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

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

PDFDataExtractor: A Tool for Reading Scientific Text and Interpreting Metadata from the Typeset Literature in the Portable Document Format

The layout of portable document format (PDF) files is constant to any screen, and the metadata therein are latent, compared to mark-up languages such as HTML and XML. No semantic tags are usually provided, and a PDF file is not designed to be edited or its data interpreted by software. However, data held in PDF files need to be extracted in order to comply with opensource data requirements that are now government-regulated. In the chemical domain, related chemical and property data also need to be found, and their correlations need to be exploited to enable data science in areas such as data-driven materials discovery. Such relationships may be realized using text-mining software such as the “chemistry-aware” natural-language-processing tool, ChemDataExtractor; however, this tool has limited data-extraction capabilities from PDF files. This study presents the PDFDataExtractor tool, which can act as a plug-in to ChemDataExtractor. It outperforms other PDF-extraction tools for the chemical literature by coupling its functionalities to the chemical-named entityrecognition capabilities of ChemDataExtractor. The intrinsic PDF-reading abilities of ChemDataExtractor are much improved. The system features a template-based architecture. This enables semantic information to be extracted from the PDF files of scientific articles in order to reconstruct the logical structure of articles. While other existing PDF-extracting tools focus on quantity mining, this template-based system is more focused on quality mining on different layouts. PDFDataExtractor outputs information in JSON and plain text, including the metadata of a PDF file, such as paper title, authors, affiliation, email, abstract, keywords, journal, year, document object identifier (DOI), reference, and issue number. With a self-created evaluation article set, PDFDataExtractor achieved promising precision for all key assessed metadata areas of the document text.

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

Osmosensor-mediated control of Ca 2+ spiking in pollen germination

Higher plants survive terrestrial water deficiency and fluctuation by arresting cellular activities (dehydration) and resuscitating processes (rehydration). However, how plants monitor water availability during rehydration is unknown. Although increases in hypo-osmolarity-induced cytosolic Ca 2+ concentration (HOSCA) have long been postulated to be the mechanism for sensing hypo-osmolarity in rehydration, the molecular basis remains unknown. Because osmolarity triggers membrane tension and the osmosensing specificity of osmosensing channels can only be determined in vivo, these channels have been classified as a subtype of mechanosensors. Here we identify bona fide cell surface hypo-osmosensors in Arabidopsis and find that pollen Ca 2+ spiking is controlled directly by water through these hypo-osmosensors—that is, Ca 2+ spiking is the second messenger for water status. We developed a functional expression screen in Escherichia coli for hypo-osmosensitive channels and identified OSCA2.1, a member of the hyperosmolarity-gated calcium-permeable channel (OSCA) family of proteins. We screened single and high-order OSCA mutants, and observed that the osca2.1/osca2.2 double-knockout mutant was impaired in pollen germination and HOSCA. OSCA2.1 and OSCA2.2 function as hypo-osmosensitive Ca 2+ -permeable channels in planta and in HEK293 cells. Decreasing osmolarity of the medium enhanced pollen Ca 2+ oscillations, which were mediated by OSCA2.1 and OSCA2.2 and required for germination. OSCA2.1 and OSCA2.2 convert extracellular water status into Ca 2+ spiking in pollen and may serve as essential hypo-osmosensors for tracking rehydration in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Classical Swine Fever Virus Structural Glycoprotein E2 Interacts with Host Protein ACADM during the Virus Infectious Cycle

The E2 glycoprotein is one of the four structural proteins of the classical swine fever virus (CSFV) particle. E2 has been shown to be involved in many virus functions, including adsorption to host cells, virus virulence and interaction with several host proteins. Using a yeast two-hybrid screen, we have previously shown that the CSFV E2 specifically interacts with swine host protein medium-chain-specific acyl-Coenzyme A dehydrogenase (ACADM), an enzyme that catalyzes the initial step of the mitochondrial fatty acid beta-oxidation pathway. Here, we show that interaction between ACADM and E2 also happens in swine cells infected with CSFV using two different procedures: coimmunoprecipitation and a proximity ligation assay (PLA). In addition, the amino acid residues in E2 critically mediating the interaction with ACADM, M49 and P130 were identified via a reverse yeast two-hybrid screen using an expression library composed of randomly mutated versions of E2. A recombinant CSFV, E2ΔACADMv, harboring substitutions at residues M49I and P130Q in E2, was developed via reverse genomics from the highly virulent Brescia isolate. E2ΔACADMv was shown to have the same kinetics growth in swine primary macrophages and SK6 cell cultures as the parental Brescia strain. Similarly, E2ΔACADMv demonstrated a similar level of virulence when inoculated to domestic pigs as the parental Brescia. Animals intranasally inoculated with 10 5 TCID 50 developed a lethal form of clinical disease with virological and hematological kinetics changes undistinguishable from those produced by the parental strain. Therefore, interaction between CSFV E2 and host ACADM is not critically involved in the processes of virus replication and disease production.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme

