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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Detecting Cage Crossing and Filling Clusters of Magnesium and Carbon Atoms in Zeolite SSZ-13 with Atom Probe Tomography

The conversion of methanol to valuable hydrocarbon molecules is of great commercial interest, as the process serves as a sustainable alternative for the production of, for instance, the base chemicals for plastics. The reaction is catalyzed by zeolite materials. By the introduction of magnesium as a cationic metal, the properties of the zeolite, and thereby the catalytic performance, are changed. With atom probe tomography (APT), nanoscale relations within zeolite materials can be revealed: i.e., crucial information for a fundamental mechanistic understanding. We show that magnesium forms clusters within the cages of zeolite SSZ-13, while the framework elements are homogeneously distributed. These clusters of just a few nanometers were analyzed and visualized in 3-D. Magnesium atoms seem to initially be directed to the aluminum sites, after which they aggregate and fill one or two cages in the zeolite SSZ-13 structure. The presence of magnesium in zeolite SSZ-13 increases the lifetime as well as the propylene selectivity. By using operando UV–vis spectroscopy and X-ray diffraction techniques, we are able to show that these findings are related to the suppression of aromatic intermediate products, while maintaining the formation of polyaromatic compounds. Further nanoscale analysis of the spent catalysts showed indications of magnesium redistribution after catalysis. Unlike zeolite H-SSZ-13, for which only a homogeneous distribution of carbon was found, carbon can be either homogeneously or heterogeneously distributed within zeolite Mg-SSZ-13 crystals as the magnesium decreases the coking rate. Carbon clusters were isolated, visualized, and analyzed and were assumed to be polyaromatic compounds. Small one-cage-filling polyaromatic compounds were identified; furthermore, large-cage-crossing aromatic molecules were found by isolating large coke clusters, demonstrating the unique coking mechanism in zeolite SSZ-13. Short-length-scale evidence for the formation of polyaromatic compounds at acid sites is discovered, as clear nanoscale relations between aluminum and carbon atoms exist.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Plasma–surface interaction in the stellarator W7-X: conclusions drawn from operation with graphite plasma-facing components

W7-X completed its plasma operation in hydrogen with island divertor and inertially cooled test divertor unit (TDU) made of graphite. A substantial set of plasma-facing components (PFCs), including in particular marker target elements, were extracted from the W7-X vessel and analysed post-mortem. The analysis provided key information about underlying plasma–surface interactions (PSI) processes, namely erosion, transport, and deposition as well as fuel retention in the graphite components. The net carbon (C) erosion and deposition distribution on the horizontal target (HT) and vertical target (VT) plates were quantified and related to the plasma time in standard divertor configuration with edge transform ι = 5/5, the dominant magnetic configuration of the two operational phases (OP) with TDU. The operation resulted in integrated high net C erosion rate of 2.8 mg s -1 in OP1.2B over 4809 plasma seconds. Boronisations reduced the net erosion on the HT by about a factor 5.4 with respect to OP1.2A owing to the suppression of oxygen (O). In the case of the VT, high peak net C erosion of 11μm at the strike line was measured during OP1.2B which converts to 2.5 nm s -1 or 1.4 mg s -1 when related to the exposed area of the target plate and the operational time in standard divertor configuration. PSI modelling with ERO2.0 and WallDYN-3D is applied in an interpretative manner and reproduces the net C erosion and deposition pattern at the target plates determined by different post-mortem analysis techniques. This includes also the 13 C tracer deposition from the last experiment of OP1.2B with local 13 CH 4 injection through a magnetic island in one half module. The experimental findings are used to predict the C erosion, transport, and deposition in the next campaigns aiming in long-pulse operation up to 1800 s and utilising the actively cooled carbon-fibre composite (CFC) divertor currently being installed. The CFC divertor has the same geometrical design as the TDU and extrapolation depends mainly on the applied plasma boundary. Extrapolation from campaign averaged information obtained in OP1.2B reveals a net erosion of 7.6 g per 1800 s for a typical W7-X attached divertor plasma in hydrogen.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Techno-economic evaluation of emission control configurations for AMP/PZ-based post-combustion CO 2 capture

