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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hydrogen-rich syngas production from the steam co-gasification of low-density polyethylene and coal refuse

Gasification provides a promising pathway for transforming waste materials into valuable products, such as fuels and chemicals. Here, this study investigates the steam co-gasification of low-density polyethylene (LDPE) and compressed thickener underflow, representative of coal refuse (CR), in a drop tube reactor. The effects of feed blend ratio (0–100 wt% LDPE) and temperature (800–1000 °C) on syngas composition, tar formation, and process efficiency are examined. The high volatility of LDPE makes it more reactive than CR but also promotes the formation of 2–7 ring aromatic tars. Increasing temperature improves carbon conversion efficiency (CCE), cold gas efficiency (CGE), and syngas yield, although the lower heating value (LHV) of syngas decreases. Hydrogen is the dominant gas product, reaching 59 vol% with the H 2 /CO molar ratio ranging from 2.27 to 4.74. Synergistic effects from alkali and alkali earth metals (AAEMs), particularly K and Ca, in CR ash enhance syngas yield by catalyzing char gasification and tar cracking. Hematite (Fe 2 O 3 ) and ash from sub-bituminous/bituminous coals are explored as tar reforming catalysts. Fe 2 O 3 achieves 100 % tar reforming efficiency, while coal ash, with a lower Fe 2 O 3 content (15 wt%), is less effective at cracking polycyclic aromatic hydrocarbons, particularly naphthalene. These findings demonstrate the flexibility of co-gasification, allowing precise tuning of syngas characteristics for specific downstream applications. Further optimization of waste-derived catalysts could enhance the economic viability of gasification in waste-to-energy processes.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

From Plastic Waste to Fuel: Pyrolysis and Gasification of Polyethylene for Hydrogen Production

Thermochemical conversion processes offer promising solutions to address the plastic pollution crisis by transforming plastic waste into valuable products, notably hydrogen. In this study, thermal pyrolysis and steam gasification of polyethylene (PE), the most abundantly produced plastic waste, are investigated in a drop tube reactor system. Various process parameters, namely temperature, residence time, and feedstock composition, are evaluated to establish their correlations with reaction performance. Coal refuse, obtained from discarded thickener underflow in coal processing, is introduced as a co-feedstock for gasification to enhance PE handling and examine synergistic effects on product distribution, particularly H2 yield and syngas quality. Furthermore, the potential of low-cost, environmentally friendly catalysts (i.e., iron oxides, coal ash) for tar reforming is explored.

Natesakhawat, Sittichai↗
DOE OSTI2024

A survey study on arsenic speciation in coal fly ash and insights into the role of coal combustion conditions

Coal fly ashes (CFAs) are the low-density byproducts of the coal combustion process. Improper or uncontrolled CFA disposal poses significant environmental and health concerns due to the potential leaching of toxic heavy metals such as arsenic (As). Previous studies have investigated the content and speciation of As in different CFA samples, yet systematic information on As speciation in CFA with representative coal source and combustion conditions is still missing. Based on a recent survey study on the typical coal sources and combustion conditions across the U.S., this study selected 19 representative CFA samples to systematically investigate As speciation and potential correlations with these parameters. The composition, morphology, mineralogy, and As speciation of these CFA samples were characterized by complementary analytical, microscopic, and spectroscopic techniques. Synchrotron X-ray spectroscopy and microscopy analyses revealed the dominant As oxidation state to be As(V) and with strong associations to Ca, with the exception of 3 samples that had 19–51% As(III), likely due to the use of selective catalytic reduction (SCR) process. Principal component analysis was conducted to identify potential correlations of As concentration and oxidation state with parameters such as major element content, loss on ignition (LOI), average particle size, coal source, and combustion condition. Al 2 O 3 and FeO content were found to capture a majority of the variability. Further, results from this study provide fundamental basis for understanding the correlations between coal source, combustion conditions, CFA characteristics, and As speciation, and providing insights for downstream beneficial utilization or disposal management.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Performance Testing of Moving Bed Gasifier Using Biomass and Waste Fuels to Generate Low-Cost Clean Hydrogen

Our need for hydrogen is growing as the world transitions toward a low-carbon future. Hydrogen provides long-term energy storage for grid stability in a solar- and wind-dominated power market and can be used to decarbonize other sectors. One promising process for generating low-cost hydrogen that produces net-negative carbon is to gasify biomass with a mixture of legacy coal wastes, waste plastics, and other wastes with carbon capture. Use of waste fuels lowers costs and diverts waste from landfills. EPRI is leading a project, funded by the U.S. Department of Energy, to conduct performance testing of modular, moving-bed gasification for the generation of low-cost, clean hydrogen from biomass mixed with legacy coal waste, waste plastic, and/or refuse derived fuels. The work scope includes preparation of multiple pellet feedstocks using biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste (wire insulation), and refuse-derived fuel (RDF). These pelletized feedstocks are being qualified based on performance testing of selected fuel blend compositions in updraft moving-bed gasifier located in Sardinia, Italy. Testing is being conducted to obtain relevant data to advance the modular design of the moving-bed gasification process, and successfully use these feedstocks to produce a high hydrogen content raw syngas that can be shifted to produce clean hydrogen. Testing results will be used to determine the effects of the various fuels on feedstock development, the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics), and impacts on gasifier operations.

