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DOE OSTI2023

Effects of 2D filler on rheology of additive manufacturing polymers: Simulation and experiment on polyetherketoneketone-mica composites

Polymeric composites have attracted increasing interest in fundamental studies and industrial applications due to their often-superior characteristics over conventional pure polymers. In this work, we studied the relationship between the rheological properties, critical in processing methods such as additive manufacturing, and the structure of a polymer-2D filler system by experiment and simulation methods. Considering the high performance polymer polyetherketoneketone (PEKK) with 2D filler (mica) composite as an example, the effects of filler size, filler content, surface chemistry and shear rate were systematically investigated. Here, it is demonstrated that the interaction between the polymer and 2D filler brings two different consequences on tuning the viscosity of polymer-filler composite. The stronger interaction increases the shear stress of the polymer-2D filler composite system, leading to higher viscosity. On the other hand, the stronger interaction can promote more absorption of polymer chains on the surface, which makes the local polymer network disentangled and decreases the continuous viscosity from the polymer network. This work provides a fundamental understanding on the relationship between macroscopic rheological properties and the structural properties and energetics at molecular level of polymer-2D filler composite.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Measure this, not that: Optimizing the cost and model-based information content of measurements

Model-based design of experiments (MBDoE) is a powerful framework for selecting and calibrating science-based mathematical models from data. Here, this work extends popular MBDoE workflows by proposing a convex mixed integer (non)linear programming (MINLP) to optimize the selection of measurements. The solver MindtPy is modified to support calculating the D-optimality objective and its gradient via an external package, scipy, using the grey-box module in Pyomo. The new approach is demonstrated in two case studies: estimating highly correlated kinetics from a batch reactor and estimating transport parameters in a large-scale rotary packed bed for CO 2 capture. Both case studies show how examining the Pareto optimal trade-offs between information content measured by A- and D-optimality versus measurement budget offers practical guidance for selecting measurements for scientific experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Mechanistic Insights into the Demethylation of Lignin‐Derived Structures Using Protic Ionic Liquids: A Density Functional Theory Study

Lignin valorization is restricted by the stability of its methoxy groups, creating a critical need for efficient demethylation strategies. Here, in this study, density functional theory (DFT) is employed to dissect the mechanistic pathways of demethylation in lignin model compounds, guaiacol and syringol, using protic ionic liquids (PILs) that act as both solvent and catalyst. Conductor‐like Screening Model for Real Solvents (COSMO‐RS) analysis identifies monoethanolammonium acetate ([MEOA][Ace]) as the most promising medium, attributed to its strong hydrogen bonding network and solvation ability. By integrating implicit and explicit solvation models, it is revealed that an acid‐catalyzed hydrolytic mechanism governs demethylation, with PILs stabilizing crucial transition states and intermediates. Complementary electronic structure evaluations, including highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO‐LUMO) gap analysis, charge distribution, and electrostatic potential mapping, demonstrate how PILs lower energetic barriers and enhance reactivity. To simulate realistic environments, this study is extended to lignin dimer complexes with varying water content, uncovering how water‐bridged solvation reverses demethylation preference from guaiacyl to syringyl units. This mechanistic shift aligns with experimental observations showing faster S‐unit reactivity in hydrated systems. Together, these findings provide atomic‐level insight into lignin demethylation dynamics and highlight how tuning acid concentration in PILs can accelerate kinetics, enabling a rational pathway toward next‐generation biomass conversion technologies.

