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Results for “Feedstock Variability”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In‐mold rheology and automated process control for injection molding of recycled polypropylene

Abstract Manufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock. Highlights Pressure‐controlled injection molding of recycled polypropylene. Automated closed‐loop adaptive process control methodology. Methodology resulted in a reduction in pressure variation during molding. Changes in mechanical properties and in‐mold viscosity were investigated. Results show the potential of pressure‐controlled molding at reducing variation.

Krantz, Joshua↗
DOE OSTI2023

Plant-wide modeling and techno-economic analysis of a direct non-oxidative methane dehydroaromatization process via conventional and microwave-assisted catalysis

Direct non-oxidative methane dehydroaromatization (DHA) process via conventional and microwave (MW)-assisted thermo-catalytic catalysis is studied. Rate models for methane DHA reactions, including the effect of catalyst deactivation, are developed by using the in-house experimental data. Model results for gas concentration profile and catalyst deactivation are in good agreement with the experimental data. This rate model is then used for the development of dynamic multi-scale, multi-physics commercial-scale reactor models. Total number of fixed bed reactors desired for a cyclic steady state process is estimated. Plant-wide models are then developed for conventional and MW-assisted processes for producing products of desired specifications. Techno-economic analysis of the methane DHA process is undertaken. Economics of these methane DHA processes are compared with the typical multi-step natural gas to aromatics production process via methanol synthesis. Sensitivity of internal rate of return (IRR) and net present value (NPV) to various economic and process parameters such as plant scale, desired rate of return, reactor cost, feedstock and utility cost, catalyst variable cost, and MW reactor cost is studied. Here, electric equivalent efficiency of the conventional methane DHA process is found to be 69.2 % and 67.3 % at 750 °C and 800 °C, respectively, while the MW-assisted methane DHA process has the electric equivalent efficiency of 48.9 % at 800 °C. IRRs of the conventional methane DHA process at 750 °C and 800 °C, and MW-assisted process are 15.2 %, 17.5 %, and 18.8 %, respectively for a methane feed flowrate of 19,782 kg/h, while the IRR of the multi-step natural gas to aromatics production process is estimated to be 0 % for the same plant scale. Impact of change in the methane price, electricity price, and catalyst cost is found to be considerable on the process economics, while the cost of the MW reactor is found to have negligible impact.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Polymer principles behind solubilizing lignin with organic cosolvents for bioenergy

Lignin solubilization is key to a viable biorefinery because its removal leads to facile deconstruction of biomass and because the isolated lignin can serve to derive precursors of novel high-value materials. The mixing of organic solvents with water has been shown to improve biomass fractionation and lignin conversion reactions. However, generally-applicable solubilization strategies are lacking because of the remarkable variability of lignin across plant feedstocks. Here, to obtain a predictive understanding of lignin solvation, we perform molecular dynamics simulations of model lignin polymers in two mixtures of water with polar aprotic solvents: tetrahydrofuran (THF) : water and γ-valerolactone (GVL) : water. The model lignins include H-, G- and S-only homopolymers and lignins with an S : G 1 : 1 ratio. We find that a well-established theory of self-avoiding polymers in a “good” solvent describes accurately the physical conformations of all types of lignin in both solvents. As the degree of methoxy substitution increases in the homopolymers, the distributions of the lignin radius of gyration and the Flory exponent ν , which describes the lignin-solvent interactions, do not change in THF : water, while ν shifts to slightly higher values in GVL : water. We attribute this increase to the interaction between the methyl group of GVL with the lignin methoxy groups. We also find that the reduction in the lignin radius of gyration due to branching is accurately described by the Zimm–Stockmayer theory for both THF : water and GVL : water. The above findings validate the applicability of polymer physics concepts to lignin and suggest that GVL : water may have the most favorable interaction with S-lignin, whereas the interactions of THF : water with lignin are independent of lignin monomeric content.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Report on Updated Properties Handbook of Printed Stainless Steel 316

This report focuses on summarizing mechanical behavior of 316H stainless steel (SS) printed using laser powder bed fusion (LPBF). 316H SS is one of the six alloys that has been qualified for use in nuclear reactors. The Advanced Materials and Manufacturing Technologies (AMMT) program has identified the use of the additive manufacturing (AM) process of LPBF as one of the manufacturing modalities to fabricate components for nuclear applications. Unlike wrought material, AM material displays significant heterogeneity in properties, resulting from changes in process parameters, machine-to-machine variability, and minor changes in feedstock chemistry from one batch to another. Although significant work has been done on 316L SS in the literature and has been summarized in several review papers, very limited data exist on 316H SS. Therefore, this report aims to provide a concise summary of the properties of 316H SS printed using different machines and at different locations as a part of the AMMT program.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanical Characterization of Loblolly Pine

