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DOE OSTI2023

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗

DOE OSTI2023

High-moisture pelleting of corn stover using pilot- and commercial-scale systems: Impact of moisture content, L / D ratio and hammer mill screen size on pellet quality and energy consumption

Here, high-moisture pelleting of corn stover was tested in pilot- and commercial-scale systems. For the pilot-scale study, a 6.35 mm screen size hammer mill ground corn stover was reconditioned to moisture between 14 and 29.6% (w.b.), and 5, 7 and 9 L/D ratio pellet die were used. At 29% corn stover moisture content and L/D ratios of 5 and 9, the bulk density and durability of the pellets were ≤450 kg/m 3 and <90% and >540 kg/m 3 and >90%, respectively. Increasing the feedstock moisture and L/D ratio increased the pelleting energy. Increasing the hammer mill screen size to 11.11 mm reduced the bulk density but not the durability. The response surface models adequately described the pelleting process (R 2 ≥ 0.88), and analysis of variance showed a strong interaction between the process variables and pellet properties. Commercial-scale testing of high-moisture pelleting using 6.35 mm ground corn stover bales in the moisture range 24–26% (w.b.) produced pellets with a density of >675 kg/m 3 and durability of >98%, whereas increasing the hammer mill screen size to 11.11 mm reduced the bulk density by about 100 kg/m 3 but not the durability. The energy consumption of the commercial-scale unit operations for the high-moisture pelleting process was in the range 98–124 kW h/ton, which is 64–72% less energy than conventional pelleting that requires energy about 350 kW h/ton for biomass drying from 30% (w.b.) to 10% (w.b.) moisture content before pelleting. Pellets produced using high-moisture pelleting met International Organization for Standardization and Pellets Fuel Institute international standards. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

09 BIOMASS FUELS↗

DOE OSTI2022

Particle scale impacts on deconstruction energy of pine residues

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on generation of fines that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbon content (minimum carbon specification) and maximum ash content and the delivered feedstock cost impacts of not being able to feed residue not meeting both specifications to the conversion reactor. Laboratory data on the impacts of input particle size and moisture content on the exit particle size were received from FCIC Subtask 5.2 from their single particle impact population balance modeling study. Additional throughput and energy consumption data were obtained from FCIC Subtask 5.2 for the same grinder with a 6 mm screen in place. These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents in the separated fines had not been analyzed in the laboratory at the time of the model runs, we chose to assume that the ash distributed proportionally with total mass into the overs and unders in the disk screen following grinding. Key takeaways from this Case Study are that it is significantly more cost effective to hammer mill the residue prior to drying, even though the grinder throughput is lower and energy consumption is higher versus drying first before grinding. An effect of dry grinding versus high moisture grinding is the production of higher amounts of fines during dry grinding, leading to significantly more of the ground feedstock being rejected by conversion for being below a minimum particle size. With wet grinding the system is still able to produce more preprocessed feedstock meeting the minimum particle size specification even though the instantaneous throughput is lower than for the case of grinding dry feedstock. Additionally, even without the higher fines production from dry grinding, the status quo would still be more costly than wet grinding because the material is rejected after the drying energy has already been input for the dry grinding case. Finally, significant reductions in drying energy are obtained by drying after grinding, and those reductions are of far greater magnitude than the grinding energy increase.

09 BIOMASS FUELS↗

NASA NTRS2018

Plasticity and Damage Modeling of Stress Asymmetry and Dynamic Behavior of AFS Additive Manufactured Aluminum Alloy 2219