08 HYDROGEN↗
DOE OSTI2024

Fluidized-Bed Gasification of Coal-Biomass-Plastics for Hydrogen Production

Coal is one of the most abundant fossil energy resources in the United States and in the world. The recoverable reserves in the United States are estimated to be about 252 billion tons – more than 350 years of supply at current rates of usage. However, the share of coal in total primary energy consumption in the US has been declining over the years. The decline of coal is mainly attributed to cheap natural gas and precipitous declines in the cost of electricity production from renewable technologies such as wind and solar. Coal can potentially be used if it is coupled with carbon-neutral feedstock such as biomass-agricultural residues, forest biomass, and forest residues. Co-gasification of coal and biomass can become a negative carbon emission technology if the carbon dioxide (CO 2 ) is captured and sequestered. Although the biomass gasification process has a lot of similarities to coal gasification, the large-scale adaptation of power production sourced from biomass has not come to fruition. The main reason is that the power production from biomass is still expensive when compared with natural gas or coal power technologies. To address the feedstock cost, one approach is to use low-cost feedstocks, such as municipal solid wastes (MSW) or plastics, for gasification. Gasification involves the partial oxidation of coal and/or biomass feedstocks to produce a combustible fuel called synthesis gas (syngas) which is composed of carbon monoxide (CO), hydrogen (H 2 ), CO 2 , methane (CH 4 ), nitrogen (N 2 ), water (H 2 O), and other compounds that might be considered as contaminants. Raw syngas from gasification must go through multiple steps to produce high-purity hydrogen. The specific steps depend upon the quality (gas composition, contaminants, and their concentration) and condition (pressure and temperature) of syngas. The long-term goal of the project was to utilize coal and plastics together with biomass to produce energy and fuels using a gasification platform while reducing greenhouse gas emissions. The main objective of this research was to examine gasification performance in a laboratory-scale fluidized-bed gasifier for hydrogen production. The specific objectives of the research were to: (i) study coal-plastic-biomass mixture flowability for consistent feeding in the gasifier; (ii) understand the gasification behavior of the mixture in steam and oxygen environments; (iii) perform thermal property characterization of ash and slag from the mixture feedstock and refractory-ash interface of the mixture under gasification conditions; and (iv) develop process models to determine the technology needed for syngas cleanup and contaminants. The study found that there was no apparent segregation when biomass, coal, and waste plastics were mixed together during feeding. Although there were differences in hydrogen production when individual feedstock were fed, the hydrogen concentration remained almost constant with various blends. Therefore, blending waste plastics with biomass and coal, which are all abundant, is a better approach for energy production. Results of the techno-economic analysis suggested that integration of advanced gasification (GTI’s R-GAS™) and syngas cleanup and conditioning technologies (RTI’s WDP and AFWGS) for clean hydrogen production resulted in substantial benefits, including significant capital cost and operating cost reductions. Advanced technologies resulted in 16% reduction in the hydrogen production cost (COH) from 2.94 $\$$/kg to 2.47 $\$$/g, with further scope for optimization and cost reduction. These advanced technologies also result in lower emissions, and improved energy efficiency.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Bipartisan Infrastructure Law (BIL) – Illinois Rare Earth Novel Extraction and Supply (IRENES)

This report presents the physical and chemical characterization of breaker and sorter reject materials sourced from the Prairie State Generation facility, as part of the Illinois Rare Earth Novel Extraction and Supply (IRENES) project. Key analyses include particle size distribution, density, angle of repose, proximate and ultimate composition, mineralogy, and elemental content. Breaker reject material was found to be coarser and higher in ash content (~80%) with lower calorific value, while sorter reject showed finer distribution, lower ash (~68%), and higher carbon and energy content. XRD and XRF analyses confirmed the presence of REE-bearing minerals and relevant oxides, supporting process design and beneficiation strategy development for critical mineral recovery.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Targeted Rare Earth Element Extraction from Mine Drainage Treatment Solids Informed by Advanced Characterization

