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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 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 OSTI2021

Transport of Compressed Woody Biomass: Correlating Rheology and Microcompounder Measurements

Transport of milled solid biomass can be problematic in biomass conversion processes due to the material’s high cohesiveness, low bulk density, and poor flowability. Here, the goal is to investigate the flow behavior of compressed biomass under conditions similar to compression-screw feeders. To mimic the flow of woody biomass inside a compression-screw feeder, two lignocellulosic biomass feedstocks were fed to a co-rotating twin-screw microcompounder. Force and screw speed from the microcompounder were correlated to viscosity in a traditional rheometer, where low-density polyethylene served as a control. The deformation of compressed biomass in a lab-scale compounder is strongly dependent on screw speed and moisture content. Shear stress in woody biomass decreased with the shear rate, indicating negative plastic viscosity. Moreover, viscosity decreased one order of magnitude as screw speed increased from 10 to 90 rpm. Increasing moisture from 10 to 50% reduced the viscosity of the compressed biomass by 60%.

09 BIOMASS FUELS↗
DOE OSTI2023

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP): 2022 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at NREL and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts and driven by data furnished by Arizona State University's (ASU's) Arizona Center for Algae Technology and Innovation (AzCATI) test bed site. The CAP model is primarily based on experimental efforts conducted under NREL research and development projects, with some process parameters provided by partner organizations. Assumptions regarding the wet storage of algae use data provided by Idaho National Laboratory (INL), while parts of the polyurethane production process leverage BETO-funded research from collaborators at Algenesis and the University of California, San Diego (UCSD). This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2022 updates to minimum fuel selling price (MFSP). This update incorporates improvements to fermentation performance for two biological pathways through carboxylic acid and 2,3-butanediol (BDO) intermediates, as demonstrated through parallel research on the biochemical conversion of corn stover. Improvements are applied to the glucose fraction of the biomass only, while parameters regarding the conversion of the mannose fraction (not a significant component in corn stover) are maintained consistently with prior CAP SOTs. Additional parameters are also updated to reflect the most current understanding of each pathway, including an increase in the catalyst loading requirement in the ketonization step of the acids pathway and a decrease in the fermentation productivity in the BDO pathway. Additionally, the biomass feedstock costs (minimum biomass selling price [MBSP]), yields, and seasonal variability from the upstream cultivation SOT model were also incorporated into downstream Aspen Plus CAP models.

09 BIOMASS FUELS↗
DOE OSTI2024

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends with Washed and Unwashed Legacy Coals and Other Waste Fuels to Generate White Hydrogen