COSMO-RS↗

DOE OSTI2025

AUTOIGNITION DELAY TIMES FOR REFORMATE GAS MIXTURES FROM METHANE GAS ENGINES

Methane slip is a prominent issue in natural gas reciprocating engines that are used in transportation and marine applications. The incomplete combustion that results in methane slip can be resolved with the introduction of hydrogen within the combustion mixture to improve methane oxidation and further enable combustion within the engine crevices where methane has previously remained unreacted. Steam methane reforming (SMR) is a common method used to produce hydrogen and can be used to design an onboard device to reduce methane slip from reciprocating engines. The development of this reformer device requires the validation of high-fidelity chemical kinetic models at the low temperatures of the crevice volumes of these engines. In this work, auto-ignition data is obtained using a shock tube at lean (φ—0.714 or λ—1.4) and stoichiometric (φ, λ = 1) equivalence ratios spanning a temperature range of 1042–1234 K at the 80-bar operating pressure of the test engine. Blends of methane, hydrogen, and reformate products from the SMR reaction are shock-heated in synthetic air, with the ignition delay time measured using an OH* chemiluminescence detector at 310 nm and a CH* detector at 430 nm. The experimental results are compared to several state-of-the-art chemical kinetic mechanisms from the literature. In general, most of the mechanisms show very good agreement with experiments at higher temperatures, with simulation results showing little deviation from experiments at lower temperatures. A sensitivity analysis was conducted, and the results reveal that the reaction H2 + CH3O2 = H + CH3O2H has a very significant role in determining low-temperature ignition delay times (IDTs) of SMR mixtures. These findings provide valuable insights into the chemical kinetics governing methane reformate combustion and contribute to the optimization of onboard reformer designs aimed at mitigating methane slip in natural gas-fueled engines.

Fraze, Matthew↗

DOE OSTI2023

Proximate spin liquid and fractionalization in the triangular antiferromagnet KYbSe 2

The Heisenberg triangular-lattice quantum spin liquid and its phase transitions to nearby magnetic orders have received much theoretical attention, but clear experimental manifestations of these states are rare. Here we demonstrate that a spin-half delafossite material, namely, KYbSe 2 , shows close proximity to the triangular-lattice Heisenberg quantum spin liquid. Using neutron scattering, we identify a diffuse continuum with a sharp lower bound within the measured spectra. Applying entanglement witnesses to the data indicates multipartite entanglement spread between its neighbours, and an analysis of its magnetic-exchange couplings reveals close proximity to the theoretical quantum spin-liquid phase. The key features of the data are reproduced by Schwinger boson theory and tensor network calculations with a substantial next-nearest-neighbour coupling. The strength of the dynamical structure factor at the Brillouin-zone K point shows a scaling collapse down to 0.3 K, indicating the existence of a second-order quantum phase transition. Finally, comparing this with previous theoretical work suggests that the proximate phase at a larger next-nearest-neighbour coupling is a gapped $\mathbb{Z}_{2}$ spin liquid, resolving a long-debated issue. Similar content being viewed by others

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Climate, soil mineralogy and mycorrhizal fungi influence soil organic matter fractions in eastern US temperate forests

Identifying the primary controls of particulate (POM) and mineral-associated organic matter (MAOM) content in soils is critical for determining future stocks of soil carbon (C) and nitrogen (N) across the globe. However, drivers of these soil organic matter fractions are likely to vary among ecosystems in response to climate, soil type and the composition of local biological communities. We tested how soil factors, climate and plant–fungal associations influenced the distribution and concentrations of C and N in MAOM and POM in seven temperate forests in the National Ecological Observatory Network (NEON) across the eastern United States. Samples of upper mineral horizon soil within each forest were collected in plots representing a gradient of dominant tree–mycorrhizal association, allowing us to test how plant and microbial communities influenced POM and MAOM across sites differing in climate and soil conditions. We found that concentrations of C and N in soil organic matter were primarily driven by soil mineralogy, but the relative abundance of MAOM versus POM C was strongly linked to plot-level mycorrhizal dominance. Furthermore, the effect of dominant tree mycorrhizal type on the distribution of N among POM and MAOM fractions was sensitive to local climate: in cooler sites, an increasing proportion of ectomycorrhizal-associated trees was associated with lower proportions of N in MAOM, but in warmer sites, we found the reverse. As an indicator of soil carbon age, we measured radiocarbon in the MAOM fraction but found that within and across sites, Δ 14 C was unrelated to mycorrhizal dominance, climate, or soil factors, suggesting that additional site-specific factors may be primary determinants of long-term SOM persistence. Our results indicate that while soil mineralogy primarily controls SOM C and N concentrations, the distribution of SOM among density fractions depends on the composition of vegetation and microbial communities, with these effects varying across sites with distinct climates. Here we also suggest that within biomes, the age of mineral-associated soil carbon is not clearly linked to the factors that control concentrations of MAOM C and N.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Superionic conduction using ion aggregates