Minimizing the environmental impacts of amine-based post-combustion carbon capture technologies is essential for regulatory compliance and public acceptance. Experimental campaigns at RWE's CO 2 capture pilot plant in Niederaussem using CESAR1 demonstrated that combining existing emission abatement technologies can substantially reduce the concentration of amines and degradation products in the CO 2 -depleted flue gas to below the detection limit of an infrared spectrometer. The campaign confirmed that a proprietary dry bed technology (OEASE aerozone™) or a second water wash can reduce AMP and PZ emissions to below 1 mg/Nm 3 . However, an acid or chemically active wash downstream of the water wash is necessary to reduce NH 3 emissions to very low levels (<2 mg/Nm 3 ). Combining a dry bed with an acid wash significantly reduces both the required acid solution and the resulting acid waste. The techno-economic analysis indicates that implementing emission mitigation technologies provides substantial environmental benefits for the CESAR1 process, with only a marginal increase (<1 €/tCO 2 ) in both the carbon capture cost (CCC) and CO 2 avoidance cost (CAC). The additional capital cost associated with extra column packing is offset by operational cost savings from reduced solvent losses. For stringent emission permits targeting NH 3 , a configuration combining a dry bed upstream of the water wash followed by an acid wash achieves the best balance between emission control and cost efficiency. This configuration results in a Levelized Cost of Electricity (LCOE) of 143 €/MWh, a CCC of 45.4 €/tCO 2 , and a CAC of 88.4 €/tCO 2 .

AMP↗
DOE OSTI2020

On the mechanism of soot nucleation

The mechanism of carbon particulate (soot) inception has been a subject of numerous studies and debates. The article begins with a critical review of prior proposals, proceeds to the analysis of factors enabling the development of a meaningful nucleation flux, and then introduces new ideas that lead to the fulfillment of these requirements. In the new proposal, a rotationally-activated dimer is formed in the collision of an aromatic molecule and an aromatic radical; the two react during the lifetime of the dimer to form a stable, doubly-bonded bridge between them, with the reaction rooted in a five-member ring present on the molecule edge. Several such reactions were examined theoretically and the most promising one generated a measurable nucleation flux. The consistency of the proposed model with known aspects of soot particle nanostructure is discussed. Here, the foundation of the new model is fundamentally the H-Abstraction-Carbon-Addition (HACA) mechanism with the reaction affinity enhanced by rotational excitation.

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

Taxogenomic analysis of a novel yeast species isolated from soil, Pichia galeolata sp. nov.

A novel budding yeast species was isolated from a soil sample collected in the United States of America. Phylogenetic analyses of multiple loci and phylogenomic analyses conclusively placed the species within the genus Pichia. Strain yHMH446 falls within a clade that includes Pichia norvegensis, Pichia pseudocactophila, Candida inconspicua, and Pichia cactophila. Whole genome sequence data were analyzed for the presence of genes known to be important for carbon and nitrogen metabolism, and the phenotypic data from the novel species were compared to all Pichia species with publicly available genomes. Across the genus, including the novel species candidate, we found that the inability to use many carbon and nitrogen sources correlated with the absence of metabolic genes. Based on these results, Pichia galeolata sp. nov. is proposed to accommodate yHMH446T (=NRRL Y-64187 = CBS 16864). This study shows how integrated taxogenomic analysis can add mechanistic insight to species descriptions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Correlation-based network analysis combined with machine learning techniques highlight the role of the GABA shunt in Brachypodium sylvaticum freezing tolerance

Perennial grasses will account for approximately 16 billion gallons of renewable fuels by the year 2022, contributing significantly to carbon and nitrogen sequestration. However, perennial grasses productivity can be limited by severe freezing conditions in some geographical areas, although these risks could decrease with the advance of climate warming, the possibility of unpredictable early cold events cannot be discarded. We conducted a study on the model perennial grass Brachypodium sylvaticum to investigate the molecular mechanisms that contribute to cold and freezing adaption. The study was performed on two different B. sylvaticum accessions, Ain1 and Osl1, typical to warm and cold climates, respectively. Both accessions were grown under controlled conditions with subsequent cold acclimation followed by freezing stress. For each treatment a set of morphological parameters, transcription, metabolite, and lipid profiles were measured. State-of-the-art algorithms were employed to analyze cross-component relationships. Phenotypic analysis revealed higher adaption of Osl1 to freezing stress. Our analysis highlighted the differential regulation of the TCA cycle and the GABA shunt between Ain1 and Osl1. Osl1 adapted to freezing stress by repressing the GABA shunt activity, avoiding the detrimental reduction in fatty acid biosynthesis and the concomitant detrimental effects on membrane integrity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Cost and life cycle analysis for deep CO 2 emissions reduction of steelmaking: Blast furnace-basic oxygen furnace and electric arc furnace technologies

