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At least 91 records · Page 5

Coupled wave-current modeling for hydrodynamic load analysis of macroalgae cultivation farms

Large-scale cultivation of macroalgae is one of the most promising biofuel sources that could reduce our consumption of fossil fuels and would be particularly economically competitive when grown for the co-production of additional goods such as food and textiles. Current production of biofuel from algal biomass is limited by labor costs and lack of data on potential impacts of cultivation and harvesting on marine and coastal environments as well as a comprehensive characterization of the impact of environmental conditions on macroalgal feedstock and their bioproduct and biofuel yield and quality. Awarded by the United States (U.S.) Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) Macroalgae Research Inspiring Novel Energy Resources (MARINER) program, which seeks to enable the U.S. as a global leader in the production of marine biomass, the Marine Biological Laboratory (MBL) has been developing a test system for tropical seaweed cultivation in the Gulf of Mexico and the Caribbean. An integral step in designing macroalgae cultivation farms is to adequately characterize the hydrodynamic climate at potential growth sites. In regions like the Gulf of Mexico and the Caribbean, which are highly exposed to tropical cyclones, it is critical to not only consider the day-to-day hydrodynamic conditions but to also assess the risk of extreme sea states to ensure the survivability of future macroalgae farms. Under these considerations, the Pacific Northwest National Laboratory (PNNL) is providing modeling support for MBL to inform the design and siting of the farm systems that have been proposed for their ARPA-E MARINER project. This report describes the development of a high-resolution coupled storm surge and wave model to simulate the hydrodynamics and wave climate at proposed macroalgae cultivation sites selected by MBL in Florida and Puerto Rico. Model results, including model validation, water level, current distributions, and sea states, are discussed for both selected sites in Florida and Puerto Rico coast. These simulations provide an accurate insight into the hydrodynamic conditions that a macroalgae farm is likely to experience during its operational lifetime, including current information to support fine-scale hydrodynamic load modeling, risk analysis and system design.

09 BIOMASS FUELS↗

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

Particle classification by image analysis improves understanding of corn stover degradation mechanisms during deconstruction

Biomass feedstock heterogeneity is a principal roadblock to implementation of the biorefinery concept. Even within an identical cultivar of corn stover, different bales contain not only varying abundance moisture, ash, glucan, and other chemical compounds, but also varying abundance of tissue anatomies (e.g., leaf, husk, cob, or stalk). These different anatomical components not only differ in their response to pretreatment and enzymatic hydrolysis to glucose, but also vary in their mechanical and conveyance properties. Although this heterogeneous nature of corn stover feedstock has been identified as a challenge, a fundamental knowledge gap of how these tissues behave during biorefining processing remains. Here, we demonstrate the use of a commercial fiber image analyzer typically used for wood fiber characterization to monitor the particle size and shapes of non-woody feedstock during milling, pretreatment, and hydrolysis. Additionally, we present novel use of Gaussian process classification to distinguish bundle, parenchyma, and fiber particles to an accuracy of 96.4%. Quantitative probability distribution plots for characteristics such as length and roundness allow elucidation of particle morphology as pretreatment and enzymatic hydrolysis progress. In both stalk pith and stalk rind, particles peel into individual cells whose walls are subsequently fragmented during enzymatic hydrolysis.

09 BIOMASS FUELS↗

Organic matter concentration and composition of experimentally burned open air and muffle furnace vegetation chars across differing burn severity and feedstock types from Pacific Northwest, USA (v4).

