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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 OSTI2015

Novel pathways for fuels and lubricants from biomass optimized using life-cycle greenhouse gas assessment

Decarbonizing the transportation sector is critical to achieving global climate change mitigation. Although biofuels will play an important role in conventional gasoline and diesel applications, bioderived solutions are particularly important in jet fuels and lubricants, for which no other viable renewable alternatives exist. Producing compounds for jet fuel and lubricant base oil applications often requires upgrading fermentation products, such as alcohols and ketones, to reach the appropriate molecular-weight range. Ketones possess both electrophilic and nucleophilic functionality, which allows them to be used as building blocks similar to alkenes and aromatics in a petroleum refining complex. Here, we develop a method for selectively upgrading biomass-derived alkyl methyl ketones with >95% yields into trimer condensates, which can then be hydrodeoxygenated in near-quantitative yields to give a new class of cycloalkane compounds. The basic chemistry developed here can be tailored for aviation fuels as well as lubricants by changing the production strategy. We demonstrate that a sugarcane biorefinery could use natural synergies between various routes to produce a mixture of lubricant base oils and jet fuels that achieve net life-cycle greenhouse gas savings of up to 80%.

09 BIOMASS FUELS↗
DOE OSTI2020

Efficient Control of Atom Arrangement in Ternary Metal Chalcogenide Nanoparticles Using Precursor Oxidation State

Controlling both the concentration and the distribution of elements in a given material is often crucial to extracting and optimizing synergistic properties of the various constituents. An interesting class of such multielement materials is metal chalcogenide nanoparticles, which exhibit a wide range of composition-dependent optoelectronic properties including both bandgap-mediated processes and localized surface plasmon resonance properties, each of which is useful in applications ranging from energy conversion to sensing. Because metal chalcogenide nanoparticles can support several different metal elements in a variety of chalcogen lattices, this material class has particularly benefited from the ability to control both atom concentration and atom arrangement to tailor final particle properties. The primary method to access complex, multimetallic chalcogenide particles is via a postsynthetic cation exchange strategy. One-pot syntheses have been less explored to access these complex particles, although this route is desirable for economy and scalability. In this work, we compare the composition and morphology outcomes from cation exchange and one-pot preparation approaches using a Cu/Ag/Se system, which is already known to exhibit both binary and ternary metal chalcogenide phases. We show that at similar concentrations of the two metal cations, initial reaction conditions for the one-pot method yield multicomponent nanoparticles, whereas cation exchange yields homogeneous ternary metal chalcogenide structures. We then show that by tuning the precursor oxidation state for the one-pot method, this approach can be used to access homogeneous ternary metal chalcogenide particles that are similar in atom arrangement to the particles obtained using cation exchange. Taken together, our results demonstrate reliable synthetic methods that yield a variety of controlled compositions and composition morphologies in the Cu/Ag/Se system. Importantly, we demonstrate that this entire collection of architectures can all be accessed via a one-pot method simply by modifying metal precursor chemistry. The mechanistic insights gained and the resulting streamlined syntheses outlined indicate pathways to easily scaled, highly tailorable syntheses for rapid translation into downstream technologies.

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

Rapid discovery and evolution of nanosensors containing fluorogenic amino acids

Binding-activated optical sensors are powerful tools for imaging, diagnostics, and biomolecular sensing. However, biosensor discovery is slow and requires tedious steps in rational design, screening, and characterization. Here we report on a platform that streamlines biosensor discovery and unlocks directed nanosensor evolution through genetically encodable fluorogenic amino acids (FgAAs). Building on the classical knowledge-based semisynthetic approach, we engineer ~15 kDa nanosensors that recognize specific proteins, peptides, and small molecules with up to 100-fold fluorescence increases and subsecond kinetics, allowing real-time and wash-free target sensing and live-cell bioimaging. An optimized genetic code expansion chemistry with FgAAs further enables rapid (~3 h) ribosomal nanosensor discovery via the cell-free translation of hundreds of candidates in parallel and directed nanosensor evolution with improved variant-specific sensitivities (up to ~250-fold) for SARS-CoV-2 antigens. Altogether, this platform could accelerate the discovery of fluorogenic nanosensors and pave the way to modify proteins with other non-standard functionalities for diverse applications.