Project objective: Engineer solid polymeric electrolytes with an optimized, self-assembled, ion network that conducts independently of polymer segmental dynamics. The goal of this project is to engineer an optimized, self-assembled ion aggregate network, by which we can incorporate an aggregate assisted, collective, superionic conduction paradigm into polymeric electrolytes. We do not seek to improve conductivity, although this is a likely result of our approach, but to propose systems in which collective motion is the main conduction mechanism. We believe that once such materials are identified, they will quickly become a subject of research in the solid polymer electrolyte community. With this in mind, we pursue three design strategies: increase ion content in PEG single ion conductors, use mixed anions (including divalent ions as crosslinkers), and introduce swelled polyanion/polycation complexes as a potential ion conducting material.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Thermal Properties of Sodium Borosilicate Glasses as a Function of Sulfur Content

SO3 additions, up to 3.0 wt%, were systematically investigated for effects on the physical properties of sodium borosilicate glass melted in air, with a sulfur-free composition of 50SiO2-10Al2O3-12B2O3-21Na2O-7CaO (wt%). Solubility measurements, using electron microscopy chemical analysis, determined the maximum loading to be ~1.5 wt% SO3. It was found that sulfur (here as sulfate) in this glass increased the glass transition temperature, thermal diffusivity, heat capacity, and thermal conductivity, and decreased the mass density. Structural analysis, performed with Raman spectroscopy, indicated that the borosilicate network polymerized with sulfur additions, presumably due to Na2O being required to charge compensate the ionic SO42- additions, thus becoming unavailable to form non-bridging oxygen in the silicate network. It is postulated that this increased crosslinking of the borosilicate backbone lead to a structure with higher dimensionality and average bond energy. This increased the mean free paths and vibration frequency of the phonons, which resulted in the observed increase in thermal properties.

Thermal properties, Borosilicate glass, Sulfur sol↗

DOE OSTI2023

Combining direct ink writing with reactive melt infiltration to create architectured thermoelectric legs

Here, we present a new additive-reactive synthesis method where inks – cast into molds or 3D-additively extruded into architectured shapes – are reacted into intermetallic thermoelectric compounds. The new method, as demonstrated for equiatomic TiNiSn, combines: (i) extrusion printing (or casting) of inks containing Ni and Ti powders, (ii) debinding and reactive sintering to form a porous NiTi network, (iii) network infiltration with liquid Sn and subsequent reaction to synthesize the TiNiSn phase. Thin plates, created through this method, show high phase purity and low residual porosity. A thermoelectric figure of merit zT = 0.47 ± 0.05 is achieved at 800 K, within the broad range of values (zT= 0.3–1.0) reported for TiNiSn created via traditional powder hot-pressing methods. Layered TiNiSn microlattices – after 3D ink-extrusion printing and infiltration – exhibit high relative densities and minimal undesirable secondary phase content, with a Seebeck coefficient on par with the ink-cast TiNiSn plates, demonstrating that thermoelectric legs with far-ranging architectural freedom can be created additively with this novel reactive manufacturing method. Numerous other thermoelectric (and other) compounds, currently limited to basic geometries due to brittleness, are amenable to this new method based on a sequence of reactive sintering/infiltration of cast or ink-extruded precursors.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Tunable thermoplastic elastomer gels derived from controlled-distribution triblock copolymers with crystallizable endblocks