The Solid State Additive Manufacturing (AM) process referred as MELD that fabricated the samples in this study, provides a new path for repairing, coating, joining and additive manufacturing metals and metal matrix composites. This research will be the first application of a physics-based microstructure dependent internal state variable (ISV) plasticity and damage material model to capture the mechanical response of an AM Aluminum Alloy (AA) 2219 via the MELD process. In this research, a microstructure-based internal state variable (ISV) plasticity-damage model was used to capture the mechanical behavior of AFS 2219 aluminum alloy. Aeroprobe Corporation, creator and patent holder for the MELD process, fabricated the material by pushing a solid filler rod of AA2219-T861 material through a hollow rotating tool onto an AA2219 T851 plate substrate. As feedstock, solid or powder precursor metals are pushed through a nonconsumable rotating cylindrical tool. Herein, added layers are deposited and metallurgically bonded to substrate material or previously deposited layers by the heat generated from the rotating tool through plastic deformation of the filler material. Once a layer has been added, the tool height increases, and starts the deposition of the next layer. This process results in beneficial properties such as grain refinement, homogenization and reduced porosity (fully dense). This process will experience temperatures similar to those in the weld nugget zone (WNZ) in friction stir welding (FSW), ranging from 0.6-0.9 Tm, with Tm being the melting point of the material. MELD is highly scalable with AA deposition rates reaching over 1000 cm3/hr, which allows for MELD being used for repairs, coatings, and building components. A motivating factor driving the research for physics-based history dependent material modeling of MELD components is the ability to accurately capture the stress-state and strain rate dependence in the material caused by variations in material microstructure from the MELD processing of new or repaired components. The ISV model incorporates microstructural content and is consistent with continuum level kinematics, kinetics, and thermodynamics. These features allow the ISV model to capture large deformations at the structural scale using the kinematic and isotropic hardening, while microscale damage is obtained from the microstructural features. The benefits of the ISV model arise from the inclusion of structure-property relationships identified from microstructural characterization and experimentation. The Bauschinger effect (BE) is an important concept, vital in the accurate prediction of cyclic stress-strain response of ductile materials such as metals. The ISV model has been successfully used to capture the behavior and damage, and the BE of different aluminum alloys and steels. The ISV model uses kinematic and isotropic hardening to help capture deformations of the material at the macro scale. To understand this hardening relationship, calculating the kinematic and isotropic hardening relationship in the material is warranted for a high-fidelity model. Electron Backscattered Diffraction (EBSD) was used to characterize the as-fabricated microstructure, where a fully-dense equiaxed grain morphology with average grain size of 2.5 μm was observed. Microhardness mapping of the as-built structures, monotonic tension and compression experiments at both quasi-static (0.001/s) strain rates, tension-followed-by-compression and compression-followed-by-tension experiments were performed to obtain the set of plasticity and damage constants necessary to capture strain rate and stress state behavior of this additive material. To calibrate the plasticity-damage model, a single set of constants were determined to capture the different stress states the MELD AA2219. One set of the constants was determined from experimental true stress-strain curves for the tension and compression data. Additionally, microstructural information and data from the open literature were used as the other model constants. This research is a first of its kind for AFS AA2219, includes correlating the ISV model to the monotonic experimental results that capture the isotropic and kinematic plasticity mechanical response.

Rivera, O. G.↗

DOE OSTI2025

Feature Based Qualification of 17-4PH Stainless Steel to Evaluate Location-Specific Variability in Wire Arc Additive Manufacturing

Qualifying large-scale metal additive manufacturing (M-AM) technologies such as wire arc additive manufacturing (WAAM) can be challenging. This is especially significant in precipitation hardened martensitic stainless steels like SS 17-4PH, where thermal histories induce location-specific microstructural variability and property anisotropy. The Department of Defense (DOD) and the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center (GVSC) Ground Vehicle Materials Engineering (GVME) aim to build robust and qualified large-scale M-AM workflows that could reduce the time and cost through quick and informed evaluation, testing, and development of feedstock, processes, and parts. The report presents the findings from the collaborative efforts between Oak Ridge National Laboratory (ORNL) and the U.S. Army GVSC GVME. The aim of this project was to develop a geometric feature-based qualification framework for WAAM of SS 17-4PH components. This report outlines selection methodology of representative build geometries, optimization of WAAM process parameters, in-situ monitoring, microstructure-property evaluation, thermal simulations, as well as data visualization techniques incorporated in this project. The results from this project demonstrate a clear understanding of thermal history dependent phase evolution and consequent location-specific property variations in WAAM of SS 17-4PH. These results in conjunction with the data-driven methodologies used in this project are expected to reduce qualification timelines, improve predictability, and accelerate the development of reliable feature-based qualification strategies for part production via large-scale M-AM technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A synthetic co-culture for bioproduction of ammonia from methane and air