The objective of this effort, primarily funded by the United States Department of Energy (DOE), and led by the Electric Power Research Institute, Inc. (EPRI), with support by Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), has been to qualify coal, biomass, and plastic waste blends based on performance testing of selected fuel pellet compositions in a pilot-scale updraft moving-bed (UDMB) gasifier. The testing provided relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are the focus. The gasifier used for testing is HMI’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips (biomass). However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The three feedstocks were densified and pelletized by California Pellet Mill (CPM) to meet the feedstock size required by Sotacarbo’s 30mm ID UDMB gasifier, under contract to HMI. The technical tasks and results from this two-year research project included: (1) Feed Procurement and Preparation: Nine different tri-fuel pellets were prepared from varying compositions of fresh mined PRB coal, corn stover biomass, and car fluff waste plastics. Tri-fuel pellets were produced by CPM and shipped to Sotacarbo’s test facility in Carbonia, Sardinia, Italy. (2) Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different UDMB gasification tests to be performed in Sotacarbo’s 12-inch ID pilot scale gasifier, the process monitoring instrumentation used, and the extractive samples recovered for analysis of the total gasification process mass and energy balance. (3) Gasifier Testing: Nine different gasification runs were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstock compositions generated from varying mixtures of PRB coal, biomass, and plastic wastes. The testing generated performance data on gasification reaction efficiency and performance, yielding relevant data for models used to scale up the gasifier design. This task also included work to refurbish and reassemble the pilot gasifier at Sotacarbo and perform a baseline 100% PRB coal run. (4) Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results are reported in the project’s final report, published in March 2024. The results show that all tri-fuel pellets gasified well and maintained structural integrity throughout the gasification process. The syngas generated can be shifted to hydrogen by using commercial syngas shifting technologies. (5) High Fidelity computational fluid dynamics (CFD) Simulation: The National Energy Technology Laboratory (NETL) team performed CFD simulations of the UDMB gasifier for two of the tri-fuel pellets gasified in Sotacarbo’s pilot scale gasifier. The kinetic mechanisms for the pyrolysis of each constituent, PRB coal, corn stover biomass, and waste plastics are based on thermogravimetric analysis performed by Sotacarbo. The gasification model was validated by comparing the predicted syngas composition at the exit of the gasifier with the measured syngas composition. In addition, the reactor’s measured internal temperature profile agreed well with the predicted internal reactor temperature profile. These results validate that the model can be used to predict the performance of the updraft moving bed gasifier for different feedstocks and operating conditions. This paper summarizes the results of the completed work in which the pelletizing procedure was validated to ensure the viability of the tri-fuel pellets for the gasification runs performed at Sotacarbo’s 30 mm UDMB gasifier. The gasification performance data from this series of nine runs will enable modeling of a full-scale HMI industrial scale gasifier supporting both combined heat and power, and Hydrogen production from coal (both fresh mined and legacy) combined with various biomass and waste plastics. Additionally, plans and progress on a follow-up project, being executed by the same project team, will be presented. In this project, a total of twenty (20) different feedstocks are being prepared from varying compositions of biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste, and refuse-derived fuel (RDF). The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design to 50 megawatt electric (MWe) (equivalent hydrogen production). Tests will also be performed on a bench-scale fluidized-bed gasifier for comparison purposes. The results of this testing will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends.

08 HYDROGEN↗
DOE OSTI2023

Belowground Biomass and Root:Shoot Ratios of Three Willow Cultivars at Two Sites

Belowground biomass is an important but less studied component of energy crop systems that is essential in understanding the greenhouse gas benefits of these systems. In this study, a complete above- and belowground biomass inventory (foliage, stems, stools, coarse and fine roots) was performed on three cultivars of short-rotation willow biomass crops at two sites. Mixed models were used to analyze the proportion of biomass allocated to each component and the ratios between different components. The root:shoot (R:S) ratio, defined here as the stable unharvested biomass (stool and coarse roots) divided by the shoot biomass, averaged 0.63 (SE: +0.04). Though the portion of the plant where the willows distributed their belowground biomass varied, the R:S ratio was not significantly different across sites (p = 0.8970), cultivars (p = 0.2834), nor in the site × cultivar interaction (p = 0.8481). These results may be associated with the consistently good growth across sites and limited differences in site conditions. However, the R:S ratios were affected by the overall productivity of the stand (p = 0.0978), with higher producing stands having moderately lower ratios. This information on biomass allocation between components is essential for understanding and estimating the carbon balance of these systems and breeding and selection programs.

09 BIOMASS FUELS↗
DOE OSTI2021

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid analysis of biomass cell wall composition and typically require the use of different data analysis tools depending on the need and application. Here, the authors report the py-MBMS analysis of several types of lignocellulosic biomass to gain an understanding of spectral patterns and variation with associated biomass composition and use machine learning approaches to classify, differentiate, and predict biomass types on the basis of py-MBMS spectra. Py-MBMS spectra were also corrected for instrumental variance using generalized linear modeling (GLM) based on the use of select ions relative abundances as spike-in controls. Machine learning classification algorithms e.g., random forest, k-nearest neighbor, decision tree, Gaussian Naïve Bayes, gradient boosting, and multilayer perceptron classifiers were used. The k-nearest neighbors (k-NN) classifier generally performed the best for classifications using raw spectral data, and the decision tree classifier performed the worst. After normalization of spectra to account for instrumental variance, all the classifiers had comparable and generally acceptable performance for predicting the biomass types, although the k-NN and decision tree classifiers were not as accurate for prediction of specific sample types. Gaussian Naïve Bayes (GNB) and extreme gradient boosting (XGB) classifiers performed better than the k-NN and the decision tree classifiers for the prediction of biomass mixtures. The data analysis workflow reported here could be applied and extended for comparison of biomass samples of varying types, species, phenotypes, and/or genotypes or subjected to different treatments, environments, etc. to further elucidate the sources of spectral variance, patterns, and to infer compositional information based on spectral analysis, particularly for analysis of data without a priori knowledge of the feedstock composition or identity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Roles of mineral matter in biomass processing to biofuels