A major challenge to achieving industry-scale biomanufacturing of therapeutic alkaloids is the slow process of biocatalyst engineering. Amaryllidaceae alkaloids, such as the Alzheimer’s medication galantamine, are complex plant secondary metabolites with recognized therapeutic value. Due to their difficult synthesis they are regularly sourced by extraction and purification from the low-yielding daffodil Narcissus pseudonarcissus. Here, we propose an efficient biosensor-machine learning technology stack for biocatalyst development, which we apply to engineer an Amaryllidaceae enzyme in Escherichia coli. Directed evolution is used to develop a highly sensitive (EC 50 = 20 μM) and specific biosensor for the key Amaryllidaceae alkaloid branchpoint 4’-O-methylnorbelladine. A structure-based residual neural network (MutComputeX) is subsequently developed and used to generate activity-enriched variants of a plant methyltransferase, which are rapidly screened with the biosensor. Functional enzyme variants are identified that yield a 60% improvement in product titer, 2-fold higher catalytic activity, and 3-fold lower off-product regioisomer formation. A solved crystal structure elucidates the mechanism behind key beneficial mutations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electron Scattering from 1-Methyl-5-Nitroimidazole: Cross-Sections for Modeling Electron Transport through Potential Radiosensitizers

In this study, we present a complete set of electron scattering cross-sections from 1-Methyl-5-Nitroimidazole (1M5NI) molecules for impact energies ranging from 0.1 to 1000 eV. This information is relevant to evaluate the potential role of 1M5NI as a molecular radiosensitizers. The total electron scattering cross-sections (TCS) that we previously measured with a magnetically confined electron transmission apparatus were considered as the reference values for the present analysis. Elastic scattering cross-sections were calculated by means of two different schemes: The Schwinger multichannel (SMC) method for the lower energies (below 15 eV) and the independent atom model-based screening-corrected additivity rule with interferences (IAM-SCARI) for higher energies (above 15 eV). The latter was also applied to calculate the total ionization cross-sections, which were complemented with experimental values of the induced cationic fragmentation by electron impact. Double differential ionization cross-sections were measured with a reaction microscope multi-particle coincidence spectrometer. Using a momentum imaging spectrometer, direct measurements of the anion fragment yields and kinetic energies by the dissociative electron attachment are also presented. Cross-sections for the other inelastic channels were derived with a self-consistent procedure by sampling their values at a given energy to ensure that the sum of the cross-sections of all the scattering processes available at that energy coincides with the corresponding TCS. This cross-section data set is ready to be used for modelling electron-induced radiation damage at the molecular level to biologically relevant media containing 1M5NI as a potential radiosensitizer. Nonetheless, a proper evaluation of its radiosensitizing effects would require further radiobiological experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Machine Learning and IAST-Aided High-Throughput Screening of Cationic and Silica Zeolites for Alkane Capture, Storage, and Separations

We present an approach for quantitatively predicting the temperature-dependent single-component adsorption behavior of linear alkanes in silica and Na-exchanged cationic zeolites using machine learning (ML) models trained from extensive molecular simulations based on force fields with coupled cluster accuracy. A high-performing classification model was developed to distinguish between instances with negligible and non-negligible adsorption. Subsequently, two ML models were trained to predict the single-component adsorption loading and the heat of adsorption at any pressure at 300 K for any zeolite topology and silicon-to-aluminum ratio. The ML models were trained on International Zeolite Association (IZA) zeolites, and their transferability to hypothetical zeolites was successfully validated. We then expand the power of these predictions to adsorbed mixtures at arbitrary temperatures by integrating them with the Clausius–Clapeyron equation and ideal adsorbed solution theory (IAST). This approach was validated and then applied to a temperature swing adsorption separation process to demonstrate its practical utility. We demonstrate how predictions from this ML-enabled approach can allow the selection of high-performing materials that are then validated using detailed molecular simulations based on quantitatively accurate force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A three-dimensional pore-scale model for redox flow battery electrode design analysis