Iron and steel manufacturing is the largest contributor to CO 2 emissions among heavy industries worldwide. This is mostly due to the use of coal in blast furnace-basic oxygen furnace (BF-BOF) process for virgin (primary) steel production. The electricity generation mix used in the electric arc furnace (EAF) process to recycle scrap steel also contributes to the CO 2 emission associated with secondary steel production. To decarbonize iron and steel sector, we investigated decarbonization options for BF-BOF and EAF processes, including energy efficiency, carbon capture and storage, and the use of clean energy sources, in various BF-BOF and EAF process configurations. Additionally, for each decarbonization approach, we evaluated the CO 2 reduction potential via life cycle analysis (LCA) and estimated the associated cost through techno-economic analysis (TEA). A typical U.S. BF-BOF for virgin steel production has a cradle-to-gate (CTG) CO 2 emissions of 1,990 kg/MT steel with a levelized cost of steel (LCOS) of $\$439$/MT steel, while a typical U.S. EAF process for secondary steel production in the United States has a CTG CO 2 emissions of 270 kg/MT steel with a LCOS of $\$365$/MT steel. Combining renewable energy sources and carbon capture, BF-BOF CTG CO 2 emissions can be reduced to 16 kg/MT steel, and EAF configurations can achieve similar deep reductions to reach 25 kg/MT steel. The corresponding LCOS with these decarbonization levels is estimated to increase to $\$542$/MT steel and $\$348$/MT steel, respectively. The estimated CO 2 avoidance costs vary from -$\$90$/MT CO 2 to $\$646$/MT CO 2 , depending on the various decarbonization technologies and energy prices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Analysis of furnace contamination on superconducting radio frequency niobium using secondary-ion mass spectrometry

Detection of surface contamination on niobium materials used in superconducting radio frequency (SRF) applications is difficult due to quantitative sensitivity and near-atomic depth resolution needed. Inspection of samples known to have experienced surface contamination was found to have inconsistent nitride coverage after high-temperature nitrogen gas exposure (“doping”). Here we compare contaminating species found on samples treated in several different vacuum furnaces, both “exposed” directly in the chamber and “protected” by containment shielding from evaporative sources with “furnace caps.” Typically, furnace caps are used to impede contamination from reaching the interior surface of cavities during the high-temperature vacuum bake that immediately precedes exposure to nitrogen gas. Although, to date, little is known about the effectiveness of these caps, SIMS results showed that they were effective in limiting contamination arising from the furnace environment. Inspection of sample surfaces by SEM showed a lack of nitrides present on contaminated specimens. TEM with energy dispersive spectroscopy performed on these samples revealed that a carbon-rich layer now existed, indicating that a relatively high contaminant load prevents the nucleation and growth of surface nitrides, while thus inhibiting interstitial nitrogen uptake. Except in extreme cases, subsequent removal of the top several micrometers of the surface via electropolishing appears to effectively eliminate any strong influence on the subsequent SRF cavity performance. With the absence of furnace cleaning, carbon contamination was found to be nearly 10× higher for protected nitrogen-doped and electropolished samples, with minimal metallic contamination detected for both processes. SIMS analysis was also performed to compare the cleanliness of samples fully prepared by such nitrogen “doping” with those prepared by a related process, involving the dissolution of niobium surface oxide and diffusion of oxygen into the surface. This oxygen doping or alloying process offers attractive advantages.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry

Abstract The role of manganese (Mn) in ecosystem carbon (C) biogeochemical cycling is gaining increasing attention. While soil Mn is mainly derived from bedrock, atmospheric deposition could be a major source of Mn to surface soils, with implications for soil C cycling. However, quantification of the atmospheric Mn cycle, which comprises emissions from natural (desert dust, sea salts, volcanoes, primary biogenic particles, and wildfires) and anthropogenic sources (e.g., industrialization and land‐use change due to agriculture), transport, and deposition, remains uncertain. Here, we use compiled emission data sets for each identified source to model and quantify the atmospheric Mn cycle by combining an atmospheric model and in situ atmospheric concentration measurements. We estimated global emissions of atmospheric Mn in aerosols (<10 μm in aerodynamic diameter) to be 1,400 Gg Mn year −1 . Approximately 31% of the emissions come from anthropogenic sources. Deposition of the anthropogenic Mn shortened Mn “pseudo” turnover times in 1‐m‐thick surface soils (ranging from 1,000 to over 10,000,000 years) by 1–2 orders of magnitude in industrialized regions. Such anthropogenic Mn inputs boosted the Mn‐to‐N ratio of the atmospheric deposition in non‐desert dominated regions (between 5 × 10 −5 and 0.02) across industrialized areas, but that was still lower than soil Mn‐to‐N ratio by 1–3 orders of magnitude. Correlation analysis revealed a negative relationship between Mn deposition and topsoil C density across temperate and (sub)tropical forests, consisting with atmospheric Mn deposition enhancing carbon respiration as seen in in situ biogeochemical studies.