Abstract Minerals in biomass have a significant impact on both biofuel quality and yield. This is especially true for current thermochemical biomass conversion processes. However, the roles of plant minerals in biochemical conversion have not been studied extensively, even though they are generally considered to lower the sugar yield because they reduce the feedstock proportion of carbohydrates. A successful strategic solution is thus necessary to overcome the challenges caused by the minerals in biomass, which include (1) decreased quality of biomass feedstocks; (2) reduction of process efficiency; and (3) reduction of the product quality and quantity from biomass conversion. This review summarizes the roles of plant minerals in a biorefinery, focusing on these key challenges. The discussion covers many issues related to plant minerals in biofuel production, including their sources, functions, and distribution in plant biomass, methods of characterizing them, their influence in a biorefinery, and the strategic handling required to manage their occurrence in biomass, based on reported studies. It could inspire better strategies to deal with the variance of mineral content in biomass feedstocks to increase process efficiency and reduce costs while supporting the concept of a circular bioeconomy. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2022

Oxygen stress mitigation for microalgal biomass productivity improvement in outdoor raceway ponds

Dissolved oxygen (DO) concentrations at supersaturated levels are commonly observed in outdoor microalgae cultures due to photosynthesis during periods of rapid growth. Paradoxically, the photosynthetically generated oxygen is inhibitory and lowers biomass productivity, therefore, increasing the cost of microalgal biofuels. In this study, photosynthetic rates of Monoraphidium minutum 26B-AM and Scenedesmus obliquus UTEX393, two of the top DISCOVR strains, were compared at three DO levels, 0, 8, and 30 mg L -1 . Increasing DO from 0 to 30 mg L -1 caused a 36.6% and 26.1% reduction in photosynthetic rate for M. minutum 26B-AM and S. obliquus UTEX393, respectively. To improve the outdoor pond biomass productivity of each strain, three oxygen stress mitigation methods were tested. The first method raised the dissolved bicarbonate concentration by an order of magnitude to favor bicarbonate transport into the cell, increasing the CO 2 :O 2 ratio near RuBisCO, thus reducing photorespiration. Although this method increased the observed photosynthesis rate of M. minutum 26B-AM by 26% and S. obliquus UTEX393 by 13% in laboratory testing, it failed to improve biomass productivity under outdoor pond conditions for both strains. The second method added sodium sulfite as an oxygen scavenger to chemically lower the DO concentration in the culture. Chemical reduction of dissolved molecular oxygen did not significantly improve the biomass productivity of M. minutum 26B-AM; however, a 10% improvement in biomass productivity for S. obliquus UTEX393 was observed. The final method sparged cultures with air to strip oxygen out of the liquid medium. This did not improve the biomass productivity of M. minutum 26B-AM, likely due to unfavorable weather conditions during cold season cultivation; however, an improvement of 36% in biomass productivity was achieved for S. obliquus UTEX393 during the warm season cultivation. Of the three tested methods, air-sparging was the most effective and practical for improving outdoor biomass production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Life cycle assessment of co-firing biomass at coal-fired power plants with carbon capture and storage toward net-zero emissions