In support of a clean energy transition in the U.S., National Energy Technology Laboratory (NETL) has collaborated with staff at Hedin Environmental and students at the University of Pittsburgh to characterize critical mineral content and recovery potential from acid mine drainage treatment solids (AMD solids). AMD solids in Appalachia are an unconventional feedstock of rare earth elements (REEs), with potential of suppling 1,102 tons REE/year. To inform recovery efforts, select AMD solids were examined using synchrotron microprobe analysis in conjunction with USGS-developed geochemical modeling to indicate likely phases hosting critical minerals (REE, Co, Ni, etc.) and associated metals . More than 100 AMD solids were collected from 94 passive AMD treatment systems in Pennsylvania, where limestone aggregates are used for acidity neutralization. As pH increases, dissolved metals and critical minerals in AMD are attenuated as surface coatings on limestone. The collected AMD solids contained up to 2000 mg/kg REE, up to 13,000 mg/kg transition metals (Co, Ni, Zn) and up to 440 mg/kg Li. Regardless of the diverse chemical compositions from AMD solids (Al-rich, Mn-rich, or Al,Fe,Mn-rich), REEs were mostly associated with Al and Mn (hydr)oxides, while select heavy REEs (e.g., Gd, Dy) were co-localized with Fe (hydr)oxides. Co and Ni have different distribution zones, while both co-localized with Mn (hydr)oxides. Based on this characterization, NETL developed a patent-pending innovative step-leaching protocol, “Targeted Rare Earth Extraction (TREE)” to effectively recover up to 90% REE and 60% Co in separate steps. In addition, select post-TREE solid residuals (purified Al oxides, or Mn oxides) can be further developed into functional materials (e.g., lithium and CO2 sorbents) needed for green energy transition and carbon management. This characterization-informed approach as well as TREE processing from AMD solids can be used for other legacy wastes (e.g., coal ash, oil and gas drill cutting, mine tailings), and offers an opportunity to transform waste streams into environmental and economic assets that meet U.S. Department of Energy and U.S. Environmental Protection Agency goals.

characterization and extraction of rare earth elem↗
DOE OSTI2023

Decision-Making Framework to Evaluate Opportunities for Recovery of Rare Earth Elements and Critical Minerals in Produced Water Networks

Oil and gas development activities require a significant amount of water. Given the environmental impacts associated with high consumption and subsequent disposal of this water, there is a need for strategies to support effective reuse of, treatment of, and/or resource recovery from this produced water. These streams can contain appreciable concentrations of rare earth elements (REE) and critical minerals (CM) (e.g., Lithium), which are critical for many important applications in electronics, technology, manufacturing, energy, and medicine [1]. Along with REE/CM present in produced water, other waste streams such as fly ash from coal-fired power plants and acid mine discharge present other potential sources for recovery of REE/CM [2-4]. And with increases in demand for REE/CM, the need for recovery from wastewater streams is becoming even more important. There is a need to develop effective decision-making tools to evaluate the economic and environmental potential for REE/CM recovery from produced water networks while supporting the needs of drilling and hydraulic fracturing activities. In this work, we present our progress in developing a decision-making framework to efficiently design and operate produced water networks for REE/CM recovery. Our approach considers REE/CM recovery from produced water streams alongside other potential wastewater sources. The models consider the location and capacity of storage and decentralized treatment processes as well as the design and operation of pipeline and transportation networks to connect different sources and effectively schedule inventories, reuse, and recovery opportunities. We focus on the evaluation of opportunities for REE/CM recovery with treatment constraints on composition and flow. We demonstrate this framework with an illustrative case study that features diverse production sites, storage facilities, transportation, and treatment sites. This proposed framework will be deployed in an open-source software package that is compatible with the PARETO framework to deliver analysis and decision-making tools that allow stakeholders to quantitatively evaluate potential opportunities for REE/CM recovery in produced water networks.

Pulsipher, Joshua↗
DOE OSTI2021

Aerodynamic effects on outer ash deposition rates in second generation atmospheric pressure oxy-coal combustion systems

Recent measurements in scenarios representative of second generation atmospheric pressure oxy-coal combustion systems have shown a significant increase in ash deposition rates in comparison to combustion in air. However, the causative mechanisms behind this increase have not been well understood. To fill this void, well-characterized experiments including fuel and deposit particle size distributions (PSDs) were coupled with highly resolved numerical simulations to isolate the aerodynamic effects impacting the deposition process such that mechanisms could be hypothesized. Three combustion scenarios (AIR, OXY27, OXY70) spanning a factor of three variation in flue gas volumetric flow rates were simulated and the deposition characteristics (impaction rates, deposit PSD, temperature, residence times, capture rates) tracked/predicted using a customized deposition module. The measured deposit PSD was significantly different from the PSD of the parent fuel indicating significant physio-chemical transformations (coalescence and particle growth in particular) at play. The use of simplistic modeling approaches (swelling parameter variations) to model particle growth led to inaccurate deposit ash PSD and rate predictions. A more satisfactory agreement between the measurements and simulations was obtained when the functional form of the parent fuel PSD (spread parameter) was modified to conform closely to the deposit PSD while still ensuring the fidelity of temperature and velocity predictions. Based on the measured ash compositions, identical capture criteria were employed across all three scenarios. Here this study further supports the theory that the ash deposition rates in these systems are dominated by aerodynamic effects with the ash PSD playing a dominant role.

42 ENGINEERING↗