Abstract Fixed nitrogen fertilizers feed 50% of the global population, but most fixed nitrogen production occurs using energy-intensive Haber–Bosch-based chemistry combining nitrogen (N2) from air with gaseous hydrogen (H2) from methane (CH4) at high temperatures and pressures in large-scale facilities sensitive to supply chain disruptions. This work demonstrates the biological transformation of atmospheric N2 into ammonia (NH3) using CH4 as the sole carbon and energy source in a single vessel at ambient pressure and temperature, representing a biological “room-pressure and room-temperature” route to NH3 that could ultimately be developed to support compact, remote, NH3 production facilities amenable to distributed biomanufacturing. The synthetic microbial co-culture of engineered methanotroph Methylomicrobium buryatense (now Methylotuvimicrobium buryatense) and diazotroph Azotobacter vinelandii converted three CH4 molecules to l-lactate (C3H6O3) and powered gaseous N2 conversion to NH3. The design used division of labor and mutualistic metabolism strategies to address the oxygen sensitivity of nitrogenase and maximize CH4 oxidation efficiency. Media pH and salinity were central variables supporting co-cultivation. Carbon concentration heavily influenced NH3 production. Smaller-scale NH3 production near dispersed, abundant, and renewable CH4 sources could reduce disruption risks and capitalize on untapped energy resources. One-Sentence Summary Co-culture of engineered microorganisms Methylomicrobium buryatense and Azotobacter vinelandii facilitated the use of methane gas as a sole carbon feedstock to produce ammonia in an ambient temperature, atmospheric pressure, single-vessel system.

Biotechnology & Applied Microbiology↗

DOE OSTI2020

Variable Chain Length Carboxylic Acids as Modifiers to Enhance the Antiviral Efficacy of Sodium Dodecyl Sulfate.

Non-toxic disinfectants composed of readily available commodity chemicals are needed for immediate response to the current COVID-19 pandemic. One such area is the active research field for food-grade sanitization. Combinations of levulinic acid, a five-carbon ketocarboxylic acid, and sodium dodecyl sulfate, have been frequently described for antibacterial use on food contact surfaces. Levulinic acid has been identified as a renewable feedstock but is not presently in commodity production. Other carboxylic acids, such as acetic acid, may be equally usable and food-safe. Acidic and buffered solutions were highly effective, yielding no countable surviving organisms. The high efficacy of each acid may suggest that carboxylic acid sanitizers in general have potential use against viruses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Characterization of Arsenic and Selenium in Coal Fly Ash to Improve Evaluations for Disposal and Reuse Potential (Final Technical Report)