Biorefineries are faced with various material flow challenges during feeding and handling, due to inherent variability and inhomogeneity of biomass feedstocks. This impacts the efficiency of refinery processes and unit operations. Proper characterization of bulk properties allows for optimal process design and reduction of overall costs. This work is aimed at evaluating the physical and mechanical properties that impact bulk flow of loblolly pine. Cyclic axial compression tests are performed to elucidate consolidation behavior under different stress conditions. The results are then used to develop correlations between material parameters (particle size, tissue type, moisture content) and Elastic Modulus of bulk samples.

09 BIOMASS FUELS↗
DOE OSTI2025

Understanding the impacts of inorganic species in woody biomass for preprocessing and pyrolysis–A review

Woody biomass represents an abundant resource for sustainable biofuels, biochemicals, and bioproducts. Technologies for converting woody biomass have been established for decades, and research consistently highlights the critical role of inorganic species and ash plays in feedstock handling and conversion processes, including equipment plugging, corrosion, and catalyst deactivation. A thorough understanding of the variability, transport behavior, and downstream impact of inorganic species in woody biomass is essential for defining feedstock quality specifications and developing effective management strategies for conversion processes. This review compiles critical information in five main sections: 1) inorganic species concentration in woody biomass, based on anatomical fractions and their sources of variability; 2) technique features for quantifying inorganic elemental chemical analysis; 3) impacts of inorganic species on biomass preprocessing; 4) impacts of inorganic species on pyrolysis, and 5) mitigation strategies. Additionally, this review explores future challenges and opportunities in addressing the impacts of inorganic species on biomass quality. These insights aim to support the sustainable development of the biomass-to-bioenergy pipeline and ensure high-quality lignocellulosic feedstocks for efficient downstream conversions. The findings offer valuable guidance to policy makers, industry stakeholders, and researchers in developing effective strategies for managing inorganic species in woody biomass and fostering the sustainable processes for lignocellulosic biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2025

Recovery of postconsumer mechanically recycled polymers

Mechanical recycling plays a key role in reducing landfill bound plastics that pollute our environment. This process converts plastic waste into marketable pellets by sorting, cleaning, grinding into flakes, compounding in the molten state, and ultimately pelletizing. A primary restriction for the widescale usage of mechanical recycling is the highly variable quality and mechanical properties of the plastic waste feedstock. Degradation can occur during the plastic life cycle with the consumer, during the mechanical processing itself, or during the complex sorting process required to produce the feedstock. This study explores how rheological characterization can mitigate the batch-to-batch variability and identify a potential application for each batch. Shear and extensional rheology of “application-specific” virgin high-density polyethylene (HDPE) and virgin polypropylene (PP) was used as the control for this categorization process. Recycled HDPE and PP from three different streams were then measured and compared to the results from the control study. Rheological measurements proved to be very effective at providing sufficient differentiation to categorize the recycled polymer as suitable for different applications such as injection molding, blow molding, or thermoforming. Finally, the usage of an additional step to sort the recycled polymers by their initial use application was found to achieve a remarkably consistent recovery of application-specific material properties. Furthermore, this secondary sorting could provide significant added value for mechanically recycled polymers.

Differential scanning calorimetry↗
DOE OSTI2022

Intra‐ and inter‐annual variability of nitrification in the rhizosphere of field‐grown bioenergy sorghum

Abstract Biological nitrification inhibition (BNI) and plant–microbe competition for ammonium (NH 4 + ) by sorghum ( Sorghum bicolor (L.) Moench) have the potential to suppress nitrification, reducing nitrate (NO 3 − ) and nitrous oxide (N 2 O) production for more sustainable bioenergy feedstock production. However, it is unknown how variability in environmental factors, field management, and plant growth affect the suppression of nitrification. We conducted a field trial with four genotypes of energy sorghum and four fertilization rates in central Illinois, USA, and measured soil N pools, potential nitrification and denitrification rates, and microbial community composition in bulk and rhizosphere soils to assess nitrification suppression throughout the 2018 and 2019 growing seasons. Concentrations of NO 3 − and NH 4 + were very low in rhizosphere soil regardless of fertilization level, suggesting strong N demand by plants and microbes. Potential nitrification was lower in the rhizosphere soil than bulk soil, and this suppression was strongest mid‐season ~2 months after planting in both years (20% suppression in 2018 and 58% in 2019). Since precipitation was lower during the mid‐growing season of 2019 compared to 2018, we speculate that hydrophilic BNI root exudates accumulated in the rhizosphere and suppressed nitrification more than in 2018 when soil moisture was higher. Unfertilized plots had greater nitrification suppression than fertilized plots during the mid‐season in 2018, but otherwise nitrification suppression was insensitive to fertilizer treatment. Potential denitrification was stimulated in the rhizosphere compared to bulk soil in both study years, suggesting that heterotrophic activity was stimulated by plant carbon inputs, possibly further suppressing slower‐growing chemoautotrophic nitrifying microbes. Overall, we found inter‐ and intra‐annual variation in nitrification suppression in the rhizosphere of field‐grown biomass sorghum, suggesting that plant phenology and environmental conditions should be considered when devising strategies to improve the nitrogen sustainability of this annual bioenergy crop.