This dataset represents results from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and feedstock materials. The dataset provides both solid and dissolved phase bulk concentration and organic matter characterization data from experimentally generated chars. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. This data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), fourteen burn table videos, burn table video metadata and three folders containing (A) data; (B) metadata and protocols; and (C) photos. The folder names and the file name of the data package readme include a version number which will be updated with future iterations of this data package. The data folder includes (1) solid carbon and solid nitrogen; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and total dissolved nitrogen (TN); (3) pH; (4) thermocouple time series temperature; (5) methods codes; (6) installation methods; (7) excitation emissions matrix (EEM) methods information; (8) a folder of excitation emissions matrix (EEM) fluorescence and absorbance spectra in dissolved organic matter and EEMs processing instructions; (9) solid state carbon-13 and solution state phosphorus nuclear magnetic resonance (13-C NMR and 31-P NMR) data and methods; (10) benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (11) FTICR-MS methods; (12) Inductively coupled plasma (ICP) data for total calcium, magnesium, iron, aluminum, potassium, phosphorus, sodium, and sulfur along with sodium hydroxide-ethylenediaminetetraacetic acid (sodium hydroxide-EDTA) extractable calcium, magnesium, iron, aluminum, potassium, phosphorus, and sulfur; (13) a folder of phosphorus, carbon, and nitrogen X-ray absorption near edge structure (P-XANES, N-XANES, C-XANES) data for samples and standards; (14) P-XANES, N-XANES, C-XANES methods; (15) molybdate reactive phosphorus; and (16) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains .txt data files and a subfolder containing instruments for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. The metadata and protocols folder includes (1) international geo-sample number (IGSN) mapping file (2) burn and laboratory metadata; (3) burn protocol; (4) laboratory protocol; (5) vegetation collection metadata; and (6) vegetation collection protocol. The folder contains photos of the solid chars. All files are .csv, .txt, .pdf, .jpg, .jpeg, .R, .ref, or .mp4. The data package was originally published October 2022 (v1). It was updated April 2023 (v2; new data files), September 2023 (v3; new and corrected data files), and September 2024 (v4; new and added/updated files). Metadata files were also updated to reflect these changes. See the change history section in the readme for more details.

54 ENVIRONMENTAL SCIENCES↗

The effect of varying powder feedstock chemistry and printing atmosphere on the microstructure of additively manufactured nickel-based ODS alloys: Role on stabilization of cellular structures vs. oxide dispersion formation

Nickel-based alloys have a wide variety of structural applications due to their high corrosion resistance and mechanical strength which depend on solid solution strengthening, or the formation of oxides and/or intermetallic precipitation for their properties. In this study, the microstructure of six Ni–Cr–Y–Ti–Al powder batches designed for the production of oxide dispersion strengthened nickel were compared. These batches varied in chemistry and atomization technique used which included Gas Atomization Reactive Synthesis (GARS). The batches of powder were then consolidated via Additive Manufacturing (AM) Powder Bed Fusion using Laser Beam (PBF-LB) and characterized via transmission electron microscopy to elucidate the influence of powder feedstock (i.e. synthesis methodology and chemistry) on the PBF-LB microstructure. The study investigates (i) how the amount of yttrium and titanium additions in the powder feedstock and the addition of oxygen during the processing (through GARS) affect the microstructure of the powder itself and the AM printed microstructure, and (ii) how the control of oxygen addition in the printing atmosphere during the PBF-LB printing process itself is another important parameter for achieving the formation of the wanted oxide dispersion versus the stabilization of the cellular structure (often observed in AM processed alloys). Microstructural characterization of both powder particles and additively manufactured nickel alloys in this study provide important insights into the movement of yttrium within the material upon solidification, particularly along cell boundaries, and how yttrium behaves depending on alloy chemistry. When a threshold of yttrium content is reached within the system, yttrium consistently reacts to form an intermetallic along cell boundaries instead of forming oxide nanoparticles.

36 MATERIALS SCIENCE↗

Corrosion and Chemical Characterization of Bio-Oils from Biomass with Varying Ash and Moisture Contents

As part of the Feedstock Conversion Interface Consortium four samples of pine chips (all combinations of low and high moisture and ash content) were collected and processed for fast pyrolysis. The prepared biomass samples were liquefied at the National Renewable Energy Laboratory (NREL) using the fast pyrolysis process. Following some characterization of the bio-oils at NREL, the bio-oils were shipped to Oak Ridge National Laboratory (ORNL) for corrosion testing and further characterization.The content and composition of ash in each bio-oil was determined. Corrosion testing consisted of exposing selected metallic and elastomer samples for 1000 hr at 50°C and for longer times at room temperature as well as electrochemical impedance spectroscopy measurements to assess relative corrosivity of the bio-oils. Chemical characterization was conducted to identify the corrosive component of the bio-oils as well as to define the chemical differences among the oils. It was hypothesized that there could be a catalytic effect from the higher ash content in two of the biomass sources. Results of these characterization and corrosion studies will be reported.