A three-dimensional (3-D) pore-scale model has been developed to construct multiscale fibrous electrodes for redox flow batteries (RFB). New designs, such as biporous electrodes modify electrode structures by creating secondary pores on single carbon fiber to reduce internal battery resistance. Existing pore-scale models only resolve electrodes to the single carbon fiber scale and cannot incorporate recent multiscale electrode designs into numerical models. Our new model aims to bridge this gap and provide a tool to rapidly screen new electrode configurations. Two multiscale electrodes, laser-perforated and biporous electrodes, were investigated at varying operation conditions with the proposed 3-D pore-scale models. The laser-perforated electrode exhibits a reduced pressure drop, but follows the same permeability correlation compared to the corresponding pristine electrode. For the biporous electrode, the added specific surface area and faster reaction kinetics from the secondary pores are the most influential factors leading to improved battery efficiency. However, operating the biporous electrode in limiting current density conditions should be avoided due to the decreased mass transfer efficiency and a more significant voltage loss. Finally, we believe that our 3-D pore-scale model can accelerate the flow battery electrode design process and provide new insights into electrode geometry optimizations.

25 ENERGY STORAGE↗
DOE OSTI2020

How Noninnocent Spectator Species Improve the Oxygen Reduction Activity of Single-Atom Catalysts: Microkinetic Models from First-Principles Calculations

Graphene-based single-atom catalysts are promising alternatives to platinum-based catalysts for fuel cell applications. Different transition metals have been screened using electronic structure methods by estimating onset potentials from the most endergonic elementary reaction step. Here, we calculate onset potentials for the oxygen reduction reaction on metal atoms embedded in N-substituted graphene di-vacancies by virtue of first-principles-informed microkinetic analysis. We find that for more oxophilic metals (Cr, Fe, Mn, and Ru), purely thermodynamic models systematically underestimate onset potentials. Furthermore, the oxophilic metals (Cr, Fe, Mn, and Ru) are oxidized under reaction conditions, leading to an increase in activity compared to their reduced state. Importantly, coadsorbed O m H n species actively participate in the reaction, which requires a dynamic treatment of spectator species. These findings highlight the limitations of thermodynamic analyses for electrocatalytic processes, which commonly assume the same oxidation state for each metal, and show that deviations between computational and experimental onset potentials cannot be solely attributed to the shortcomings of the electronic structure methods.

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

All-Glass Metasurfaces for Ultra-Broadband and Large Acceptance Angle Antireflectivity: from Ultraviolet to Mid-Infrared

For many optics technologies, such as display screens, solar cells, laser systems, and eyeglasses, antireflective (AR) coatings are well integrated; these applications frequently benefit from the ability to function as broadband AR. Here, in this work, all-glass metasurfaces are reported on, exhibiting a measured reflectance of 0.18% ± 0.23% per interface, averaged across wavelengths spanning from 350 nm (ultraviolet) to 2350 nm (mid-infrared); to the best of knowledge, this is the first-ever demonstration of an AR layer capable of this. Furthermore, acceptance angles up to 100° (angle of incidence = ±50°) results in % R < 0.6% per interface over the band 350–1300 nm for P-polarization and S-polarization, with wavelength averaged reflectance values 0.04% ± 0.05% and 0.11% ± 0.15%, respectively – another technological first. The process advancements presented here allow for reflectance suppression over a broad range of wavelengths, angles, and polarizations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Precipitate Phase Stability and Mechanical Properties of Alloy 263 and Variants in Wrought or Cast Form

Alloy 263 is a candidate Ni-based superalloy for use in advanced ultra-supercritical (AUSC) power plants that are targeted to operate above 700 °C. Exposure times in this type of environment are considerable with target creep properties specified at 100,000 h making phase stability an important parameter in the alloy selection process. In this investigation, the microstructure of alloy 263 and two modified compositions in both cast and cast/wrought forms were investigated after exposure at 800 °C for various times ranging from 1,000 h to 10,000 h. Tension and creep properties were assessed for all alloys in both forms. Modification to the Ti and Al concentrations successfully slowed down the γ' to η transformation while doubling the γ' fraction. Thin elongated η needles or platelets formed in the wrought products while thicker, plate-like, η precipitates were found in the castings. The effect of the various microstructures on the creep properties were determined using isothermally aged specimens aged at 800 °C for 3,000 h and 10,000 h prior to creep screening. Strong precipitation of the η phase was found to considerably decrease creep life and increase minimum creep rate. By modifying the Ti and Al content, the creep life and ductility of the new formulation tested on specimens isothermally aged for 3,000 and 10,000 h were near that of the nominal alloy in its standard aged condition.

