Oluwafemi Oyedeji

Miscanthus × giganteus (Mxg) is a high-yield bioenergy perennial crop suitable for resilient cultivation and conversion into fuels, chemicals, and biomaterials due to its adaptability to marginal lands and low input needs. In this study, we present a Python-based integrated Geographic Information System (GIS) Decision Support System model, named DREEM, for identifying optimal cultivation sites for Mxg in Tennessee (TN). The DREEM incorporates an initial data processing layer that corrects over- and under-estimated sub-county land availability to better reflect on-ground conditions. The model prioritizes pastureland parcels ≥30 acres, applying thresholds of ≥30 inches/year precipitation, ~50 °F average temperature, soil pH 5.5–7.5, well- to moderately well-drained soils, slopes ≤15%, and county-level land rent. Our model estimates yield, normalized costs, and greenhouse gas emissions via techno-economic (TEA) and life cycle assessment (LCA). DREEM identified approximately 2,319,875 acres of USDA-calibrated pastureland across TN that met parcel size and climate suitability criteria. DBSCAN outlined three clusters for which normalized unit production costs ranged from $46.7–52.7/dry-tonne, with emissions averaging 67.4 kg CO2e/dry-tonne. Cluster 2 showed the lowest normalized production costs of $46.7–48.1/dry-tonne, but required a higher supply radius of 65 km. The establishment year (Year 1) had the highest costs and emissions, which declined with yield gains in subsequent years (Years 2-15). In Years 2-15, fertilizers dominate cost and emission metrics, underscoring the importance of input management. In summary, the DREEM provides a scalable, data-driven site selection model applicable beyond TN for Mxg production, supporting bioeconomy development through transparent, stakeholder-oriented insights.

Tristructural-isotropic (TRISO) fuel and other coated particle nuclear fuels have been selected as candidate fuels for a wide range of microreactor concepts for terrestrial use and space exploration. The fabrication of these fuels largely relies on spout fluidized bed chemical vapor deposition, a process in which a batch of fuel kernels is subjected to flows of fluidizing and pyrolyzing gases, which are precursors to the desired coating composition. Kernel sphericity, particle size distribution (PSD), and surface roughness are critical parameters that can affect fluidization, coating quality, and ultimately fuel performance. Understanding the impact of PSD of the initial fuel kernel could allow the use of kernels with a wider fuel specification. If possible, reducing requirements on sphericity and particle size uniformity without compromising coating performance could reduce process cost, time, and waste generation. Therefore, a better understanding of their impact on the fluidization and coating characteristics is needed. This work used computational fluid dynamics coupled with discrete element modeling to assess the impact of polydispersity of the initial kernel population on fluidization for two mean particle sizes: 250 and 400 um. The initial particle size is normally distributed with standard deviations varying from 12 um (matching experimental conditions) to 63 um. The results show that preferential fluidization effects are increasingly present with wider PSDs and are more prevalent for the smaller mean particle size of 250 um. Increasing the PSD leads to an increase in coating thickness variations for the smallest particles and smaller coating thickness variations for the largest particles. The results have important implications to fabrication efforts, where consistency of coating thickness is of importance.

Achieving a secure, abundant, and affordable energy future requires a robust and adaptable energy strategy, with bioenergy playing a pivotal role. Biomass‐based energy presents a promising pathway to use domestic resources while fostering economic opportunities in rural areas. Despite the potential to source more than 1 billion dry short tons of biomass annually in the US, significant infrastructure and economic barriers hinder full utilization for energy production. This study used the Biofuel Infrastructure, Logistics, and Transportation (BILT) model to assess biorefinery siting and scale and determine the number and size of facilities required to maximize use of the US biomass potential. A spatially agnostic approach first assessed the effects of facility capacity and transportation constraints on biomass use. Then, a spatially explicit analysis integrated county‐level biomass availability from the US Department of Energy's 2023 Billion‐Ton Report and technoeconomic assessments to evaluate different biorefinery deployment scenarios. The results indicate that an optimized mix of facility sizes is essential to leverage biomass resources fully across varying regional production densities to maximize use of the US biomass potential. Larger biorefineries or co‐located smaller facilities significantly enhance biomass use while reducing costs through economies of scale. These findings underscore the importance of strategically balancing facility capacity and spatial distribution to optimize the bioenergy supply chain. This study provides critical insights for advancing the US bioenergy economy by aligning biorefinery deployment with biomass resource availability and economic viability.