Co-firing biomass with carbon capture and storage (BECCS) offers a technological option to decarbonize coal-fired power plants toward net-zero emissions. This study estimates the life cycle emissions of co-firing biomass at coal-fired power plants with CCS and quantifies its variability and uncertainty. Deployment of co-firing BECCS at coal-fired power plants can significantly reduce the life cycle emissions toward the net-zero target but lower the power plant performance, which vary with numerous factors, including coal type, biomass type, co-firing level, and CO 2 capture rate. The breakeven co-firing levels required for biomass at coal-fired power plants with 90 % CO 2 capture to reach net-zero emissions fall with a range roughly from 15 % to 25 % on an energy basis, depending on coal and biomass types. Increasing the CO 2 capture rate from 90 % to 95 % can lower the breakeven co-firing levels by about 5 to 8 percentage points for the biomass resources of interest, which can lower reliance on biomass resources and facilitate large-scale deployment of co-firing BECCS in fossil-rich regions but with limited biomass resources. Furthermore, findings improve the understanding of the techno-environmental performance of co-firing BECCS and inform strategic planning decisions on net-zero emissions in the coal-fired power sector.

Breakeven co-firing level↗
DOE OSTI2020

Anaerobic Storage and Conversion of Microalgal Biomass to Manage Seasonal Variation in Cultivation

Seasonal variation in microalgal biomass production is a well-known challenge when optimizing economics for algal fuel conversion, especially given the fluctuation in biomass production between winter and summer. Wet storage offers significant potential for cost and energy savings compared to dewatering and dry storage. This study demonstrates the feasibility of preserving harvested Scenedesmus acutus biomass through wet anaerobic storage for use in biochemical conversion. Anaerobic storage effectively preserved biomass with minimal degradation of carbohydrates and preservation of lipids and proteins. Screening experiments identified optimal pretreatment conditions for stored biomass. Scale-up of pretreatment enabled fermentation of the hydrolysate to butyric acid and indicated no observable difference in conversion between unstored and stored biomass. Lipid extraction improved by a relative 12% for stored biomass. These results suggest that wet anaerobic storage can effectively manage seasonal variation in biomass production and is compatible with biochemical approaches for biofuel production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

ACS Sustainable Chemistry & Engineering Virtual Special Issue on Recent Advances in Biomass Characterization and Modeling

Recognizing the importance of biomass characterization and modeling, a virtual special issue (VSI) entitled Recent Advances in Biomass Characterization and Modeling was organized to showcase the recent contributions to this emerging field. This VSI features contributions from leading scientists in the biorefinery field, intending to provide the readers with the latest advances in analytical methodology and modeling to characterize biomass feedstocks and biomass-derived products. Further, the VSI contains perspectives and research articles. Advanced analytical methods that measure the mechanical, chemical, physical, biological, and other properties of biomass and biomass pyrolysis products are described along with their application’s limitations in two perspectives. Biomass is a multicomponent/multiscale, complex, nonconducting, and highly heterogeneous material; thus, it could be problematic for many characterization techniques. Traditional biomass analysis tools that are slow, laborious, and generally require harsh reagents have been replaced or supplemented by simpler and more rapid chromatographic and spectroscopic approaches such as GC-MS, HPLC, FTIR, Raman, and NMR spectroscopies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Production of carotenoids from aromatics and pretreated lignocellulosic biomass by Novosphingobium aromaticivorans