Coal fly ash is a high volume waste material that is discarded in landfills and surface water impoundments across the U.S. and is also widely recycled for a variety of applications. The leaching of potential of contaminants of concern, such as arsenic (As) and selenium (Se), is often the driver of risk assessments for coal ash disposal and reuse. The extent of leachable As and Se depends on several factors related to environmental conditions and fly ash characteristics. Previous studies employed various methods to delineate the concentration, chemical form, and distribution of As and Se in fly ash materials. However, few studies have attempted to directly correlate these properties to mobilization parameters relevant to disposal and reuse. Instead, the coal residuals industries often rely upon standardized leaching protocols that can be laborious or involve hazardous chemicals. The goals of the project were to: 1) Develop and evaluate a characterization protocol that can be used to screen fly ash samples for leachability of As and Se; 2) Characterize As, Se, and associated constituents of fly ash particles at multiple length scales (nanometer to micrometer) to determine if elemental associations differ as a function of the resolution of characterization; and 3) Establish a predictive model for the chemical composition of coal ash produced annually at major U.S. coal fired power facilities on 50-year national coal supply records. For the first objective, we performed leaching experiments with 52 fly ash samples collected from 15 different U.S. power plants and representing coal feedstocks from the three major domestic coal regions. For this work, we assessed the mobilization potential of As and Se in fly ash based on standardized leaching protocols and performed multivariate and lasso regression analyses to explore correlations of leachable As and Se contents with characteristics such as major element contents, loss on ignition (LOI) and pH. The results of regression models indicated that major elements (Fe, Ca, Al) for a wide range of fly ashes can serve as predictor variables for the leaching potential of As, but not for Se. LOI and pH were not important predictive variables in the models. Both regression approaches resulted in relatively strong fits for leachable As (correlation coefficient R 2 = 0.78 for both models) compared to models for leachable Se (R 2 = 0.49). Overall, these results suggest that correlation models combined with on-site elemental analysis with portable analyzers may enable a screening method for leachable As in coal ash. For the second objective, we utilized nanoscale 2-D imaging (30-50 nm spot size) with the Hard X-ray Nanoprobe (HXN) in combination with microprobe X-ray capabilities (~5 µm resolution) to determine As and Se elemental associations in fly ash particles. Speciation of As and Se was also measured at the nano- to microscale with X-ray absorption spectroscopy. The enhanced resolution of HXN showed As and Se that were diffusely located around or comingled with Ca- and Fe-rich particles. The results also showed nanoparticles of Se attached to the surface of fly ash grains. Overall, a comparison of As and Se species across scales highlights the heterogeneity and complexity of chemical associations for these trace elements of concern in coal fly ash. For the final objective, we developed a predictive model for major element composition of coal ash in reserve at disposal sites of major U.S. coal fired power plants. This model was constructed from coal purchase records of 705 power stations from 1973-2022 and was trained on coal ash composition data showing that coal ash elemental composition is strongly associated with the source of feedstock coal. The model showed regional shifts in the major element contents of ash produced by power plants in the last 50 years, particularly for calcium and iron (expressed as %CaO and %Fe 2 O 3 ), as coal-fired power stations changed their source of coal over this time frame. Our approach enables an estimation of coal ash chemical composition that is stored in waste impoundments at individual power stations. Such information can help delineate the regional market potential for material applications that would utilize coal ash harvested from disposal sites across the U.S.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Impact of Anatomical Fractionation of Corn Stover on Hammer Mill Throughput and Energy Consumption

ash content↗

DOE OSTI2023

The significance of biomass densification in biological-based biorefineries: A critical review

Replacing fossil fuels with renewable biofuels derived from lignocellulosic biomass is an important aspect of addressing environmental challenges and developing a sustainable industrial society. Densification overcomes the problems of low bulk density and poor flowability of biomass and has been commercialized for producing solid biofuels, but the overall impact of densification on biological-based biorefineries that primarily target liquid fuels (e.g., ethanol) is still under investigation. Herein, this review provides a thorough summary of the application of densified biomass in biological-based biorefineries. First, the effects of densification parameters as well as variables of biomass materials on the densified products’ quality are reviewed, and different commonly used densification technologies are also discussed and compared. Then, the discussion focuses on the physiochemical modifications of biomass caused by densification that may influence further pretreatment and/or enzymatic hydrolysis in biorefineries. Industrial pelleting has been generally shown to exhibit positive/neutral effects on the enzymatic hydrolysis of multiple biomass feedstocks after pretreatments, indicating the viability of using pellets as starting feedstocks in biorefineries. Densification causes structural disruption of biomass, which may facilitate further biochemical conversions. Integrating biomass densification in the feedstock supply chain is feasible for large-scale biorefineries to overcome the techno-economic barriers and become profitable. Suggestions are presented for the efficiency enhancement and cost reduction in densification-based biorefineries. To enable wider applications, it is now the time to employ more demo and full-scale activities in different regions of the world pushing the research and innovation of densification integrated within biorefining.