Keiser, Jim↗

Novel Preprocessing Techniques for Enhancing Flowability of Miscanthus

Purpose-grown energy crops possess significant potential as promising feedstocks for biofuel and biochemical production. However, similar to other biomass feedstocks, their utilization has been hindered by handling and feeding challenges such as clogging and segregation, which prevent biorefineries from operating at full capacity. These challenges arise primarily due to particle attributes including irregular shape, high flexibility, and high compressibility, leading to interlocking, high compaction, and significant friction under stress consolidation. To enhance operational reliability, it is crucial to focus on preprocessing techniques to address these issues, alongside accurately characterizing the mechanical and physical properties and flow performance of these feedstocks. This study investigates novel preprocessing techniques, including pelletization and torrefaction, to fundamentally alter these particle attributes and improve flowability. Miscanthus, an herbaceous energy crop, was the primary focus of this study. Samples were processed using a Forest Concepts Crumbler rotary shear system and an oscillating multi-stack screen bed to achieve two nominal (baseline) particle sizes: 6mm and 2mm. The study evaluated the efficiency and energy consumption of size reduction, revealing that while 2mm particles required more energy, they exhibited better flowability and higher yield strength compared to 6mm particles. Shear and compression tests assessed the material's shear strength, internal friction, and elastic modulus, while wedge-shaped hopper tests measured the critical arching distance and mass flow rate. The results provide valuable insights into the mechanical properties and processing efficiency of Miscanthus, contributing to the development of a preprocessing framework that enhances energy efficiency and material flowability in bioenergy production. However, further preprocessing and development are required to optimize this framework fully.

09 - BIOMASS FUELS↗

Advanced mass balance characterization and fractionation of algal biomass composition

Abstract Opportunities associated with biomass production and bioproduct isolation from algae-derived feedstocks are plentiful and promising; however, there are challenges associated with realizing these applications. One of the most important, and often overlooked, challenges is the lack of availability of a strong foundation of compositional analysis methods validated on microalgal biomass. Currently, compositional analysis in algae is dominated by the use of interference-prone methods, a lack of full mass balance accounting, and the use of top-down approaches that bin all unaccounted-for mass into a single category, such as carbohydrates. We present here an approach based on a bottom-up algal biomass characterization aimed at moving towards, and highlighting the importance of, full and accurate mass closure to achieve the maximum economic potential from a sustainable and renewable feedstock. Algal biomass representing three genera, Nannochloropsis , Scenedesmus , and Monoraphidium , was subjected to a cell rupture and fractionation process, followed by detailed characterization of each fraction to determine the partitioning of measured and unknown components. The goal of this work is to identify where the missing components partition, and develop a strategy to close the mass balance or identify the unknowns, while utilizing a rigorous characterization approach for characterizing algal biomass. Although only 75–80% of the biomass was accounted for, the fractionation approach utilized here provides key insight into possible chemical components for future investigations.

59 BASIC BIOLOGICAL SCIENCES↗

Chapter Four—MSW characterization and preprocessing for biofuels and bioproducts

The organic fraction of MSW (OFMSW) has a high carbohydrate and lipid content, indicating its good potential as a feedstock for bioethanol and biodiesel production. However, variability in feedstock composition for MSW is a critical challenge for downstream conversion processes such as pyrolysis, gasification, incineration, and biotechnological conversion. MSW characterization is critical to inform and optimize the design of physical handling processes to minimize costs and environmental impacts, and improve the downstream conversion performance of MSW materials. Here, this book chapter focuses on current MSW characterization and preprocessing technologies and discusses the costs, benefits, and environmental impacts associated with MSW preprocessing. Also, the book chapter outlines the potential strategies to increase total revenue and mitigate negative environmental impacts for MSW recycling systems.