Detrois, Martin↗
DOE OSTI2026

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗
DOE OSTI2026

Entropy-defect synergy for dual luminescence mechanism in spinel: Time-resolved anti-counterfeiting and fingerprint visualization

Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.

Defect project↗
DOE OSTI2022

Low-Pressure Electrolytic Ammonia (LPEA) Production

The project goal was to advance and demonstrate the techno-economic viability of a low-pressure electrolytic ammonia (LPEA) process for producing ammonia from electricity, hydrogen, and nitrogen. The critical enabling technology of the LPEA process is a proton-conducting electrolyte (PCE) developed by EERC and North Dakota State University (NDSU) capable of high proton conductivity (at least 1×10 -2 [0.01] siemens/centimeter [S/cm]) at 200°–300°C. An affordable PCE that works at 200°–300°C has been a major goal of the global electrochemistry industry for over 25 years, because it would enable operation at temperatures high enough to prevent catalyst poisoning and simplify water management and low enough to avoid temperature-driven degradation of fuel cell components comprising materials with differing coefficients of thermal expansion. Also critical to LPEA performance is a cathode catalyst capable of ammonia synthesis at a rate of ≥1×10 -10 moles/second-cm 2 catalyst surface area (mol-s -1 cm -2 ) in screening tests conducted at room temperature, and 1×10 -7 mol-s -1 cm -2 at 200°–300°C for commercial viability.

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

Extraction of valuable chemicals from food waste via computational solvent screening and experiments

About 1.3 billion tons of global food production end up in landfills and composting, leading to significant anthropogenic greenhouse gas (GHG) emissions. Extracting antioxidant and antimicrobial chemicals (flavonoids, phenolic acids, etc.) from food waste is an economically lucrative valorization strategy but is hindered by efficient solvent selection. Here we perform in silico high throughput screening to identify high solubility solvents for key phenolics and reveal more than 100+ higher-performing solvents than the traditional ethanol and methanol. Solubilities of nine shortlisted solvents are measured and found in reasonable agreement with model predictions. Analysis of the Conductor like Screening Model for Real Solvents (COSMO-RS) σ-profiles and Hansen Solubility Parameters reveals that polarity and hydrogen bonding make dimethylformamide (DMF) an excellent single solvent. We showcase the replacement of high-solubility toxic solvents with green mixtures and demonstrate the approach to potato peel waste. As a result, our work provides a blueprint for solvent selection and generates new insights into extraction from food waste.

09 BIOMASS FUELS↗
DOE OSTI2021

Identification of Known and Novel Monomers for Poly(hydroxyurethanes) from Biobased Materials

Sourcing polymers from biobased materials is desirable for a transition to a more sustainable world. However, finding new monomers sourced from biobased molecules requires extensive experimental effort, due to the fact that most biomolecules lack the functional groups or properties needed to serve as a monomer in a particular polymeric system without chemical modification. In this work, we demonstrate a computational screening method to obtain monomers of a non-isocyanate polyurethane (NIPU), polyhydroxyurethane (PHU), from biomolecules. Our method generates candidate monomers from a list of 15 selected biobased starting molecules by performing chemical transformations that are standard to chemical catalysis and organic synthesis on these starting molecules and then screening the results for molecules with moieties that can be used as monomers for a PHU. Product molecules from two generations of reaction, a total number of 20,057, were analyzed automatically to identify molecules that have two or more epoxy or cyclic carbonate functional groups as candidates for further derivatization. These 21 candidate molecules were then subjected to another two generations of reaction, producing a set of 17,913 additional molecules. Further scrutiny of this set for desired functional groups characterizing PHUs and querying against the PubChem database was carried out, and 15 known molecules that are commercially available were identified, with the desirable features that they are predicted to be derived from biobased starting molecules in four or fewer steps. Moreover, molecule space generated from this process was primarily comprised of molecules that were not known to PubChem, indicating the framework also has the ability to generate novel candidate monomers that originate from biobased starting points.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Towards time-resolved MicroED grid preparation using mix-and-inject gas dynamic virtual nozzles