Thermoplastic elastomers (TPEs), a commercially important category of triblock copolymers, are employed alone or upon physical modification with a midblock-selective oil (to form TPE gels, TPEGs) in a broad range of contemporary technologies. While most copolymers in this class of self-networking macromolecules possess glassy polystyrene endblocks and a rubbery polydiene or polyolefin midblock, we investigate TPEGs fabricated from a novel controlled-distribution copolymer with crystallizable polyolefin endblocks and a random-copolymer midblock. According to both electron microscopy and small-angle scattering, the morphologies of these TPEGs remain largely invariant up to 40 wt% oil and then transform considerably at higher oil levels. Although reductions in endblock melting point and crystallinity measured by thermal calorimetry accompany increasing oil content, mechanical properties such as the uniaxial strain at break and fracture toughness improve in some cases by over 50% between 5 and 40 wt% oil. In fact, the strain at break can reach 2500% within this range, thereby confirming that (i) the structure–property relationships of these unique TPEGs are highly composition-tunable and (ii) these TPEGs, stabilized by crystallizable endblocks, provide an attractive alternative for ultrasoft and stretchy recyclable materials.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Daily evapotranspiration changes during heatwaves at 32 NEON sites, 2019-2021

This dataset provides partitioned evapotranspiration (ET, the combined loss of water from soil and plant surfaces) anomalies during heatwave events—soil evaporation (E) and transpiration (T)—for 268 heatwave events across 32 National Ecological Observatory Network (NEON) flux sites in the contiguous United States from 2019–2021. Using an ensemble of four high-frequency turbulence methods (Flux-variance Similarity, Conditional Eddy Covariance [CEC], CEC with Water-Use Efficiency, and Conditional Eddy Accumulation; see Zahn and Bou-Zeid 2024), half-hourly transpiration-to-evapotranspiration (T/ET) ratios were derived from 20 hertz (Hz, cycles per second) eddy covariance measurements of carbon dioxide (CO₂) and water vapor (H₂O) concentrations. The dataset spans six vegetation types including evergreen and deciduous forests, grasslands, cultivated crops, shrublands, and emergent herbaceous wetlands. Data Package Contents: The dataset includes a single CSV (comma-separated values) file containing daily anomalies (deviations from baseline conditions) for transpiration (Delta_T), evaporation (Delta_E), total evapotranspiration (Delta_ET), and T/ET ratio (Delta_T_ET) during each day of identified heatwave events. The file also includes site codes, dates, heatwave event identifiers, and day-of-heatwave indicators. The CSV file can be opened with spreadsheet software (Microsoft Excel, Google Sheets) or programming environments (Python, R, MATLAB). This resource enables researchers to investigate ecosystem-specific responses to thermal extremes, validate land surface model partitioning of ET fluxes, and examine feedbacks between water cycling and surface energy balance during heatwaves. The dataset is particularly valuable for studies linking vegetation hydraulic strategies to climate resilience, as it captures the divergent responses of shallow-rooted versus deep-rooted ecosystems. Potential applications include improving drought early warning systems, informing irrigation management strategies, and advancing our mechanistic understanding of land-atmosphere interactions under extreme heat conditions.

Day of Heatwave↗

DOE OSTI2022

Dynamics of Glyceline and Interactions of Constituents: A Multitechnique NMR Study

In this work, the dynamics of the organic components of the deep eutectic solvent (DES) glyceline are analyzed using an array of complementary nuclear magnetic resonance (NMR) methods. Fast-Field Cycling 1 H relaxometry, Pulsed Field Gradient diffusion, Nuclear Overhauser Effect Spectroscopy (NOESY), 13 C NMR relaxation and pressure dependent NMR experiments are deployed to sample a range of frequencies and modes of motion of the glycerol and choline components of the DES. Generally, translational and rotational diffusion of glycerol are more rapid than those of choline while short range rotational motions observed from 13 C relaxation indicate slow local motion of glycerol at low choline chloride (ChCl) content. The rates of glycerol and choline local motions become more similar at higher ChCl. This result taken together with pressure dependent NMR studies show that the addition of ChCl makes it easier to disrupt glycerol packing. Finally, a relatively slow hydroxyl H-exchange process between glycerol and choline protons is deduced from the data. Consistent with this, NOESY results indicate relatively little direct H-bonding between glycerol and choline. These results suggest that the glycerol H-bonding network is disrupted as choline is added, but primarily in regions where there is intimate mixing of the two components. Thus, the local dynamics of most of the glycerol, resembles that of pure glycerol until substantial choline chloride is present.