09 BIOMASS FUELS↗
DOE OSTI2026

Computational methods in solution-based plastics purification

Plastic waste can be recycled into resins with near-virgin properties by solution-based purification processes that selectively dissolve polymers, remove contaminants, or detach printing residues. Here, in this review, we examine computational methods for predicting the behavior governing solution-based plastic purification, motivated by the vast polymer–solvent–contaminant compositional space. We discuss thermodynamic and machine learning methods for predicting polymer–solvent and polymer–contaminant interaction and review physics-based molecular dynamics simulations that resolve molecular-scale phenomena within polymer matrices inaccessible to screening methods. We highlight how these methods have informed experimental design for dissolution-based recycling and solvent-based contaminant removal. Finally, we discuss the prospective role of agentic AI in integrating these computational tools with real-time sorting data to adapt purification conditions to the compositional variability of real post-consumer feedstocks. This review charts a path toward computationally guided solution-based purification workflows that can respond to the complexity inherent in plastic waste streams.

Altamimi, Ali [Univ. of Wisconsin, Madison, WI (Un↗
DOE OSTI2024

Integrating Experiments, Simulations, and Artificial Intelligence to Accelerate the Discovery of High-Performance Green Composites

The imperative for incorporating greener materials into the aerospace industry necessitates addressing significant challenges associated with the microstructural variability exhibited by recycled and sustainable feedstocks. In this study, we propose an integrated methodology that combines experimental investigations, finite element analysis, and artificial intelligence to develop sustainable composites with consistent properties. Our approach utilizes a pipeline comprising an automated mechanical tester, a finite element method simulator, and a convolutional neural network predictor to identify and optimize fabrication parameters for achieving desired mechanical characteristics in composites. By employing a nested-loop pipeline, our methodology improves sample efficiency, accuracy, and effectively bridges the gap between simulations and real-world performance. This unique methodology offers a promising avenue for facilitating the adoption of aerospace-appropriate green composites.

Athanasiou, Christos↗
DOE OSTI2022

Key environmental and production factors for understanding variation in switchgrass chemical attributes

Abstract Switchgrass ( Panicum virgatum L.) is a promising feedstock for bioenergy and bioproducts; however, its inherent variability in chemical attributes creates challenges for uniform conversion efficiencies and product quality. It is necessary to understand the range of variation and factors (i.e., field management, environmental) influencing chemical attributes for process improvement and risk assessment. The objectives of this study were to (1) examine the impact of nitrogen fertilizer application rate, year, and location on switchgrass chemical attributes, (2) examine the relationships among chemical attributes, weather and soil data, and (3) develop models to predict chemical attributes using environmental factors. Switchgrass samples from a field study spanning four locations including upland cultivars, one location including a lowland cultivar, and between three and six harvest years were assessed for glucan, xylan, lignin, volatiles, carbon, nitrogen, and ash concentrations. Using variance estimation, location/cultivar, nitrogen application rate, and year explained 65%–96% of the variation for switchgrass chemical attributes. Location/cultivar × year interaction was a significant factor for all chemical attributes indicating environmental‐based influences. Nitrogen rate was less influential. Production variables and environmental conditions occurring during the switchgrass field trials were used to successfully predict chemical attributes using linear regression models. Upland switchgrass results highlight the complexity in plant responses to growing conditions because all production and environmental variables had strong relationships with one or more chemical attributes. Lowland switchgrass was limited to observations of year‐to‐year environmental variability and nitrogen application rate. All explanatory variable categories were important for lowland switchgrass models but stand age and precipitation relationships were particularly strong. The relationships found in this study can be used to understand spatial and temporal variation in switchgrass chemical attributes. The ability to predict chemical attributes critical for conversion processes in a geospatial/temporal manner would provide state‐of‐the‐art knowledge for risk assessment in the bioenergy and bioproducts industry.

