least one of (a) infrastructure in the ground and (b) a formation feature in the ground, wherein predicted data is generated; comparing the measured data to the predicted data to calculate an estimated error; analyzing the estimated error via an inversion process to update the at least one of the Earth model and infrastructure model so as to reduce the estimated error and to determine a final composite Earth model of at least one of the infrastructure and the feature; and using the final composite Earth model to characterize at least one of the process and the physical object.

Source record↗
NASA NTRS1988

Flight and ground packet telemetry systems activities at NASA's Goddard Space Flight Center

NASA's Goddard Space Flight Center (GSFC) has the responsibility for the telemetry ground data processing for two current spacecraft which use packet telemetry. These spacecraft are the Hubble Space Telescope (HST) and the Gamma Ray Observatory (GRO). GSFC has designed and built two ground systems to meet this responsibility. The first is the HST DATA Capture Facility (DCF), which has now completed its integration and test phase and is supporting spacecraft and data flow tests. The second is the Packet Processor System (Pacor). This system became operational in July 1987. These systems are known generally as Level Zero Processors. Level Zero Processors ingest telemetry composite bit streams, output selected user specific data in real time, and in a batch mode perform all necessary processing to produce individual user data files which are, within the limits of the quality of the received data, contiguous, complete, ordered and nonredundant.

Carper, Richard D.↗
NASA NTRS1992

Research experiences on materials science in space aboard Salyut and Mir

From 1980 through 1991 approximately 500 materials processing experiments were performed aboard the space stations Salyut 6, Salyut 7 and Mir. This includes work on catalysts, polymers, metals and alloys, optical materials, superconductors, electronic crystals, thin film semiconductors, super ionic crystals, ceramics, and protein crystals. Often the resulting materials were surprisingly superior to those prepared on earth. The Soviets were the first to fabricate a laser (CdS) from a crystal grown in space, the first to grow a heterostructure in space, the first super ionic crystal in space, the first crystals of CdTe and its alloys, the first zeolite crystals, the first protein crystals, the first chromium disilicide glass, etc. The results were used to optimize terrestrial materials processing operations in Soviet industry. The characteristics of these three space stations are reviewed, along with the advantages of a space station for materials research, and the problems encountered by the materials scientists who used them. For example, the stations and the materials processing equipment were designed without significant input from the scientific community that would be using them. It is pointed out that successful results have been achieved also by materials processing at high gravity in large centrifuges. This research is also continuing around the world, including at Clarkson University. It is recommended that experiments be conducted in centrifuges in space, in order to investigate the acceleration regime between earth's gravity and the microgravity achieved in orbiting space stations. One cannot expect to understand the influence of gravity on materials processing from only two data points, earth's gravity and microgravity. One must also understand the influence of fluctuations in acceleration on board space stations, the so-called 'g-jitter.' This paper is presented in outline and graphical form.

Regel, Liya L.↗
DOE OSTI2024

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development and Advanced Testing of DPC Cement Fillers

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The research presented here is focused Sandia’s efforts for the development of phosphate-based cement fillers. Molten metal filler research is an ongoing activity at Oak Ridge National Laboratories and is not discussed herein. After the completion of the FY20 research effort the following cement filler compositions were selected for further experimental development work and advanced testing in FY21: 1. Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with various phosphate sources; 2. Wollastonite phosphate cements (WPCs), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material bound by a calcium phosphate that serves as the binder; and 3. Calcium aluminate phosphate cements (CAPCs) specifically grossite (CaAl 4 O 7 ) and hibonite (CaAl 11 O 18 ) fillers bound by an aluminum phosphate that serves as the binder. This effort focused on the optimization and subsequent processing of these three cements to achieve dense and well-consolidated monolithic samples. Upon completion of the FY21 effort the aluminum phosphate cements (APCs) and the calcium aluminate phosphate cements (CAPCs) show the most promise for advanced testing and scale up. We will begin the work in FY22 focused on testing the performance of these two cements in small scale DPCs as well as advanced materials testing to evaluate cement performance under expected radiation doses and representative post-closure geochemical environments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1990