Biosensors↗
DOE OSTI2015

Gold-doped graphene: A highly stable and active electrocatalysts for the oxygen reduction reaction

In addressing the growing need of renewable and sustainable energy resources, hydrogen-fuel-cells stand as one of the most promising routes to transform the current energy paradigm into one that integrally fulfills environmental sustainability. Nevertheless, accomplishing this technology at a large scale demands to surpass the efficiency and enhance the cost-effectiveness of platinum-based cathodes, which catalyze the oxygen reduction reaction (ORR). In this work, our first-principles calculations show that Au atoms incorporated into graphene di-vacancies form a highly stable and cost-effective electrocatalyst that is, at the same time, as or more (dependently of the dopant concentration) active toward ORR than the best-known Pt-based electrocatalysts. We reveal that partial passivation of defected-graphene by gold atoms reduces the reactivity of C dangling bonds and increases that of Au, thus optimizing them for catalyzing the ORR and yielding a system of high thermodynamic and electrochemical stabilities. We also demonstrate that the linear relation among the binding energies of the reaction intermediates assumed in computational high-throughput material screening does not hold, at least for this non-purely transition-metal material. We expect Au-doped graphene to finally overcome the cathode-related challenge hindering the realization of hydrogen-fuel cells as the leading means of powering transportation and portable devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
NASA NTRS1978

Low cost satellite land mobile service for nationwide applications

A satellite land mobile system using mobile radios in the UHF band, and Ku-band Communications Routing Terminals (earth stations) for a nationwide connection from any mobile location to any fixed or mobile location, and from any fixed location to any mobile location is proposed. The proposed nationwide satellite land mobile service provides: telephone network quality (1 out of 100 blockage) service, complete privacy for all the users, operation similar to the telephone network, alternatives for data services up to 32 Kbps data rates, and a cost effective and practical mobile radio compatible with system sizes ranging from 10,000 to 1,000,000 users. Seven satellite alternatives (ranging from 30 ft diameter dual beam antenna to 210 ft diameter 77 beam antenna) along with mobile radios having a sensitivity figure of merit (G/T) of -15 dB/deg K are considered. Optimized mobile radio user costs are presented as a function of the number of users with the satellite and mobile radio alternatives as system parameters.

Weiss, J. A.↗
DOE OSTI2018

Tribological behavior prediction of friction materials for ultrasonic motors using Monte Carlo‐based artificial neural network

ABSTRACT In this article, the relationship of complexity, diversity, and uncertainty between components and tribological properties of friction materials based on a Monte Carlo‐based artificial neural network (MC‐ANN) model was predicted precisely. Meanwhile, the grey relational analysis was applied to figure out weight of factors, optimize formulation design, and calculate nonlinear dependency of ingredients. The accuracy of model was studied by comparing experimental and simulated values on the basis of statistical methods (root‐mean‐squared error). It was found that the model exhibited an excellent performance in predicting and fitting effect. Moreover, comprehensive analysis of weight indicated that nano‐SiO 2 and mica exerted a significant role in improving the friction stability and wear resistance. According to different contents of each ingredient, the corresponding friction coefficient and specific wear rate could be obtained by virtue of a well‐trained MC‐ANN model without experiments, which saved a lot of time and money. It can be expected that the results of this work will extend the current research and pave a route for further in‐depth studies of friction materials. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136 , 47157.

Li, Song↗
DOE OSTI2026

Comparing Synthetic Routes and Thermal Characteristics of Alternate APO Variants

Low density, high-strength, temperature-resistant foams see widespread application in the aerospace and weapons fields due to their excellent qualities as structural supports. In these demanding environments, the most common formulation is a three-phase syntactic foam containing APOCure-601, BMI, and carbon or glass microballoons. Of these, APOCure-601 and BMI form the polymer resin amino-poly(oxadiazole) bismaleimide (APO-BMI), also known as Legacy APO or S-1,2-Ethyl-APO. In manufacturing this foam, the selective laser sintering (SLS) additive manufacturing technique is quickly gaining prominence, over more traditional injection molding since SLS allows for 3D printing of materials and reduces overall cost and waste production. That said, SLS also requires a narrow window between the melt and cure temperatures for a successful print. SLS printing of APO-BMI is therefore difficult since the compound possesses a broad window between its melting and curing temperatures, and also requires several post-cure steps or complete polymerization. This work explores synthesis optimization and thermal characteristics for variant Apo-BMI structures by observing the effect that alternative heteroatoms in the APO linkages, geometries 0f the BMI groups, and bridge structure identities impart on the resultant material. Synthetic methods for these altered structures were established in batch, with some others further converted to continuous flow chemistry, a method that produces materials in a continuous stream and is highly reproducible and readily scaled. Additionally, each structural change significantly altered the melt and cure properties for each APO variant, which is advantageous for SLS manufacturing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A chemical bath deposition route to facet-controlled Ag{sub 3}PO{sub 4} thin films with improved visible light photocatalytic activity