Recent progress in gas dynamic virtual nozzle (GDVN) technologies in combination with high-brilliance synchrotron and X-ray free-electron lasers (XFELs) has allowed the visualization of protein dynamics in crystallo by mixing macromolecular protein crystals with a substrate using tunable mixing times on the order of milliseconds to seconds prior to serial X-ray diffraction data collection. This has become the method of choice for high-resolution structure determination of intermediate states. However, such experiments require large counts of crystals of proper sizes for high-resolution data collection, and premium beam times for screening efforts. Cryogenic microcrystal electron diffraction (MicroED) represents a complementary technique that may be a more accessible avenue for time-resolved nanocrystallography compared with serial X-ray diffraction experiments. MicroED can produce full diffraction datasets from just a few submicrometre-thick crystals, and the approach is more readily accessible, requiring standard cryogenic transmission electron microscopy (TEM) equipment available at many universities and institutes. Cryogenic MicroED, like other forms of cryo-EM, begins with rapidly freezing biological material on electron microscopy grids. In the case of MicroED, micro- to nano-crystals (<500 nm thick) are deposited onto electron microscopy grids and plunge-frozen for subsequent electron diffraction data collection. Here, we have incorporated GDVN technology developed originally for XFEL experiments into the freezing process as a first step towards time-resolved studies. We describe the limited deposition efficiency of the model MicroED protein proteinase K on TEM grids using GDVNs, preceding sample vitrification and successful MicroED data collection. We discuss both the initial results from such experiments and the methodological challenges in developing this approach into a reliable workflow for millisecond-to-second time-resolved structural studies of macromolecules. Our results promise a strategy to deposit crystals on grids using GDVNs and determine high-resolution structures by MicroED, constituting a first step towards development of time-resolved MicroED experiments.

MicroED↗
DOE OSTI2021

Microwave Plasma Flash Pyrolysis for Coal-to-Product Applications

Since 2010, the US coal industry has experienced a precipitous decline, with coal production volumes dropping by as much as 35% according to EIA. This decline is hardly surprising given that 90% of domestic coal use is allocated to electricity production: While coal generation supplied about 45% of the nation's power in 2010, its share is projected to fall to only 22% in 2020. Fortunately, alternative uses for coal as a feedstock rather than as energy source are available. Coal tar is an established feedstock for chemicals and high-value carbon products including carbon fiber and battery-grade graphites. At present, growth of these uses is constrained by the low availability, purity, and yields of currently available coal liquids, and high energy- and CO2-intensity of current methods of production (i.e. coking). Previously reported work conducted in a partnership with Pacific Northwest National Laboratory demonstrated technical and economic viability of flash pyrolysis of coal in a microwave plasma environment at bench scales targeting production of fuel feedstocks (synthetic oil). H Quest’s work since then indicated promise of microwave-derived coal liquids to be uniquely suited for the lower-cost production of carbon materials, including synthetic graphite, carbon fiber, and composites. Low bulk process temperatures, subsecond residence times, and ambient pressure operation enable small-scale deployment, reduce capital and operating costs, and suppress formation of impurities, including QI material, typical in conventional coal tars. With no inherent production of CO2 or water consumption, microwave plasma flash pyrolysis presents a viable route to the sustainable production of both platform chemicals and carbon-based materials. Most recently, H Quest developed a novel, ruggedized microwave plasma reactor, which departs from the proof-of-concept approach and addresses the problems typically encountered in scaling laboratory microwave plasma apparata (e.g. eliminating fragile quartz enclosures prone to coking and fouling). This reactor has been integrated with a 15kW microwave power supply, a pulverized coal injection system, and a product recovery system. A series of screening tests across a range of coals (including hv-, lv-bituminous and subbituminous PRB), entrainment gas flows and compositions and microwave energy inputs are performed to evaluate conversion rates within the novel, scaled-up system, confirm yields of liquid products, and to perform compositional (GC/MS and elemental) analyses of the products. Results of these tests will be presented and discussed.

Skoptsov, George↗