Environmental Sciences & Ecology↗
DOE OSTI2024

DE-FE0029488 - North Dakota Integrated Carbon Capture and Storage Complex Feasibility Study Public Data

Data from award DE-FE0029488 - North Dakota Integrated Carbon Capture and Storage Complex Feasibility Study performed by the Energy & Environmental Research Center including the following: - 2D Seismic {Input data, sgy files, maps, logs, and descriptors} - Core Petrophysics {Core analysis of plugs from the two stratigraphic test wells (Flemmer-1 [API 33-057-00039] and BNI-1 [API 33-065-00018])} - North Dakota Oil and Gas File No 37380 Files - North Dakota Oil and Gas File No 37672 Files - Well Testing Data {Summary of well testing methods and results from the stratigraphic test wells (Flemmer-1 and BNI-1)} Additional References: https://www.netl.doe.gov/sites/default/files/2017-12/Wesley-Peck-_Mastering-the-Subsurface_CarbonSAFE-Phase-II_August-2017-final.pdf Peck, W.D., Ayash, S.C., Klapperich, R.J., Gorecki, C.D. (2019) The North Dakota integrated carbon storage complex feasibility study, International Journal of Greenhouse Gas Control, Volume 84, 2019, Pages 47-53, https://doi.org/10.1016/j.ijggc.2019.03.001

Carbon Storage↗
DOE OSTI2023

A pyridoxal 5'-phosphate-dependent Mannich cyclase

Pyridoxal 5'-phosphate (PLP)-dependent enzymes catalyse a diverse range of chemical transformations. Despite their extraordinary functional diversity, no PLP-dependent enzyme is known to catalyse Mannich-type reactions, an important carbon–carbon bond-forming reaction in synthetic organic chemistry. Here we report the discovery of a biosynthetic enzyme LolT, a PLP-dependent enzyme catalysing a stereoselective intramolecular Mannich reaction to construct the pyrrolizidine core scaffold in loline alkaloids. Importantly, its versatile catalytic activity is harnessed for stereoselective synthesis of a variety of conformationally constrained α,α-disubstituted α-amino acids, which bear vicinal quaternary–tertiary stereocentres and various aza(bi)cyclic backbones, such as indolizidine, quinolizidine, pyrrolidine and piperidine. Furthermore, crystallographic and mutagenesis analysis and computational studies together provided mechanistic insights and structural basis for understanding LolT’s catalytic activity and stereoselectivity. As a whole, this work expands the biocatalytic repertoire of carbon–carbon bond-forming enzymes and increases our knowledge of the catalytic versatility of PLP-dependent enzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multi-Fidelity Scheme for Accelerating 4D Finite Element Analysis for Mircoreactors

Next-generation microreactors are currently being designed to be operated terrestrial and extraterrestrial for remote surface power production. These systems will provide an alternative source of carbon-free energy that is versatile and can be utilized for various applications. These applications of microreactors have prompted the usage of high-fidelity unstructured finite element (FE) based approaches to provide time-dependent solutions for multiple physics fields. Computing these high-fidelity (4-D) solutions for multiple design iterations, physics fields, and transient events requires an immense computational cost. These high-fidelity solutions are computational expensive and the cost can be reduced through the implementation of less accurate low-fidelity solutions. Unlike the current fleet of commercial nuclear reactors, these next-gen systems present challenges due to the material and physical limitations required. Due to these constraints, the brute force technique of parameterizing important system characteristics determines whether a design meets the project objective. A system such as a nuclear reactor could have thousands of design parameters that affect system performance. In order to analyze the entire parameter space of such a complex system would require millions of CPU hours and countless design iterations. This costly approach is not practical due to regulatory and budget limitations. In this proposal, an approach that utilizes hybrid high-fidelity and low-fidelity FE models to reduce the computational cost of evaluating these applications in 4-D will be presented. The accuracy of the high-fidelity model and the computational efficiency of the low-fidelity model are taken advantage of to produce a solution that closely resembles the full order high-fidelity solution. By utilizing an unconverged coarse FE mesh, operation limits such as temperature, structural loading, etc., can be evaluated in an accelerated fashion and then can be spatially interpolated onto a finer mesh. The resulting error arising from the coarse mesh can be mitigated with a discrepancy function that actively quantifies and corrects the error in the coarse solution. This discrepancy function can be periodically updated with high-fidelity calculations across the temporal domain thus requiring less iterations on the fine mesh. As a result, the computational cost can be reduced for the evaluation and design iteration of microreactors. The proposal for this research contains three sections: Section 2 provides a literature review, Section 3 outlines the methodology for the proposed multi-fidelity scheme, and Section 4 displays preliminary results of the proposed research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Analysis of Real-World Preignition Data Using Neural Networks

Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure. Further, this indicates that the alternating pattern of preignition cycles within clusters is influenced by the thermodynamic state as reflected in the pressure, but that the trigger for the initial preignition cycle is not thermodynamic in nature, but more likely tied to a critical threshold in the chemistry of the fuel/lubricant mixture in the upper crevice or other factors related to the presence of an ignition source.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Streamlining heterologous expression of top carbonic anhydrases in Escherichia coli : bioinformatic and experimental approaches

Carbonic anhydrase (CA) enzymes facilitate the reversible hydration of CO 2 to bicarbonate ions and protons. Identifying efficient and robust CAs and expressing them in model host cells, such as Escherichia coli, enables more efficient engineering of these enzymes for industrial CO 2 capture. However, expression of CAs in E. coli is challenging due to the possible formation of insoluble protein aggregates, or inclusion bodies. This makes the production of soluble and active CA protein a prerequisite for downstream applications. In this study, we streamlined the process of CA expression by selecting seven top CA candidates and used two bioinformatic tools to predict their solubility for expression in E. coli. The prediction results place these enzymes in two categories: low and high solubility. Our expression of high solubility score CAs (namely CA5-SspCA, CA6-SazCAtrunc, CA7-PabCA and CA8-PhoCA) led to significantly higher protein yields (5 to 75 mg purified protein per liter) in flask cultures, indicating a strong correlation between the solubility prediction score and protein expression yields. Furthermore, phylogenetic tree analysis demonstrated CA class-specific clustering patterns for protein solubility and production yields. Unexpectedly, we also found that the unique N-terminal, 11-amino acid segment found after the signal sequence (not present in its homologs), was essential for CA6-SazCA activity. Overall, this work demonstrated that protein solubility prediction, phylogenetic tree analysis, and experimental validation are potent tools for identifying top CA candidates and then producing soluble, active forms of these enzymes in E. coli. The comprehensive approaches we report here should be extendable to the expression of other heterogeneous proteins in E. coli.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”

This data package contains data and code used in the paper “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”. This paper details results from two studies: 1) a laboratory leaf litter incubation experiment (lab experiment) and 2) a multi-site observational field study (field study). Both studies were designed to test the relationships among litter quality, microbial physiological traits, and mineral-associated soil carbon (C). In the lab experiment, we incubated 16 temperate tree litters of differing chemical quality with isotopically distinct soil, measuring microbial physiological traits and the flow of litter-derived C into the mineral-associated soil C pool. In the field study, we sampled soils (0-5 cm) across six eastern US temperate forests, measuring microbial physiological traits, soil abiotic properties, and leaf litter chemistry. The analysis data are provided in two .csv files corresponding to either the lab experiment or field study. Both files contain data on litter chemistry, microbial physiological traits (growth and turnover rates, and carbon use efficiency [CUE]), and the mineral-associated soil C pool. The lab experiment dataset additionally contains litter-derived versus soil-derived soil C, respiration, and litter decomposition parameters. The field study dataset additionally contains site-level climatic information, ectomycorrhizal dominance of plots, and plot-level soil properties. Also provided is the R code and output reproducing the results in the related publication. Analyses were originally performed using R version 3.6.1 using the package "lavaan" and the packages listed on lines 5-7 in the file "data.R".