13C NMR relaxation↗

DOE OSTI2024

Defect Production and Microstructural Feature Impact for Radiation Damage in Additively Manufactured 316 Stainless Steel

This milestone presents multi-scale modeling research results for additively manufactured 316 stainless steel. A combination of phase field, cluster dynamics, molecular dynamics, and density functional theory with machine learning is used, allowing for predictions of radiation-driven microstructural evolution in additively manufactured 316 stainless steel over a range of temperatures, damage rates, neutron spectra, and microstructures, and supporting the development of combined ion and neutron irradiation for material qualification. Informed by ion irradiation and neutron irradiation results across the Advanced Materials and Manufacturing Technologies program, we investigate the unique aspects of radiation-driven microstructure evolution in additively manufactured 316 stainless steel. In particular, we focus on understanding the impact of carbon concentration (varying, for example, between the 316L and 316H standards) on void formation; radiation-induced segregation at dislocation cells and grain boundaries; and the evolution of dislocation loops and network dislocation populations. We find that the unique characteristics of the additively manufactured microstructures must be accounted for in understanding the evolution of dislocation populations under thermal and irradiation conditions, such as the variation in sink strengths arising due to the variation in dislocation density. We also find that the radiation-induced segregation of Cr and Ni to grain boundaries and cell walls differs due to the differences in their defect sink biases. We also find that increasing the Ni content can slow vacancy diffusion, which may provide a mechanism for the observed reduction in transient swelling rate for austenitic Fe-Cr-Ni alloys with increasing Ni content. In addition, ion irradiations have shown that increasing carbon content in 316 SS results in a larger population of smaller voids, suggesting reduced vacancy diffusion. Our results show that the carbon content of additively manufactured 316 SS has a significant impact on the migration rate of defect clusters. The presence of carbon atoms results in carbon-vacancy trapping, significantly reducing the diffusion rate of vacancies. Carbon atoms may also be trapped near the surface of a void, which may reduce void growth by trapping vacancies that diffuse toward the void.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Oak Ridge Computing Academy: An HPC cluster deployment and management pilot

The High Performance Computing Technologies (HPCT) course is a hands-on High Performance Computing (HPC) cluster deployment and management training program offered as part of the International School for Advanced Studies (SISSA) and the International Center for Theoretical Physics (ICTP) Master in High Performance Computing (MHPC) specialization. Here, this training program introduces students to key concepts in cluster configuration. which include networking, software stack provisioning, job scheduling, and monitoring. The publicly available course materials feature several examples and underlying methods that are broadly applicable to cluster deployment and management. This paper discusses the design of a new workforce development program at the Oak Ridge National Laboratory that is based on HPCT, the Oak Ridge Computing Academy (ORCA). The ORCA pilot program was hosted by the Oak Ridge Leadership Computing Facility (OLCF) in Summer 2025. As a part of this discussion, HPCT and ORCA course contents and infrastructure are outlined, ORCA participant experiences are detailed, and potential opportunities for improvement are discussed.