09 BIOMASS FUELS↗
DOE OSTI2025

Environmental Metrics of Ethanol Production Improve with Increased Biomass Yield and Carbohydrate Content in Populus Trichocarpa

When selecting economically and environmentally advantageous genotypes for domestication in a biofuel supply chain, variability of cell-wall composition within a feedstock population and its impact on biorefinery metrics must be understood. We performed a life cycle assessment (LCA) on a poplar-to-ethanol supply chain to quantify global warming potential and cumulative energy demand as affected by variable carbohydrate content in a large representative natural variant population of Populus trichocarpa. The results showed that both environmental metrics decrease with increasing tree size and with increasing biomass carbohydrate content. These trends parallel prior economic results and provide clear direction to breeders or genetic engineers when improving poplar cultivars.

09 BIOMASS FUELS↗
DOE OSTI2026

Final Report: Process Intensification of Hydrogen Production through Sorption-Enhanced Gasification of Biomass

The University of Utah, in partnership with Idaho National Laboratory (INL), evaluated Sorption-Enhanced Gasification (SEG) as a transformative pathway for producing hydrogen with the potential for negative CO 2 emissions. SEG integrates gasification, water-gas shift, and in-situ carbon capture within a dual fluidized bed reactor to enable efficient clean hydrogen production. Key challenges related to biomass variability and process complexity were addressed through feedstock engineering, reaction optimization, and process validation. A co-pelletized biomass–limestone feedstock was developed to simplify feeding and introduction of makeup limestone. Kinetic and sorbent studies identified optimal operating conditions and confirmed the suitability of low-cost limestone, while catalysts were developed to reduce tar formation. Reactor modeling and techno-economic analysis indicated that SEG can achieve competitive hydrogen production costs, particularly when combined with carbon incentives, supporting its potential for scale-up and carbon-negative operation.

08 HYDROGEN↗
DOE OSTI2026

Evidence for carbon dioxide removal via enhanced rock weathering with steel slag, though not basalt, in a midwestern U.S. field trial

Enhanced weathering is an emergent pathway for permanent atmospheric carbon dioxide removal (CDR). However, despite a dramatic increase in academic and commercial research, there remain relatively few published examples of field evidence demonstrating the effectiveness of enhanced weathering. Here, we present results from a three-year field trial that evaluated steel slag and crushed basalt applied as amendments in a conventional agricultural system in the Midwestern United States. Steel slag applied to initially acidic soil increased porewater pH and alkalinity and increased soil pH and Ca-saturation. Together, changes in porewater chemistry and soil properties provide strong evidence for steel slag weathering and CDR. However, steel slag applied to soils with a neutral initial pH did not generate significant changes in soil or porewater chemistry. In addition, coarse-grained crushed basalt did not generate significant change in any of the soils. Strong acid effects were apparent in all 3 years of monitoring soil porewater chemistry. Overall, our results demonstrate clear evidence of CDR from applying steel slag amendments to acidic cropland soils while also highlighting the difficulty of greenhouse gas reduction accounting from enhanced weathering and the variable outcomes that can occur depending on feedstock and soil type.

Geosciences↗
DOE OSTI2024

A Novel Framework to Evaluate the Costs and Potential of Bioenergy in Decarbonization of the U.S. Economy

The long-term strategy of the United States targets reaching economy-wide net-zero emissions by 2050 and a carbon-neutral electricity grid by 2035 (U.S. Department of State and U.S. Executive Office of the President, 2021). Meeting these targets would require considerable changes to the energy system. Some key characteristics of illustrative net-zero energy systems include increased penetration of renewable energy and carbon sources, use of CO2 capture and storage (CCS) in hard-to-abate sectors, and a greater role for energy carriers such as electricity and hydrogen (Davis et al, 2018). Another common feature of such energy systems is the need for carbon dioxide removal (CDR) approaches (Horowitz et al, 2022). Across all these characteristics of net-zero energy systems, bioenergy and biomass feedstock is anticipated to play an important role. Biomass feedstock serves as a renewable carbon source. This can enable conversion of such feedstock into fuels and energy carriers for hard-to-abate sectors such as aviation. Indeed, the U.S. Government has a target to meet all jet fuel demand by 2050 from sustainable aviation fuel (SAF), where biofuel pathways are likely to have an important role (EERE, 2020). Bioenergy is also highly versatile with the possibility to convert feedstock into electricity, hydrogen, liquid fuels, heat or high-value products, based on biomass type, demand and technology availability (Clarke et al, 2022). Combination of bioenergy with CCS can also nominally deliver CDR (Fuhrman et al, 2023). As such, the share of bioenergy is expected to grow by at least five time across scenarios studied for the long-term strategy of the U.S. between 2020 and 2050 (Horowitz et al, 2022). Notwithstanding the role of bioenergy in the energy systems, its deployment, costs and scalability are influenced by a number of factors. Some of these factors pertain to policy interventions such as imposition of a binding decarbonization target either at an economy-wide level or the sectoral level. Resource availability and type of biomass feedstock also varies considerably across regions. From a technological perspective, the readiness of bioenergy conversion pathways is subject to high variability. This influences the costs of deployment. Moreover, the sourcing of feedstock, grid carbon intensity, and co-product handling approaches all affect the life cycle efficacy of bioenergy. The latter, in turn, is particularly important in determining the extent to which bioenergy with CCS or BECCS can effectively deliver CDR (Fajardy and Mac Dowell, 2017).