Project WISH: The Emerald City

The preliminary design of a permanently manned autonomous space oasis (PEMASO), including its pertinent subsystems, was performed during the 1990 Winter and Spring quarters. The purpose for the space oasis was defined and the preliminary design work was started with emphasis placed on the study of orbital mechanics, power systems and propulsion systems. A rotating torus was selected as the preliminary configuration, and overall size, mass and location of some subsystems within the station were addressed. Computer software packages were utilized to determine station transfer parameters and thus the preliminary propulsion requirements. Power and propulsion systems were researched to determine feasible configurations and many conventional schemes were ruled out. Vehicle dynamics and control, mechanical and life support systems were also studied. For each subsystem studied, the next step in the design process to be performed during the continuation of the project was also addressed.

Oz, Hayrani↗
DOE OSTI2018

Final Report: Scale-up of Algal Biofuel Production Using Waste Nutrients

Renewable fuels can be more environmentally friendly than conventional fuels and can be produced locally, supporting energy independence. Liquid renewable fuels are of special interest due to their high energy density. Algae are a promising prospective feedstock for low carbon intensity liquid biofuels, due to their high productivity and potential for high lipid or carbohydrate content. Their ability to grow on wastewater and waste nutrients and on non-arable land are cost and sustainability advantages. The organic matter content of wastewater promotes mixotrophic and/or heterotrophic growth of both algae and bacteria, boosting biomass productivity further. However, economic and technologic challenges persist that prevent the scale-up of algal biofuels to commercial relevance. These challenges include algal harvesting, drying, dewatering, and the conversion of algal biomass to usable fuels (Hannon et al 2010, Dunlap and Shaw 2009, Pienkos et al. 2009). The US Department of Energy (DOE) Bioenergy Technologies Office (BETO) supports research to overcome these challenges and outlines the research and development goals for algal biofuels in their Multi-Year Program Plan (MYPP). The long-term goals of the MYPP for algal biofuels research are briefly as follows: develop the domestic ability to produce algal biofuels at a scale of 5 billion gallons per year (BGY) by 2030 and demonstrate technologies that produce biofuel intermediates from algae at a cost of $3/gallon of gasoline equivalent (GGE) by 2022 (BETO MYPP 2016). This research reported herein was funded to investigate methods of meeting an intermediate milestone of 2,500 gallons of biofuel intermediate per acre per year for a non-integrated process by improving algal productivity, harvesting efficiency, and conversion to biofuel intermediates. Use of wastewater and wastewater nutrients was a key distinguishing characteristic of this project. In pursuit of 2,500 gallons of biofuel intermediate (BFI) per acre per year, California Polytechnic State University, San Luis Obispo (Cal Poly) sought to develop the capability to produce biofuel intermediates from microalgae grown on municipal wastewater at a 20-acre algae-based wastewater treatment facility in Delhi, California (37.43° N), which includes 7 acres of raceway ponds. Coupling algal biofuel production with wastewater treatment capitalizes on the abundant waste nutrients and carbon present in wastewater and reduces use of clean water in algal biorefinery systems. In this research, the performance of the full-scale wastewater treatment plant was characterized by measuring productivity, wastewater treatment performance, hydraulic characteristics, and energy consumption. Nine 1,000-L pilot raceways with CO2 addition were used in experiments to maximize productivity. Low-cost, energy-efficient algae bioflocculation and settling were monitored. Population genetics were monitored in an attempt to correlate taxa with superior productivity and/or settling. Algae-bacterial biomass was converted to biofuel intermediates via bench-scale hydrothermal liquefaction (HTL), and the resulting fuel quality was characterized. To develop rapid strain screening capabilities, a climate simulating photobioreactor (“LEAPS”) was developed and validated against outdoor raceways. A techno-economic analysis (TEA) and a lifecycle assessment (LCA) were performed to model process economics and sustainability. The major outcomes of this research included demonstration of 33 g/m2-day annual average algal-bacterial productivity in pilot raceways, and a biofuel intermediate yield of 0.35 g intermediate/g algae biomass via HTL, for a yield of 4,100 gallons BFI per acre per year, assuming a 90% harvest efficiency and ignoring other minor losses. This exceeded the project goal of 2,500 gallons of BFI per acre per year and nearly met the 2030 program goal, highlighting the promise of integrating wastewater treatment and biofuels production. The biocrude BFI produced by the process is refined to diesel and naphtha fuels. These fuels are normalized to the energy content of gasoline (gallons gasoline equivalent, GGE, for comparison to other fuels). Results from the TEA of the this complete “well-to-wheel” process demonstrated that, at a 400-ha scale, a minimum fuel selling price (MFSP) of $12.55/GGE, which could be decreased 57% to $7.14/GGE when including revenue from coupling the biofuel production with the co-products of wastewater treatment services and low carbon fuel credits from California and Federal programs. Due mainly to the high capital costs of thickener centrifuges and hydrothermal processing equipment, the fuel cost is sensitive to scale, with significantly lower costs expected for larger farms. In this research project, significant advances were made in improving raceway algal productivity and fuel production from algae biomass, while also improving process economics. These outcomes brought the algal biofuel technology closer to being a sustainable and marketable process. The remainder of this executive summary is organized into the following six primary project tasks: (1) to optimize biomass productivity for a selected strain at Delhi, (2) to maximize algal productivity and harvesting efficiency in Delhi pilot ponds, (3) a full-scale raceway hydraulic characterization, (4) biomass processing to biofuel intermediates, and (5) scale-up engineering analysis, modeling, and planning.