Education↗

DOE OSTI2020

The landscape of disc outflows from black hole–neutron star mergers

ABSTRACT We investigate mass ejection from accretion discs formed in mergers of black holes (BHs) and neutron stars (NSs). The third observing run of the LIGO/Virgo interferometers provided BH–NS candidate events that yielded no electromagnetic (EM) counterparts. The broad range of disc configurations expected from BH–NS mergers motivates a thorough exploration of parameter space to improve EM signal predictions. Here we conduct 27 high-resolution, axisymmetric, long-term hydrodynamic simulations of the viscous evolution of BH accretion discs that include neutrino emission/absorption effects and post-processing with a nuclear reaction network. In the absence of magnetic fields, these simulations provide a lower limit to the fraction of the initial disc mass ejected. We find a nearly linear inverse dependence of this fraction on disc compactness (BH mass over initial disc radius). The dependence is related to the fraction of the disc mass accreted before the ouflow is launched, which depends on the disc position relative to the innermost stable circular orbit. We also characterize a trend of decreasing ejected fraction and decreasing lanthanide/actinide content with increasing disc mass at fixed BH mass. This trend results from a longer time to reach weak freezout and an increasingly dominant role of neutrino absorption at higher disc masses. We estimate the radioactive luminosity from the disc outflow alone available to power kilonovae over the range of configurations studied, finding a spread of two orders of magnitude. For most of the BH–NS parameter space, the disc outflow contribution is well below the kilonova mass upper limits for GW190814.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Identification of Novel Genomic Associations and Gene Candidates for Grain Starch Content in Sorghum

Starch accumulated in the endosperm of cereal grains as reserve energy for germination serves as a staple in human and animal nutrition. Unraveling genetic control for starch metabolism is important for breeding grains with high starch content. In this study, we used a sorghum association panel with 389 individuals and 141,557 single nucleotide polymorphisms (SNPs) to fit linear mixed models (LMM) for identifying genomic regions and potential candidate genes associated with starch content. Three associated genomic regions, one in chromosome (chr) 1 and two novel associations in chr-8, were identified using combination of LMM and Bayesian sparse LMM. All significant SNPs were located within protein coding genes, with SNPs ∼ 52 Mb of chr-8 encoding a Casperian strip membrane protein (CASP)-like protein (Sobic.008G111500) and a heat shock protein (HSP) 90 (Sobic.008G111600) that were highly expressed in reproductive tissues including within the embryo and endosperm. The HSP90 is a potential hub gene with gene network of 75 high-confidence first interactors that is enriched for five biochemical pathways including protein processing. The first interactors of HSP90 also showed high transcript abundance in reproductive tissues. The candidates of this study are likely involved in intricate metabolic pathways and represent candidate gene targets for source-sink activities and drought and heat stress tolerance during grain filling.

genomics↗

DOE OSTI2022

Nth-plant scenario for forest resources and short rotation woody crops: Biorefineries and depots in the contiguous US

Estimating the US potential of woody material is of vital importance to ensure cost-effective supply logistics and develop a sustainable bioenergy and bioproducts industry. We analyzed a mature conversion technology for woody resources for the contiguous US that takes advantage of economies of scale: the nth-plant. Here, we developed a database to quantify the total accessible woody biomass within a distributed network of preprocessing depots and biorefineries considering both quality specifications for conversion and a target cost to compete with fossil fuels. We considered two categories of woody biomass: 1) forest residues from trees, tops and limbs produced from conventional thinning and timber harvesting operations as well as non-timber tree removal; and 2) short rotation woody crops such as poplar, willow, pine, and eucalyptus. A mixed integer linear programming model was developed to analyze scenarios with woody feedstock blends at variable biomass ash contents and cost targets at the biorefinery. When considering a target cost of 85.51 dollars/dry ton (2016$) at the biorefinery, the maximum accessible biomass from forest residues in 2040 remained constant at 106 million dry tons regardless of ash targets. Including short rotation woody crops as part of the blend increased the total accessible biomass to 153 and 195 million dry tons at ash targets of 1% and 1.75%, respectively. We concluded from our analysis that woody resources could address about 55% of EPA’s (Environmental Protection Agency) target of 16 billion gallons of cellulosic biofuel.

09 BIOMASS FUELS↗