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Universal Solvent Viscosity Reduction via Hydrogen Bonding Disruptors

Liquid Ion Solutions LLC (DBA RoCo Global) in partnership with Carnegie Mellon University and Carbon Capture Scientific LLC, has performed lab-scale development and evaluation of novel additives that lower the viscosity of water-lean amine solvents for post-combustion carbon dioxide capture. This project focuses on developing additives that minimize the formation of long-range electrostatic and hydrogen bonding (HB) networks, decreasing the solvent viscosity, improving diffusion, and improving the process economics. The project objectives included: 1) performing computer simulation to understand the molecular interactions of the additive molecules in water-lean CO 2 capture solvents, 2) design and synthesis of HB disruptors additives, 3) performance testing with additive molecules on model amine solvents, and 4) demonstration of the effectiveness of the optimized additives in the presence of synthetic flue gas. To meet the abovementioned objectives, the project team utilized a holistic approach that combines molecular simulation, experimental testing, and economic analysis studies. The project team developed ab initio molecular model and then perform computer simulation to develop relationship between hydrogen bonding, viscosity, and performed quantitative analysis of additive on the viscosity of the solvent. The team completed computational comparative study on a range of organic functional groups such as ethers, esters, cyclic carbonates, alkanes, and ammonium salts for their effect on viscosity gaining key insights into molecular interactions and the impact of various functional groups and molecular shapes on viscosity. Assisted with molecular simulation insights, the project team conducted additive synthesis and testing, including a proof-of-concept study, additive screening, optimization, and synthetic flue gas testing. The experimental proof-of-concept study proved that the hydrogen bonding acceptors result in significant decrease of viscosities. Detailed additive screening (exploring various functionalities and molecular structures) has been performed. Several promising additives showed excellent reduction in viscosity (30-41%) at 5% additive loading, and over 50% viscosity reduction at 10% additive loading for the model solvents. The team also performed complex screening studies on additive loadings and mixing effect among additives using the design of experiments. Based on multiple screening experiments, one additive-solvent candidate was down-selected for synthetic flue gas testing. A 100-hour continuous absorption/desorption study was conducted under simulated flue gas using a lab-scale continuous capture and separation system. No degradation (for both solvent and additive) was observed based on the GC results of the solvent samples collected from the continuous study. The team conducted preliminary engineering analyses and cost-benefit analyses to quantify the potential economic benefits of the additive approach for solvent viscosity reduction. Based on the experimental data, CO 2 capture cost savings from the capital and operating cost savings are estimated at $\$$4.7/tonne and $\$$0.3/tonne CO 2 captured, respectively. Considering the additive cost, the net benefit is estimated to be between $\$$4.32~$\$$4.86/tonne CO 2 captured.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Structural Transformation and Degradation of Cu Oxide Nanocatalysts during Electrochemical CO 2 Reduction

The electrochemical CO 2 reduction reaction (CO 2 RR) holds enormous potential as a carbon-neutral route to the sustainable production of fuels and platform chemicals. The durability for long-term operation is currently inadequate for commercialization, however, and the underlying deactivation process remains elusive. A fundamental understanding of the degradation mechanism of electrocatalysts, which can dictate the overall device performance, is needed. In this work, we report the structural dynamics and degradation pathway of Cu oxide nanoparticles (CuO x NPs) during the CO 2 RR by using in situ small-angle X-ray scattering (SAXS) and X-ray absorption spectroscopy (XAS). The in situ SAXS reveals a reduction in the size of NPs when subjected to a potential at which no reaction products are detected. At potentials where the CO 2 RR starts to occur, CuO x NPs are agglomerated through a particle migration and coalescence process in the early stage of the reaction, followed by Ostwald ripening (OR) as the dominant degradation mechanism for the remainder of the reaction. As the applied potential becomes more negative, the OR process becomes more dominant, and for the most negative applied potential, OR dominates for the entire reaction time. The morphological changes are linked to a gradual decrease in the formation rate for multicarbon products (C 2 H 4 and ethanol). Other reaction parameters, including reaction intermediates and local high pH, induce changes in the agglomeration process and final morphology of the CuO x NPs electrode, supported by post-mortem ex situ microscopic analysis. The in situ XAS analysis suggests that the CuO x NPs reduced into the metallic state before the structural transformation was observed. The introduction of high surface area carbon supports with ionomer coating mitigates the degree of structural transformation and detachment of the CuO x NPs electrode. These findings show the dynamic nature of Cu nanocatalysts during the CO 2 RR and can serve as a rational guideline toward a stable catalyst system under electrochemical conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