ABSTRACT Carotenoids are lipophilic compounds found in the membranes of various organisms. Individual carotenoids are also commodity chemicals, produced industrially for use as food additives, nutritional supplements, cosmetics, and pharmaceuticals. The alphaproteobacterium Novosphingobium aromaticivorans has previously been established as a potential platform microbe for converting aromatic compounds derived from lignocellulosic plant biomass into valuable extracellular products. Here, we show that N. aromaticivorans DSM 12444 cells naturally produce the carotenoid nostoxanthin, and we construct a set of gene deletion mutants that accumulate β-carotene, lycopene, or zeaxanthin, which are predicted intermediates in nostoxanthin biosynthesis as well as commodity chemicals. We also show that a mutant strain heterologously expressing a CrtW protein accumulates the carotenoid astaxanthin. When grown on vanillate as the carbon source, we find that the levels of carotenoids are not significantly affected by O 2 concentration in the tested range of 5% to 21% O 2 . We also show that these carotenoids are produced at comparable levels when strains are grown in liquor from alkaline pretreated sorghum biomass [sorghum alkaline pretreatment liquor (APL)], which contains a mixture of aromatics. Finally, we construct strains that produce zeaxanthin, β-carotene, or astaxanthin concurrently with 2-pyrone-4,6-dicarboxylic acid, a potential building block for biodegradable polymers, when grown in sorghum APL. Combined, our results show that N. aromaticivorans can simultaneously produce valuable intracellular and extracellular commodities when grown in the presence of either pure aromatics or pretreated lignocellulosic biomass. IMPORTANCE There is economic and environmental interest in generating commodity chemicals from renewable resources, such as lignocellulosic biomass, that can substitute for chemicals derived from fossil fuels. The bacterium Novosphingobium aromaticivorans is a promising microbial platform for producing commodity chemicals from lignocellulosic biomass because it can produce these from compounds in pretreated lignocellulosic biomass, which many industrial microbial catalysts cannot metabolize. Here, we show that N. aromaticivorans can be engineered to produce several valuable carotenoids. We also show that engineered N. aromaticivorans strains can produce these lipophilic chemicals concurrently with the extracellular commodity chemical 2-pyrone-4,6-dicarboxylic acid when grown in a complex liquor obtained from alkaline pretreated lignocellulosic biomass. Concurrent microbial production of valuable intra- and extracellular products can increase the economic value generated from the conversion of lignocellulosic biomass-derived compounds into commodity chemicals and facilitate the separation of water- and membrane-soluble products.

09 BIOMASS FUELS↗
DOE OSTI2025

Rhamnogalacturonan I is a recalcitrant pectin domain during Clostridium thermocellum -mediated deconstruction of switchgrass biomass

Background Liquid fuels from lignocellulosic feedstocks are required for transition to a sustainable bioeconomy. However, the recalcitrance of carbon-containing feedstock cell walls to deconstruction poses a barrier to cost effective biological conversion of plant biomass to biofuels. One-step consolidated bioprocessing (CBP) in which anaerobic thermophilic bacteria convert lignocellulosic biomass into liquid fuels is a platform for overcoming the recalcitrance of plant biomass. Results The amounts of hemicellulosic and pectic polysaccharides, two complex cell wall glycans that contribute to plant biomass recalcitrance and that are partially solubilized during CBP of switchgrass aerial biomass by Clostridium thermocellum were evaluated in the liquor, solid residues and residue washate recovered during a 120-h CBP process. After 120 h, 24% of milled switchgrass was solubilized in the C. thermocellum CBP platform. Higher concentrations of arabinose, xylose, galactose, and glucose accumulated in the CBP-fermentation liquor and washate compared to fermentation controls without C. thermocellum, indicating that C. thermocellum solubilized hemicelluloses, but did not fully metabolize them. After five days of fermentation, the relative amount of rhamnose in the solid residues increased by 16% compared to controls, and CBP solid residues had more than 23% increased reactivity against RG-I reactive monoclonal antibodies, indicating that the pectic polymer rhamnogalacturonan I (RG-I) was not effectively solubilized from switchgrass biomass by C. thermocellum CBP. Similarly, the amount of mannose (Man) in the CBP solid residues increased by 7% and reactivity against galactomannan reactive antibodies increased by greater than 14%, indicating that the hemicellulosic polymer galactomannan was also resistant to degradation by C. thermocellum during CBP fermentation. Conclusions These findings show that C. thermocellum is unable to effectively degrade RG-I pectic and galactomannan hemicellulosic components in switchgrass biomass. Targeting these polymers for improved solubilization could enhance the efficiency of conversion of grass biomass to biofuels.