A facile, economic, and reproducible chemical bath deposition (CBD) method is developed for the fabrication of facet-controlled Ag{sub 3}PO{sub 4} thin films with enhanced visible light photocatalytic activity. The fine-control of bath temperature, precursor, complexing agent, substrate, and solution pH is fairly crucial in preparing the facet-selective thin film of Ag{sub 3}PO{sub 4} nanocrystal. The change of precursor from silver nitrate to silver acetate makes possible the tailoring of the crystal shape of Ag{sub 3}PO{sub 4} from cube to rhombic dodecahedron and also the bandgap tuning of the deposited films. The control of [Ag{sup +}]/[phosphate] ratio enables to maximize the loading amount of Ag{sub 3}PO{sub 4} crystals per the unit area of the deposited film. All the fabricated Ag{sub 3}PO{sub 4} thin films show high photocatalytic activity for visible light-induced degradation of organic molecules, which can be optimized by tailoring the crystal shape of the deposited crystals. This CBD method is also useful in preparing the facet-controlled hybrid film of Ag{sub 3}PO{sub 4}–ZnO photocatalyst. The present study clearly demonstrates the usefulness of the present CBD method for fabricating facet-controlled thin films of metal oxosalt and its nanohybrid. - Highlights: • The crystal facet of Ag{sub 3}PO{sub 4} films can be tuned by chemical bath deposition. • The crystal shape of Ag{sub 3}PO{sub 4} is tailorable from cube to rhombic dodecahedron. • Facet-tuned Ag{sub 3}PO{sub 4} film shows enhanced visible light photocatalyst activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Prediction of grain structure after thermomechanical processing of U-10Mo alloy using sensitivity analysis and machine learning surrogate model

Abstract Hot rolling and annealing are critical intermediate steps for controlling microstructures and thickness variations when fabricating uranium alloyed with 10% molybdenum (U-10Mo), which is highly relevant to worldwide nuclear non-proliferation efforts. This work proposes a machine-learning surrogate model combined with sensitivity analysis to identify and predict U-10Mo microstructure development during thermomechanical processing. Over 200 simulations were collected using physics-based microstructure models covering a wide range of thermomechanical processing routes and initial alloy grain features. Based on the sensitivity analysis, we determined that an increase in rolling reduction percentage at each processing pass has the strongest effect in reducing the grain size. Multi-pass rolling and annealing can significantly improve recrystallization regardless of the reduction percentage. With a volume fraction below 2%, uranium carbide particles were found to have marginal effects on the average grain size and distribution. The proposed stratified stacking ensemble surrogate predicts the U-10Mo grain size with a mean square error four times smaller than a standard single deep neural network. At the same time, with a significant speedup (1000×) compared to the physics-based model, the machine learning surrogate shows good potential for U-10Mo fabrication process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Integrated Solar-Driven Device with a Front Surface Semitransparent Catalysts for Unassisted CO 2 Reduction

Monolithic integrated photovoltaic-driven electrochemical (PV-EC) artificial photosynthesis is reported for unassisted CO 2 reduction. The PV-EC structures employ triple junction photoelectrodes with a front mounted semitransparent catalyst layer as a photocathode. The catalyst layer is comprised of an array of microscale triangular metallic prisms that redirect incoming light toward open areas of the photoelectrode to reduce shadow losses. Full wave electromagnetic simulations of the prism array (PA) structure guide optimization of geometries and length scales. An integrated device is constructed with Ag catalyst prisms covering 35% of the surface area. The experimental device has close to 80% of the transmittance with a catalytic surface area equivalent 144% of the glass substrate area. Experimentally this photocathode demonstrates a direct solar-to-CO conversion efficiency of 5.9% with 50 h stability. Selective electrodeposition of Cu catalysts onto the surface of the Ag triangular prisms allows CO2 conversion to higher value products enabling demonstration of a solar-to-C 2+ product efficiency of 3.1%. This design featuring structures that have a semitransparent catalyst layer on a PV-EC cell is a general solution to light loss by shadowing for front surface mounted metal catalysts, and opens a route for the development of artificial photosynthesis based on this scalable design approach.