09 BIOMASS FUELS↗
DOE OSTI2024

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Fuel Cell Power Plant Initiative: Preliminary Design of a Fixed-Base LFP/SOFC Power System - Volume 2

This report documents the preliminary design for a military fixed-base power system of 3 MWe nominal capacity using Westinghouse's tubular Solid Oxide Fuel Cell [SOFC] and Haldor Topsoe's logistic fuels processor [LFP]. The LFP provides to the fuel cell a methane rich sulfur free fuel stream derived from either DF-2 diesel fuel, or JP-8 turbine fuel. Fuel cells are electrochemical devices that directly convert the chemical energy contained in fuels such as hydrogen, natural gas, or coal gas into electricity at high efficiency with no intermediate heat engine or dynamo. The SOFC is distinguished from other fuel cell types by its solid state ceramic structure and its high operating temperature, nominally 1000'C. The SOFC pioneered by Westinghouse has a tubular geometry closed at one end. A power generation stack is formed by aggregating many cells in an ordered array. The Westinghouse stack design is distinguished from other fuel cell stacks by the complete absence of high integrity seals between cell elements, cells, and between stack and manifolds. Further, the reformer for natural gas [predominantly methane] and the stack are thermally and hydraulically integrated with no requirement for process water. The technical viability of combining the tubular SOFC and a logistic fuels processor was demonstrated at 27 kWe scale in a test program sponsored by the Advanced Research Projects Agency [ARPA) and carried out at the Southern California Edison's [SCE] Highgrove generating station near San Bernardino, California in 1994/95. The LFP was a breadboard design supplied by Haldor Topsoe, Inc. under subcontract to Westinghouse. The test program was completely successful. The LFP fueled the SOFC for 766 hours on JP-8 and 1555 hours of DF-2. In addition, the fuel cell operated for 3261 hours on pipeline natural gas. Over the 5582 hours of operation, the SOFC generated 118 MVVH of electricity with no perceptible degradation in performance. The LFP processed military specification JP-8 and DF-2 removing the sulfur and reforming these liquid fuels to a methane rich gaseous fuel. Results of this program are documented in a companion report titled 'Final Report-Solid Oxide Fuel Cell/ Logistic Fuels Processor 27 kWe Power System'.