09 BIOMASS FUELS↗
DOE OSTI2024

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗
DOE OSTI2023

Estimating Field-Level Perennial Bioenergy Grass Biomass Yields Using the Normalized Difference Red-Edge Index and Linear Regression Analysis for Central Virginia, USA

We investigated the indicative power of the normalized difference red-edge index (NDRE) for estimating field-level perennial bioenergy grass biomass yields utilizing Sentinel-2 imagery and a linear regression model as a rapid, cost-effective method for biomass yield estimations for bioenergy. We used 2019 data from three study sites containing mature perennial bioenergy grass stands in central Virginia, USA. Of the simulated daily NDRE values based on the temporally weighted averaging of two temporal neighbors, we found the strongest index–yield correlation on 11 August (R = 0.85). We estimated the perennial bioenergy grass biomass yields for (1) all sites using the data pooled from the three sites (all-site estimation) and (2) each site using the data pooled from the other two sites (cross-site estimation). The estimated field-level perennial bioenergy grass biomass yields strongly correlated with the recorded yields (average R2 = 0.76), with a root mean square error (RMSE) of 1.5 Mg/ha and a mean absolute error (MAE) of 1.2 Mg/ha for the all-site estimation. For the cross-site estimation, the site with diverse perennial grass types had the weakest correlation (R2 = 0.44) of the sites, indicating a difficulty in accounting for heterogeneous index–yield relationships in a single model. In addition to identifying a strong indicative power of the NDRE for estimating the overall perennial bioenergy grass biomass yields at a field level, the findings from this study call for an analysis across multiple perennial grasses and a comparison using multiple sites to understand (1) if the indicative power of the index shifts from the biomass of the specific perennial bioenergy grass type to the overall biomass during the growing season and (2) the level of perennial bioenergy grass heterogeneity that may hinder the remotely sensed biomass yield estimation using a single model.

09 BIOMASS FUELS↗
NASA NTRSDate not supplied

Limitations to Biomass Estimation for FAV Using NDVI Analysis of Satellite Acquisitions

The distribution and standing biomass (mass per unit area) of Floating Aquatic Vegetation (FAV)provide assessment metrics for productivity of vegetative communities. Remote sensing acquisition data has been used to estimate standing biomass in various ecosystems using vegetation indices, particularly the normalized difference vegetation index (NDVI), comparing the relative strength of radiation absorbance and reflectance of vegetation in specific wavebands. Obstacles to estimating vegetation biomass using NDVI reported are related to diversity of the vegetation community and high-density saturation. We evaluate the potential for using NDVI derived estimates for FAV biomass in the California Delta by focusing on patches of predominantly single species and compare biomass estimates for specific patches with measurement of total biomass and partitioning within the vegetation canopy. Using Landsat satellite acquisitions, biomass estimates are made for individual pixels and vegetation samples were collected from those same pixels. Focus on patches of predominantly single FAV species resulted in successful estimation of standing biomass beyond that previously reported in other ecosystems. A saturation response for the estimations was observed, however, with a much higher threshold high than previously reported for diverse population aquatic ecosystems. We discuss the likely cause for the saturation phenomenon and potential improvement utilizing altered spectral indices possible with higher spectral resolution from satellites carrying higher waveband multispectral and hyperspectral instruments.

Biomass↗
DOE OSTI2026

An Anisotropic Yield and Damage Material Model to Improve the Contact Pressure Analysis in a Biomass Shredding System

Size reduction systems used in biomass processing break biomass into smaller pieces by utilizing the kinetic energy from the sharp rotating blades. Abrasive and/or erosive wear caused by biomass comminution results in blade wear of the sharp edged cutters, deteriorating the process efficiency. Here, this study aims to optimize the blade design and improve the system efficiency by attempting to understand the interactions between the blades and biomass particles. Since real-time monitoring of these interactions is impractical during operation, mechanical simulations offer a viable alternative for investigating the shredding process. Yet, the irregular geometry and complex mechanical properties of biomass—such as the anisotropic nature of woodchips and their nonlinear fracture behavior—pose significant challenges for accurately simulating contact pressure. In this work an anisotropic yield material model, along with a damage initiation and evolution function, is applied to the woodchip particle to study the contact pressure on shredder blade, offering a scientific basis for improved blade design and process efficiency. This approach can be extended to other biomass processing systems with similar anisotropic feedstocks, making it a valuable tool for advancing sustainable biomass utilization.

09 - BIOMASS FUELS↗