09 BIOMASS FUELS↗

DOE OSTI2022

Impact of anatomical fractionation of corn stover on hammer mill throughput and energy consumption

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on loss of very wet stover that causes failures in the first stage grinder and that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbohydrate content (minimum total carbohydrate specification) and maximum ash content and the delivered feedstock cost impacts of not being able to feed stover not meeting the total carbohydrate specification to the conversion reactor. Laboratory data on the impacts of moisture content and tissue fraction on throughput and energy consumption in a stage 2 hammer mill were received from FCIC Subtask 5.1. Additional air classifier throughput, energy consumption and separation efficiency data were obtained from FCIC Subtask 5.1 for the new air classifier, which has three exit streams (lights, middle and heavies). These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents and particle sizes had not been analyzed in the laboratory at the time of the model runs, we assumed that the ash distributed proportionally with total mass into the lights and heavies in an air classifier having two exit streams (lights and heavies) and that the lights fraction from the air classifier was not removed. Key takeaways from this Case Study are that due to lower energy consumption, it is more cost effective to hammer mill fractionated corn stover tissues than whole stover. Reduction of grinding energy was significant and may possibly be connected to particle-particle interactions in the grinder that lead to increased residence time of leaves and husks, resulting in decreased throughput and higher generation of fines when milling whole stover. While we did not see significant impacts to throughput, this was due to moisture failures of the first stage grinder in each system dominating failures and downtime. The operating cost savings of reduced grinding energy savings in the second stage hammer mills alone was high enough to offset the added capital cost of the air classifier and extra grinding line.

09 BIOMASS FUELS↗

DOE OSTI2020

Preservation of Microalgae, Lignocellulosic Biomass Blends by Ensiling to Enable Consistent Year-Round Feedstock Supply for Thermochemical Conversion to Biofuels

Seasonal variation in microalgae productivity is a significant barrier to economical production of algae biofuels and chemicals. Summer production can be 3–5 times higher than in the winter resulting in uneven feedstock supplies at algae biorefineries. A portion of the summer production must be preserved for conversion in the winter in order to maintain a biorefinery running at capacity. Ensiling, a preservation process that utilizes lactic acid fermentation to limit microbial degradation, has been demonstrated to successfully stabilize algae biomass (20% solids) and algae-lignocellulosic blends (40% algae-60% lignocellulosic biomass, dry basis) for over 6 months, resulting in fuel production cost savings with fewer emissions. Preservation of algae as blends could be beneficial to biorefineries that utilize thermochemical approaches to fuel production as co-processing of algae and lignocellulosic biomass has been observed to enhance biocrude yield and improve oil quality. This study conducts a resource assessment of biomass residues in the southern United States to identify materials available during peak algae productivity and in sufficient quantity to meet the algae storage needs of an algae biofuel industry. Eight feedstocks met the quantity threshold but only three, distillers grains, haylage, and yard waste, were also available in season. Storage experiments utilizing both freshwater and marine strains of microalgae – Scenedesmus acutus, Chlorella vulgaris, Chlorella zofingiensis, Nannochloropsis gaditana, and Porphyridium purpureum – and yard waste were conducted for 30 days. Storage losses were less than 10% in all but one case, and the pH of all but one blend was reduced to less than 4.7, indicating that yard waste is a suitable feedstock for blending with algae prior to storage. To better understand whether the benefits to conversion realized by processing blends might be affected by storage, elemental analysis and bomb calorimetry of pre- and post-storage algae-yard waste blends were conducted to characterize changes occurring during storage. Storing algae biomass as blends with lignocellulosic biomass could be an effective method of mitigating seasonal variability in algae biomass production while retaining the synergistic effect of co-processing algae blends in thermochemical conversion.