14 SOLAR ENERGY↗
DOE OSTI2024

Tuning austenite stability through prior microstructure control in a low-alloy Q&P steel

Quenching and partitioning (Q&P) processing is a widely accepted heat treatment methodology for creating high strength steels consisting of ferrite, martensite, and austenite, while maintaining relatively low manufacturing costs. Though the research on effects of prior microstructure is limited, an understanding of the heat treatment response of different starting microstructures is critical to processing and creating steels with complex microstructures that contain retained austenite and may afford opportunities to further optimize properties. This study investigates the influence of starting microstructure (ferrite/pearlite versus martensite) and prior levels of cold work (38 verses 58 %) on the microstructural development and mechanical properties of a 0.2 C-2.0 Mn-1.5 Si (wt.%) steel exposed to Q&P processing. Samples with a starting martensitic microstructure resulted in higher retained austenite fractions and a more homogeneous microstructure after Q&P processing compared to a starting microstructure of ferrite-pearlite. Starting martensitic microstructures also displayed higher work hardening rates and higher uniform elongations. Larger cold reductions saw accelerated dissolution kinetics and austenite formation during intercritical annealing, resulting in more similar final microstructures from the ferrite-pearlite and martensitic starting microstructures. Finally, the results presented here indicate that varying prior processing can be a route to manipulate and control austenite stability in a Q&P processed steel.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Effect of silver on the shape of palladium nanoparticles

We report a facile route to prepare palladium-silver nanoparticles at considerably low temperature. First the controlled synthesis of palladium nanoparticles was performed via reduction of sodium tetrachloropalladate (II) in ethylene glycol in the presence of PVP(polyvinylpyrrolidone) as capping agent. The reaction was carried out at three different temperatures-80°C, 100°C and 120°C for one hour. Short reaction time and low synthesis temperature adds advantage to this method over others. Formed palladium nanoparticles were nearly spherical with the average particle size of 7.5±0.5 nm, 9.5±0.5 nm and 10.5±0.5 nm at 80°C, 100°C and 120°C respectively. Secondly, the palladium-silver nanoparticles were prepared by the simultaneous reduction of palladium and silver from their respective precursors in ethylene glycol at 100°C (optimized temperature). The shape and size distribution was studied by TEM (Transmission Electron Microscopy). The role of silver in transforming the shape of palladium nanoparticles from spherical to triangular has been discussed. Spherical symmetry of palladium nanoparticles is disturbed by the interaction of silver ions on the crystal facets of palladium nanoparticles. From UV-vis spectra, the absorption maxima of palladium nanoparticles at 205 nm and absorption maxima of palladium-silver nanoparticles at 272 nm revealed the partial evidence of their formation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗
DOE OSTI2021

Investigating the Chinese postman problem on a quantum annealer

The recent availability of quantum annealers has fueled a new area of information technology where such devices are applied to address practically motivated and computationally difficult problems with hardware that exploits quantum mechanical phenomena. D-Wave annealers are promising platforms to solve these problems in the form of quadratic unconstrained binary optimization. Here we provide a formulation of the Chinese postman problem that can be used as a tool for probing the local connectivity of graphs and networks. We treat the problem classically with a tabu algorithm and simulated annealing, and using a D-Wave device. The efficiency of quantum annealing with respect to the simulated annealing has been demonstrated using the optimal time to solution metric. We systematically analyze computational parameters associated with the specific hardware. Our results clarify how the interplay between the embedding due to limited connectivity of the Chimera graph, the definition of logical qubits, and the role of spin-reversal controls the probability of reaching the expected solution

36 MATERIALS SCIENCE↗
DOE OSTI2026

Diabatization with Electrostatic Embedding for Studying Photophysics in Organic Molecular Crystals