air emission↗
DOE OSTI2024

Woody Feedstock 2022 State of Technology Report

The U.S. Department of Energy promotes production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement in this mission, Idaho National Laboratory completes an annual SOT report for n th -plant and 1 st -plant woody biomass feedstock logistics. The purpose of the SOT is to provide the status of feedstock supply system technology development for woody biomass to biofuels relative to technical targets and cost goals from specific design cases, based on data and experimental results. Conventional feedstock supply systems need to be modified to meet the demands of conversion pathways, specifically to have the ability to adjust the quality of the raw biomass materials. Advanced systems incorporate innovative methods of material handling, preprocessing and supply chain configuration. In advanced designs, variability of the raw biomass can be reduced to produce feedstocks of a uniform format, moving toward biomass commoditization. Against this backdrop, the 2022 Woody SOT for low-ash woody feedstocks utilizes feedstock fractionation by incorporating technologies that can separate the biomass into its anatomical fractions (wood, bark, needle, and extrinsic ash) to reduce impurities and attempt to maximize the retention of usable fractions that satisfy downstream quality considerations. By using a series of air classification steps, this strategy can reduce the extrinsic ash in forest residues, separate out a majority of the incoming needles (which can be supplied to alternate markets), and maximize the retention of whitewood in the usable fraction. The fractionated forest residues are then mixed with clean-pine chips in a 50-50 blend to prepare the feedstock for the desired conversion pathway. The n th -plant analysis estimated the delivered cost for the feedstock at $\$$69.23/dry ton (2016$\$$) which represents a $\$$6.64/dry ton decrease compared to the cost estimate of the 2021 Woody SOT supply system for low-ash woody feedstocks. The quality requirements in the 2022 Woody SOT were identical to those of the 2021 Woody SOT at = 1.00 wt % ash and = 50.51 wt% carbon. The cost savings derive primarily from reductions in dry matter losses during air classification. The GHG emissions for the n th -plant analysis were estimated at 178.39 kg CO2e/dry ton compared to 178.71 kg CO 2 e/dry ton in the 2021 Woody SOT, a decrease of 0.32 kg CO2e/dry ton. The small change stems from an increase in emissions attributed to preprocessing and slightly larger savings in emissions from transportation. In the 1 st -plant analysis of the 2022 Woody SOT system, the average throughput was estimated to be approximately 2,128 dry tons/day or 96.51% of the name plate capacity. During the simulation the daily throughput ranged from 1,090 dry tons/day to 2,200 dry tons/day, or 49.43% to 99.75% of the daily nameplate capacity. After the year of operation 722,403 tons of processed feedstock were produced in total without regard to quality considerations (99.64% of the annual nameplate capacity). The variability in throughput was primarily caused by equipment failures in the system. Regular failures, downtime caused by routine maintenance per manufacturer guidelines, contributed to a majority 62.50% of failures and 62.60% of downtime. Failures due to wear were the other cause of disruption within the system, impacting the rotary shear and orbital screen and accounting for 37.50% of the failures and 37.40% of the total downtime. Ultimately the system was on stream for 87.84% during the simulation period, which is only 2.16 percentage points below the nth-plant assumption for on-stream time. The production cost of the system averaged $\$$71.66/dry ton. The costs ranged from a minimum of $\$$71.23/dry ton to a maximum of $\$$2,115.30/dry ton. When dry matter losses (disposed low-quality fractions as well as other losses such as in grinders) were considered the costs increased to an average of $\$$75.11/dry ton with a minimum of $\$$74.69/dry ton and a maximum of $\$$2,136.86/dry ton...

09 BIOMASS FUELS↗