09 BIOMASS FUELS↗

Global biomass supply modeling for long-run management of the climate system

Bioenergy is projected to have a prominent, valuable, and maybe essential, role in climate management. However, there is significant variation in projected bioenergy deployment results, as well as concerns about the potential environmental and social implications of supplying biomass. Bioenergy deployment projections are market equilibrium solutions from integrated modeling, yet little is known about the underlying modeling of the supply of biomass as a feedstock for energy use in these modeling frameworks. We undertake a novel diagnostic analysis with ten global models to elucidate, compare, and assess how biomass is supplied within the models used to inform long-run climate management. With experiments that isolate and reveal biomass supply modeling behavior and characteristics (costs, emissions, land use, market effects), we learn about biomass supply tendencies and differences. The insights provide a new level of modeling transparency and understanding of estimated global biomass supplies that informs evaluation of the potential for bioenergy in managing the climate and interpretation of integrated modeling. For each model, we characterize the potential distributions of global biomass supply across regions and feedstock types for increasing levels of quantity supplied, as well as some of the potential societal externalities of supplying biomass. We also evaluate the biomass supply implications of managing these externalities. Finally, we interpret biomass market results from integrated modeling in terms of our new understanding of biomass supply. Overall, we find little consensus between models on where biomass could be cost-effectively produced and the implications. We also reveal model specific biomass supply narratives, with results providing new insights into integrated modeling bioenergy outcomes and differences. The analysis finds that many integrated models are considering and managing emissions and land use externalities of supplying biomass and estimating that environmental and societal trade-offs in the form of land emissions, land conversion, and higher agricultural prices are cost-effective, and to some degree a reality of using biomass, to address climate change.

09 BIOMASS FUELS↗

Improving knife milling performance for biomass preprocessing by using advanced blade materials

Mechanical preprocessing of biomass, including size reduction, is a crucial step in converting biomass into biofuel. However, feedstock inevitably contains abrasive intrinsic and extrinsic inorganics that may cause excessive tool wear in preprocessing. Here, this work demonstrates that performance of a knife mill can be significantly improved by applying a more wear-resistant blade material. A series of full-scale knife mill tests were performed for size reduction of forest residue using blades of tungsten carbide (WC–Co), iron-borided tool steel, and diamond-like carbon (DLC) coated tool steel. Blade material loss was quantified in correlation to the amount of feedstock processed and wear mechanisms were investigated via worn surface characterization. While the thin DLC coating was removed quickly, the WC-Co and iron-borided blades improved the tool life by 8X and 3X compared with the M2 tool steel blades (baseline), respectively. The in-situ throughput and power consumption measurements provided additional insights. The WC-Co and iron-borided blades had ~3X higher throughput than the baseline blades by the end of the test with lower normalized power consumption. The experimental results were then used as input for a techno-economic analysis, which suggested that the more wear resistant blades could cut the knife milling cost by $2–3 per ton of biomass processed with downtime reduced by 65–85%.

36 MATERIALS SCIENCE↗

Rapid and high-throughput determination of sorghum ( Sorghum bicolor ) biomass composition using near infrared spectroscopy and chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum (Sorghum bicolor) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

09 BIOMASS FUELS↗

Integration of plant and microbial oil processing at oilcane biorefineries for more sustainable biofuel production