09 BIOMASS FUELS↗

DOE OSTI2024

Modeling the Moisture Content and Dry Matter Loss in Dynamic Woody Biomass Storage Piles with Variable Extraction

The urgent need to mitigate climate change has spurred significant interest in renewable energy sources. This paper explores the storage and processing of woody biomass for biofuel production, considering the dynamic nature of biomass piles in real-world scenarios. A model has been developed to analyze moisture content changes and dry matter loss in woody biomass stored in piles prior to processing, taking into account varying extraction methods and environmental conditions. Case studies that examine the effects of different unpiling methods (FIFO, LIFO, and homogeneous) on moisture content and dry matter loss under various feedstock arrival rates and weather conditions are presented. Results indicate that unpiling methods significantly impact moisture content, with LIFO typically resulting in higher moisture content due to the utilization of fresher feedstock. Dry matter loss increases with pile size and time, emphasizing the importance of accurate modeling for assessing carbon emissions and feedstock quality. Furthermore, the model highlights the importance of process loading order and extraction methods in biomass storage, suggesting potential cost benefits associated with decreased moisture content. The difference between different extraction methods could vary the moisture content in the feedstock reaching the biofuel process by as much as 37.6%, however dry matter loss varies minimally for realistic pile changes. Overall, this research contributes to a better understanding of biomass storage dynamics and informs sustainable biofuel production practices.

Niska, Janel↗

DOE OSTI2022

Data Mining and Visualization of High-Dimensional ICME Data for Additive Manufacturing

Integrated computational materials engineering (ICME) methods combining CALPHAD with process-based simulations can produce rich, high-dimensional data for alloy and process design. In ICME methods for metallurgical applications, the visualization and interpretation of such high-dimensional data has previously been through heat maps represented in 2 or 3 dimensions. While such an approach is ideal when one variable is varied at a time, in the case of high-dimensional data with multiple variables varied simultaneously, as is the case in additive manufacturing, interpreting the trends through two- or three-dimensional heat maps becomes challenging. Here, we propose a strategy of mixed visual data mining and quantitative analysis for high-dimensional metallurgical and process data using high-throughput thermodynamic calculations. Two case studies show the application of the proposed approach. The first case study investigated the effects of feedstock chemistry on the δ ferrite formation in 316L stainless steel powders used for binder jet additive manufacturing. The second case study linked Scheil–Gulliver calculations to a process model for dissimilar joining of aluminum alloys 5356 and 6111 during laser hot-wire additive manufacturing. Both cases contained thousands of calculated data points, showcasing the utility of visual data analysis through parallel coordinate plotting, Pearson correlation coefficient matrices, and scatter matrices compared to traditional process maps. These visualization techniques can be extended to many additive manufacturing problems to capture process–structure–property relationships for additively manufactured components.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Sustainable Li-ion anode material from Fe-catalyzed graphitization of paper waste

We report a novel method for the conversion of paper towel waste to biographite anode material is developed and optimized for use in Li-ion batteries. The surge in demand for Li-ion battery anode materials coupled with the unsustainable and inefficient methods of producing battery-grade graphite necessitate alternative carbon feedstocks and graphitization technologies. Paper waste (PW) is identified as a suitable carbon feedstock for iron-catalyzed graphitization due to its sustainability, low cost, low ash content, and ample supply for the intended end use. A Box Behnken experimental design for statistical optimization is pursued for untreated and pre-carbonized PW with factors of temperature (1100-1300 °C), hold time (1-5 h), and iron catalyst loading (0.5-1.5x fixed carbon content) with biographite crystal size as the primary response variable. Temperature and iron catalyst loading are found to be significant factors, whereas hold time is found to be insignificant. Reversible capacities of the biographite anodes are found to be 340-355 mAh g-1 with 99% capacity retention over 100 cycles, indicating good electrochemical performance relative to commercial graphite anodes. The initial Coulombic efficiency of untreated and pre-carbonized biographites, however, are 77% and 75%, respectively, suggesting parasitic reactions including electrolyte decomposition.