Highly emissive organic molecular crystals find applications in several areas, such as organic electronics, solar cells, and sensors. Understanding the excited-state mechanisms underlying these applications is essential for optimizing and controlling them effectively. Exciton models coupled with nonadiabatic dynamics, particularly quantum dynamics, provide crucial insights into photochemical and photophysical processes in molecular crystals. Nevertheless, there remains a lack of general tools and automated workflows to facilitate such simulations. In this paper, we present a computational strategy to investigate the photoactivated dynamics of organic molecular crystals, bridging methodologies traditionally used for molecular systems and materials science, with a particular focus on the interplay between local excitations and charge transfer (CT) processes. We have implemented an interface between the fromage and Overdia programs, enabling the construction of vibronic Hamiltonians for molecular crystals within an excited-state ONIOM(QM:QM′) framework, incorporating long-range electrostatics through a RESP-based Ewald summation. Fragment-based diabatization provides a route to quantum dynamics simulations in weak-to-intermediate coupling regimes. The method was applied to the photophysics of dibenzo[g,p]chrysene (DBC) crystals using time-dependent DFT. The fromage/ Overdia interface was employed to compute the couplings of local excitations and CT states for 18 unique DBC dimers in the crystal and to quantify the influence of electrostatic embedding, which was found to be modest (10−20%). Simulations on π-stacked dimers reproduced the small red shift observed experimentally from solution to crystal, attributed to electronic interactions among fixed monomers rather than crystal electrostatics. Quantum dynamics simulations revealed ultrafast population transfer from bright local excitations to CT states. This approach establishes a robust framework linking molecular and solid-state excited-state dynamics, with potential applications for studying excitations, defects, and impurities in molecular crystals.

Crystals↗
DOE OSTI2015

A new method for the preparation of a Fe{sub 3}O{sub 4}/graphene hybrid material and its applications in electromagnetic wave absorption

Graphical abstract: A microwave-assisted solvothermal process was used to prepare Fe{sub 3}O{sub 4} nanoparticles/graphene hybrids, which could be applied as an electromagnetic (EM) radiation absorbent. The absorber, composed of 20 wt% Fe{sub 3}O{sub 4}/graphene–epoxy, exhibited a dual-frequency reflection characteristic covering the C and Ku bands with maximum reflection losses of less than −20 dB at thicknesses of 4 and 5 mm. - Highlights: • Fe{sub 3}O{sub 4}/graphene composites were prepared by a microwave-assisted solvothermal route. • Uniform loading of Fe{sub 3}O{sub 4} nanoparticles on graphene was obtained. • The products as-synthesized show great promise as a microwave absorption material. • Synergistic effects of Fe{sub 3}O{sub 4} and graphene caused improved absorption efficiency. • The Fe{sub 3}O{sub 4}/graphene product possessed a dual-frequency reflection characteristic. - Abstract: A rapid, simple, and inexpensive process combining a microwave-assisted technique and a solvothermal method has been developed using graphene sheets and FeCl{sub 3}·6H{sub 2}O as the reactant to prepare graphene/Fe{sub 3}O{sub 4} nanoparticle hybrids, which can be applied as an electromagnetic radiation absorbent. The experimental factors (i.e., composition ratio, microwave power, and irradiation time) on the products’ characteristics were examined. Under optimal conditions, the morphological analysis revealed that the graphene sheet was homogeneously covered with Fe{sub 3}O{sub 4} nanoparticles (∼50 nm). The electromagnetic parameters of the composites made from 20 wt% Fe{sub 3}O{sub 4}/graphene–epoxy were measured by a vector network analyzer. It was found that the 4- and 5 mm-thick composites could attain a reflection loss below −20 dB in the dual-ranges of 4–8 and 12–18 GHz.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Comparative assessment of municipal sewage sludge incineration, gasification and pyrolysis for a sustainable sludge-to-energy management in Greece

Highlights: • The high output of MSS highlights the need for alternative routes of valorization. • Evaluation of 3 sludge-to-energy valorisation methods through SWOT analysis. • Pyrolysis is an energy and material recovery process resulting to ‘zero waste’. • Identification of challenges and barriers for MSS pyrolysis in Greece was investigated. • Adopters of pyrolysis systems face the challenge of finding new product markets. - Abstract: For a sustainable municipal sewage sludge management, not only the available technology, but also other parameters, such as policy regulations and socio-economic issues should be taken in account. In this study, the current status of both European and Greek Legislation on waste management, with a special insight in municipal sewage sludge, is presented. A SWOT analysis was further developed for comparison of pyrolysis with incineration and gasification and results are presented. Pyrolysis seems to be the optimal thermochemical treatment option compared to incineration and gasification. Sewage sludge pyrolysis is favorable for energy savings, material recovery and high added materials production, providing a ‘zero waste’ solution. Finally, identification of challenges and barriers for sewage sludge pyrolysis deployment in Greece was investigated.

09 BIOMASS FUELS↗