Oilcane—an oil-accumulating crop engineered from sugarcane—and microbial oil have the potential to improve renewable oil production and help meet the expected demand for bioderived oleochemicals and fuels. To assess the potential synergies of processing both plant and microbial oils, the economic and environmental implications of integrating microbial oil production at oilcane and sugarcane biorefineries were characterized. Due to decreased crop yields that lead to higher simulated feedstock prices and lower biorefinery capacities, current oilcane prototypes result in higher costs and carbon intensities than microbial oil from sugarcane. To inform oilcane feedstock development, we calculated the required biomass yields (as a function of oil content) for oilcane to achieve financial parity with sugarcane. At 10 dw% oil, oilcane can sustain up to 30% less yield than sugarcane and still be more profitable in all simulated scenarios. Assuming continued improvements in microbial oil production from cane juice, achieving this target results in a minimum biodiesel selling price of 1.34 [0.90, 1.85] USD∙L –1 (presented as median [5th, 95th] percentiles), a carbon intensity of 0.51 [0.47, 0.55] kg CO 2 e L –1 , and a total biodiesel yield of 2140 [1870, 2410] L ha –1 year –1 . Compared to biofuel production from soybean, this outcome is equivalent to 3.0–3.9 as much biofuel per hectare of land and a 57%–63% reduction in carbon intensity. While only 20% of simulated scenarios fell within the market price range of biodiesel (0.45–1.11 USD∙L –1 ), if the oilcane biomass yield would improve to 25.6 DMT∙ha –1 ∙y –1 (an equivalent yield to sugarcane) 87% of evaluated scenarios would have a minimum biodiesel selling price within or below the market price range.

09 BIOMASS FUELS↗

Data for Rapid and High-Throughput Determination of Sorghum ( Sorghum bicolor ) Biomass Composition using Near Infrared Spectroscopy and Chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum ( Sorghum bicolor ) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

Biomass Analytics↗

Coupled Hydrothermal Extraction and Ligand-Associated Swellable Glass Media Recovery of Rare Earth Elements from Coal Fly Ash (Final Report)

Wayne State University (WSU) researchers, in collaboration with the University of California-Los Angeles (UCLA) and Los Alamos National Laboratory (LANL), have successfully developed a new sorbent media used in a process that concentrated the rare earth content in a coal fly ash sample from southeast MI by >350×, resulting in >13 wt% REO powder. The project developed a new DTPA-associated media that was used to concentrate total REEs. This project demonstrated a coupled hydrothermal extraction and solid-liquid recovery process that produced REO powder from raw fly ash while nearly eliminating the use of organic solvents. The project successfully: 1) identified a commercially viable ash supply with >$2.5 M in REO value being deposited monthly, 2) hydrothermally extracted >77% of REEs in coal fly ash (20% more than acid alone), 3) developed a new sorbent media that was used to concentrate REEs, 4) and engineered a process that resulted in a >13 wt% REO powder. The media also demonstrates a selectivity for mid and heavy REEs over Ce and La and the potential for use in separating individual rare earth elements. An invention disclosure for the sorbent media has been filed with WSU and a patent application will be submitted in the near future. The project examined the potential to couple hydrothermal leaching of coal fly ash with the engineering of a custom ligand-associated media to provide an organic solvent-free method of extracting and recovering REEs. Fly ash feedstock was collected from Detroit area coal-fired power plants, characterized for REE content, and subjected to a bench-top batch hydrothermal leaching/dissolution process inside custom-build pressure reactors at Los Alamos National Laboratory (LANL). This process applied a dissolution technique previously developed to process spent nuclear fuel and other nuclear materials. The modified ash was acidified and the resulting leachate was enriched with REEs along with Ca, Al, and Si. Ligands known to be effective in lanthanide/actinide separation were evaluated based on a series of criteria such as selectivity and association to organosilica through hydrophobicity. Batch experiments were conducted to establish the best conditions (e.g., pH, eluent, etc.) and best ligand systems for the effective extraction of REEs from the alkaline feed solution obtained from the hydrothermal leaching process. Once the organosilica-ligand extraction media was developed for REE concentration, an acidic solution was used to back extract and concentrate the REEs into a heavily REE-laden strip solution. The REEs in the strip solution were precipitated with oxalate to produce rare earth oxides.