Fast pyrolysis of woody materials is a technology pathway for producing renewable fuels and chemicals. This is a presentation of isolating needles, bark, and stemwood from a single tree as well as isolating stemwood and whole tree samples from the same species of tree with different ages and pyrolyzing each individually as well as in mixtures. This gives insight into the role of tree anatomical fractions on the resulting intermediate oil product as well as into interactions between these components. The highest carbon content oil (45.1 wt% as received) was produced from a one-to-one mixture of stemwood and needles, followed by the pure stemwood (43.4–43.8 wt% as received), while the lowest oil carbon content was from a one-to-one blend of bark and needles (26.7 wt% as received). The pyrolysis oil yield (combining oil and aqueous where separation occurred) varied from 54 wt% as received (needles) to 72.3 wt% as received (stemwood). When comparing trees of different ages, we find the change in the ratio of the anatomical fractions is a dominant factor in the product composition and yields, while the product composition and yields vary slightly with tree age when only the stemwood is pyrolyzed. Here we present the bench-scale pyrolysis, yields, and product characterization of loblolly pine feedstocks (13- vs. 23 year-old, residues, air-classified residues, whole tree, needles, bark, and stemwood).

Biofibers serve as effective reinforcements for neat polylactic acid (PLA) in biocomposites, offering an attractive opportunity to decarbonize the manufacturing sector of the United States by displacing fossil‐based reinforcement fibers such as carbon fibers. Also, biofiber production can stimulate economic growth in rural economies, fueling sustainable development. PLA resins are commonly compounded with biofibers to create biocomposites suitable for additive manufacturing. PLA‐biofiber composites often exhibit better overall material properties than neat (pure) PLA, but the associations between biofiber properties and the material properties of their biocomposites remain largely unexplored. Hence, this research delves into a comprehensive exploration of diverse biofibers, scrutinizing their physical and chemical attributes, including size, shape, ash content and biochemical composition. The study meticulously analyzes the flow properties of each biofiber and elucidates the ultimate tensile strengths and Young's modulus of corresponding biocomposite samples. Noteworthy correlations between biofiber and biocomposite tensile properties are uncovered, shedding light on critical interrelationships. The study introduces an approach employing regression models to predict the ultimate tensile strength and Young's modulus of biocomposites. These models, validated with a cross‐validation technique, exhibit remarkable predictive accuracy, particularly in estimating ultimate tensile strength. © 2024 Oak Ridge National Laboratory managed by UT‐Battelle, LLC and The Author(s). Polymer International published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Bioenergy provided the largest single source of renewable energy in the United States in 2022, comprising approximately 5% of U.S. energy produced (EIA 2023) (Figure ES-1). The mission of the U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) is to develop and demonstrate technologies to accelerate net greenhouse gas emissions reductions through the cost-effective, sustainable use of biomass and waste feedstocks across the U.S. economy. This report assesses the potential for renewable biomass resources to support DOE goals by displacing fossil resources such as petroleum with renewable biogenic carbon resources that, when managed efficiently, have a lower climate impact than petroleum sources of carbon. Demand for renewable fuels is growing, especially for the aviation, marine, and rail sectors. For example, the Biden administration’s Sustainable Aviation Fuel (SAF) Grand Challenge targets the production of 35 billion gallons per year of SAF by 2050. Such targets raise the question: Does the United States have sufficient biomass supplies, within a practical range of environmental, economic, and resource constraints, to fill these needs? The answer is yes, provided adequate markets can be established, and that environmental safeguards are established to ensure sustainable outcomes. This report aims to inform stakeholders of the types and quantities of biomass resources that could potentially be available in the future and under what conditions. The report provides a detailed assessment of current and potential biomass production capacity in the United States at defined price points and under conditions that protect food production and environmental integrity.

Highlights Loblolly pine and corn stover fiber were successfully surface-treated with epoxy. Surface-treated fibers produced biocomposites with improved tensile properties. Surface treatment process results in a more evenly dispersed fiber bulk structure. Tensile strength and Young’s modulus of the biocomposite reached 58 MPa and 5 GPa, respectively. Abstract. Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber’s characteristics and biocomposite’s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young’s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties. Keywords: Fiber size and shape, Fiber surface roughness, Flow properties, PLA-based biocomposite, Surface treatment.