Veyo, S.E.↗
NASA NTRS2016

Development of a Fully Automated Guided Wave System for In-Process Cure Monitoring of CFRP Composite Laminates

A guided wave-based in-process cure monitoring technique for carbon fiber reinforced polymer (CFRP) composites was investigated at NASA Langley Research Center. A key cure transition point (vitrification) was identified and the degree of cure was monitored using metrics such as amplitude and time of arrival (TOA) of guided waves. Using an automated system preliminarily developed in this work, high-temperature piezoelectric transducers were utilized to interrogate a twenty-four ply unidirectional composite panel fabricated from Hexcel (Registered Trademark) IM7/8552 prepreg during cure. It was shown that the amplitude of the guided wave increased sharply around vitrification and the TOA curve possessed an inverse relationship with degree of cure. The work is a first step in demonstrating the feasibility of transitioning the technique to perform in-process cure monitoring in an autoclave, defect detection during cure, and ultimately a closed-loop process control to maximize composite part quality and consistency.

Hudson, Tyler B.↗
DOE OSTI2019

Simultaneous upgrading of biomass-derived sugars to HMF/furfural via enzymatically isomerized ketose intermediates

Abstract Background Recently, exploring fermentative or chemical pathways that convert biomass-derived sugars to fuels/chemicals has attracted a lot of interest from many researchers. We are investigating a hydrocarbon pathway from mixed sugars via 5-hydroxymethyl furfural (HMF) and furfural intermediates. To achieve this goal, we must first convert glucose and xylose to HMF and furfural in favorable yields. Current processes to produce HMF/furfural generally involve the use of acid catalysts in biphasic systems or solvents such as ionic liquids. However, the yield from transforming glucose to HMF is lower than the yield of furfural from xylose. Results In this study, we present an efficient chemical pathway simultaneously transforming glucose and xylose to HMF and furfural via ketose intermediates, i.e., fructose and xylulose, which were generated from glucose and xylose via enzymatic isomerization. In the enzymatic isomerization, by adding sodium borate to complex with the ketoses, xylose conversion reached equilibrium after 2 h with a conversion of 91% and glucose conversion reached 84% after 4 h. By enzymatically isomerizing the aldoses to ketoses, the following dehydration reactions to HMF and furfural could be performed at low process temperatures (i.e., 110–120 °C) minimizing the side reactions of the sugars and limiting the degradation of furfurals to humins and carboxylic acids. At 120 °C, pH 0.5, and 15 min reaction time, mixed ketose sugars were converted to HMF and furfural in yields of 77% and 96%, respectively (based on starting aldose concentrations). Conclusion Taken together, our results demonstrate that this combined biological and chemical process could be an effective pathway to simultaneously convert biomass-derived glucose and xylose to HMF and furfural, for use as intermediates in the production of hydrocarbons.

09 BIOMASS FUELS↗
DOE OSTI2019

Metal-Supported Solid Oxide Electrolysis Cell with Significantly Enhanced Catalysis

High-temperature electrolysis (HTE) using solid oxide electrolysis cells (SOECs) is a promising hydrogen production technology and has attracted substantial research attention over the last decade. While most studies are conducted on hydrogen electrode-supported type cells, SOEC operation using metal-supported cells has received minimal attention. The development of metal-supported SOECs with performance similar to the best conventional SOECs is reported. These cells have stainless steel supports on both sides, 10Sc1CeSZ electrolyte and electrode backbones, and nano-structured catalysts infiltrated on both hydrogen and oxygen electrode sides. Samarium-doped ceria (SDC) mixed with Ni is infiltrated as a hydrogen electrode catalyst, and the effect of ceria:Ni ratio is studied. On the oxygen electrode side, catalysts including lanthanum strontium manganite (LSM), lanthanum strontium cobalt ferrite (LSCF), praseodymium oxide (Pr 6 O 11 ), and their composite catalysts with SDC (i.e., LSM-SDC, LSCF-SDC, and Pr 6 O 11 -SDC) are compared. Utilizing the materials with highest catalytic activity (Pr 6 O 11 -SDC and SDC40-Ni60) and optimizing the catalyst infiltration processes, excellent electrolysis performance of metal-supported cells is achieved. Current densities of –5.31, –4.09, –2.64, and –1.62 A cm –2 are accomplished at 1.3 V and 50 vol% steam content at 800, 750, 700, and 650 °C, respectively.

08 HYDROGEN↗