01 COAL, LIGNITE, AND PEAT↗

Production of Carbon Nanomaterials and Sorbents from Domestic U.S. Coal (Final Report)

The main goal of this project was to produce high-value carbon nanomaterials and carbon sorbents from domestic coal resources in a cost-effective manner. Four types of domestic coal samples were processed through a combination of deashing, devolatilization, oxidation, reduction, and activation treatments to produce graphene oxide (GO), reduced graphene oxide (RGO), and activated carbon (AC). The precursors and developed materials were extensively characterized by various methods to investigate the impact of the coal feedstock type on the yield and quality of each product. A commercial graphite-based GO sample was included in the experimental work as the baseline material for comparison with the coal-based materials developed in this work. The performed work also included a technoeconomic analysis and cost estimation for a plant processing 20 tons/day coal, a market evaluation for the graphene materials, and a technology gap analysis. A simple process by concentrated nitric acid oxidation is used to oxidize coal precursors for the production of GO. Fine oxidized coal particles that were separated from larger oxidized coal particles had significantly higher oxygen contents and were identified as coal-based GO samples. Coarse oxidized coal particles were used as precursors for production of AC. Based on the Raman spectroscopy results, coal-based GO samples exhibited G and D bands similar to those of graphite-based GO samples. X-ray photoelectron spectroscopy revealed that coal-based GO samples had surface oxygen contents of ~26-35% that were higher than the oxygen contents of graphite-based GO samples. Larger particles of oxidized coal samples were activated under different conditions to produce high surface area functionalized AC. Prepared materials had surface areas exceeding 1,500 m 2 /g and pore volumes more than 1 cm 3 /g with different pore size distributions. Reduced graphene oxide samples were prepared by thermal reduction of both coal-based and graphite-based GO samples at 170-2800 ºC. Coal-based and graphite-based RGO samples exhibited similar carbon contents, Raman spectra, and XRD profiles. Heat treatment above 1500 ºC shifted RGO to synthetic graphite. Among anthracite, bituminous, subbituminous, and lignite coals tested, anthracite was the best precursor to produce carbon nanomaterials exhibiting properties similar to those of graphite-based materials. Anthracite-based carbon nanomaterials also had the highest production yields. Technoeconomic analysis estimated the production cost of GO and RGO for anthracite-based samples at about 2,600 and 4,200 $/ton, respectively, which is about two orders of magnitude lower than the current estimated price of graphite-based materials. Several gaps to further develop the proposed technology were identified and discussed that include process and equipment optimization, process integration, need for additional bench- and pilot-scale experiments, and other items to reduce the scale up risk. Market analysis reports suggested a compound annual growth rate of 40% for graphene and related materials. Short-term applications include composites, inks, and coatings. However, energy storage applications appear to be the dominant potential long-term applications. Different applications of coal-based GO and RGO need to be explored and clear metrics and standards for each application need to be developed.

01 COAL, LIGNITE, AND PEAT↗

Discerning the Impact of Powder Feedstock Variability on Structure, Property, and Performance of Selective Laser Melted Alloy 718: A Principal Component Analysis (PCA) of Feedstock Variability

Extensive mechanical, chemical and microstructural analyses were conducted on additively manufactured Alloy 718 to characterize powders from multiple vendors to determine the effects of variations observed in the powders had on the consolidated material. With over 190 variables examined, it was necessary to reduce the number of variables and identify the variables and classes of variables that had the greatest effect. Principle Component Analysis (PCA) was used to reduce the number of variable to effectively 12 while identifying several classes of variables as most important.

Ellis, David↗

Lunar mineral feedstocks from rocks and soils: X-ray digital imaging in resource evaluation

The rocks and soils of the Moon provide raw materials essential to the successful establishment of a lunar base. Efficient exploitation of these resources requires accurate characterization of mineral abundances, sizes/shapes, and association of 'ore' and 'gangue' phases, as well as the technology to generate high-yield/high-grade feedstocks. Only recently have x-ray mapping and digital imaging techniques been applied to lunar resource evaluation. The topics covered include inherent differences between lunar basalts and soils and quantitative comparison of rock-derived and soil-derived ilmenite concentrates. It is concluded that x-ray digital-imaging characterization of lunar raw materials provides a quantitative comparison that is unattainable by traditional petrographic techniques. These data are necessary for accurately determining mineral distributions of soil and crushed rock material. Application of these techniques will provide an important link to choosing the best raw material for mineral beneficiation.

Chambers, John G.↗