25 ENERGY STORAGE↗

DOE OSTI2022

Hydrogen and Battery Storage Technologies for Low-Cost Energy Decarbonization in Distribution Networks

Deep energy decarbonization cannot be achieved without high penetration of renewables. At higher renewable energy penetrations, the variability and intermittent nature of solar photovoltaic (PV) electricity can cause ramping issues with existing fossil fuel generation, requiring longer term energy storage to increase the reliability of grid operation. Here, a proton exchange membrane electrolyzer can produce H 2 and serves as a utility controllable load. The produced H 2 can then be stored and converted back into electricity, or mixed with natural gas, or used as transportation fuel, or chemical feedstock. This paper considers the perspective of the distribution system operator that operates the distributed energy resources on a standard IEEE 33-node distribution network considering the technical and physical constraints with the goal of minimizing total investment and operation cost. Different case studies, at very high PV penetrations are considered to show the challenges and path to net-zero emission energy production using H 2 energy. Sensitivity of utility PV costs and electrolyzer capital costs on producing H 2 at $\$1$ /kg are presented showing that the distribution network could produce 100% renewable electricity and H 2 could be produced at a cost of $\$1$ /kg by 2050 with conservative cost estimates and by 2030 with accelerated cost declines.

25 ENERGY STORAGE↗

DOE OSTI2025

Effect of particle size and moisture on flow performance of loblolly pine anatomical fractions: Experimental findings and model predictions

The rising energy demand has highlighted biomass as a promising next-generation energy source. However, commercializing biomass-derived energy faces challenges, particularly in handling biomass feedstock. Factors like particle size, shape, moisture content, and surface roughness significantly impact biomass flowability. This study addresses a crucial knowledge gap by examining the effects of particle size and moisture content on the flow behavior and shear properties of different anatomical fractions of loblolly pine (Pinus taeda). The bulk shear behavior was examined using a Schulze ring shear tester, while flow performance was tested through gravity-driven flow experiments in a variable wedge-shape hopper. Results were incorporated into empirical and machine learning-based flow prediction models to evaluate their accuracy and limitations. The study found that samples with higher moisture content show higher unconfined yield strength. The critical arching distance increased with particle size, e.g., from approximately 13 and 33 mm for 2- and 6-mm whole chips, respectively at a 32-degree inclination angle. Conversely, the flow rate decreased for a given hopper opening as particle size increased. For instance, at a 60-mm hopper opening and a 32-degree inclination angle, the mass flow rates for 2- and 6-mm whole chips were 7.83 and 6.42 tonne/h, respectively. The empirical model consistently overpredicted the mass flow rate for all anatomical fractions, while the machine learning model more accurately predicted the central tendency of flow rate but was insensitive to varying tissue proportions. These novel findings provide comprehensive characterization of anatomical fractions, reveal significant combined effects of particle size and moisture content on biomass flow behavior, and demonstrate a better predictive accuracy of a machine learning model, all of which are useful for optimizing material handling strategies and biomass utilization technologies in the industry.

09 - BIOMASS FUELS↗

NASA NTRS1982

Glass shell manufacturing in space

Highly-uniform, hollow glass spheres, which are used for inertial-confinement fusion targets, are formed from metal-organic gel powder feedstock in a drop-tower furnace. The modelling of this gel-to-sphere transformation has consisted of three phases: gel thermochemistry, furnance-to-gel heat transfer, and gravity-driven degradation of the concentricity of the molten shell. The heat transfer from the furnace to the free-falling gel particle was modelled with forced convection. The gel mass, dimensions, and specific heat as well as furnace temperature profile and furnace gas conductivity, were controlled variables. This model has been experimentally verified. In the third phase, a mathematical model was developed to describe the gravity-driven degradation of concentricity in molten glass shells.

Nolen, R. L.↗