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Community-Driven Metadata Standards for Agricultural Microbiome Research

Accelerating the pace of microbiome science to enhance crop productivity and agroecosystem health will require transdisciplinary studies, comparisons among datasets, and synthetic analyses of research from diverse crop management contexts. However, despite the widespread availability of crop-associated microbiome data, variation in field sampling and laboratory processing methodologies, as well as metadata collection and reporting, significantly constrains the potential for integrative and comparative analyses. Here we discuss the need for agriculture-specific metadata standards for microbiome research, and propose a list of “required” and “desirable” metadata categories and ontologies essential to be included in a future minimum information metadata standards checklist for describing agricultural microbiome studies. We begin by briefly reviewing existing metadata standards relevant to agricultural microbiome research, and describe ongoing efforts to enhance the potential for integration of data across research studies. Our goal is not to delineate a fixed list of metadata requirements. Instead, we hope to advance the field by providing a starting point for discussion, and inspire researchers to adopt standardized procedures for collecting and reporting consistent and well-annotated metadata for agricultural microbiome research.

59 BASIC BIOLOGICAL SCIENCES↗

Energy Storage Sizing and Operation of an Integrated Utility-Scale PV+ESS Power Plant

Integration of an energy storage system (ESS) into a large-scale grid-connected photovoltaic (PV) power plant is highly desirable to improve performance of the system and overcome the stochastic nature of PV power generation. Algorithms to size ESS within an integrated PV and ESS ( PV+ESS) power plant, conventionally, require a large number of high-resolution samples of PV generation. These algorithms are computationally expensive. In this paper, a two-day optimization algorithm that utilizes n-step constant power output dispatch every day from the PV+ESS power plant is proposed to size the ESS. Additionally, an n-step power dispatch every day through the one-year timeframe based optimization of the size of ESS is also performed. The proposed methods are computationally cheaper and provide acceptable accuracy with respect to the conventional sizing methods. The economics identified from the proposed methods are compared with the typical day-ahead hourly dispatch-based power production from the PV+ESS power plant. This comparison has shown similar economic performance showcasing the accuracy of the proposed methods in sizing the ESS. It also shows the potential for operating PV+ESS power plant in n-step constant power generation mode.

Xia, Qian↗

Flammability and thermal stability of thermoplastic-based composites filled with natural carbon

This investigation characterized flammability and thermal stability for a novel sustainable composite engineered for use in building applications. Flammability and thermal stability of coal plastic composites composed of coal (40–60 wt.%) and high-density polyethylene were compared to commercial wood–plastic composites. Pyrolysis thermogravimetric analysis results indicated that coal plastic composites possessed a single-step decomposition and higher char residue, while wood–plastic composites had two-step decomposition, with the first peak occurring at much lower temperatures. Thermogravimetric analyses in air suggest coal plastic composites, compared to wood–plastic composites and neat high-density polyethylene, were more thermally stable. Flash ignition temperatures for coal plastic composites were higher than high-density polyethylene and wood–plastic composites, while self-ignition temperatures were in the same range as wood–plastic composites. Rate of burning data indicated coal plastic composites were slower burning than wood–plastic composites, with increasing coal content slowing burning rate by 19.9%–27.6%. Cone calorimeter testing showed 27% and 59% reduction in total heat release and total smoke release as coal content increased while coal plastic composite with 60 wt.% coal possessed lower overall flammability in comparison with predominant commercially available wood–plastic composite products. Coal improved composite overall thermal stability and flammability by acting as char former and foaming agent.

Engineering↗

Technoeconomic Evaluation of Solid Oxide Fuel Cell Hydrogen-Electricity Co-Generation Concepts

This report evaluates the cost and performance of several types of Integrated Energy Systems (IES) based on solid oxide fuel cells (SOFCs) to generate power and solid oxide electrolysis cells (SOECs) to produce hydrogen. All cases feature carbon capture at rates exceeding 97 percent. The report also describes the development of optimized steady state process models for each system. These are used to calculate overall electricity and hydrogen production costs using a consistent methodology that facilitates comparisons of these cases to one another and to prior NETL cost and performance estimates. The SOFC and SOEC costs and performance are based on nth-of-a-kind systems and include research and development and learning associated with mass-scale commercial deployment of the technology over the next decade required for commercial utility-scale systems.

08 HYDROGEN↗

Response to “how robust are reductions in modeled estimates from GTAP-BIO of the indirect land use change induced by conventional biofuels?”

Malins et al. (2020) recently published "How robust are reductions in modeled estimates from GTAP-BIO of the indirect land use change induced by conventional biofuels?", provided their narrative from the model improvements in GTAP-BIO over time, made several critical points regarding this model, and argued that the implemented improvements in this model tended to decrease Induce Land Use Changes (ILUC) emissions. Furthermore, they also provided several critical points regarding the Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) emissions model. In this response to Malins et al. we address these critiques point-by-point by providing our detailed responses to key issues: 1) the GTAP-BIO model and its improvements over time; 2) the inclusion of cropland pasture in the model; 3) the observed land use changes in the US that have been the bases for improvements in GTAP-BIO model, 4) the time trends in corn price and yield to challenge the concept of the yield to price response; 5) some sources of land intensification in crop production; 6) the FAO notifications with respect to the comparison between harvested area and arable land; and 7) the GTAP-BIO results for multiple cropping. We also provided responses to Malins et al. critical points regarding the CCLUB emissions model. We hope that this response letter will open more constructive discussion among the LUC modeling community to remain focused on the big picture regarding agriculture's role as a very effective GHG mitigation tool that can shape the new policies to govern the production and consumption of biofuels.

09 BIOMASS FUELS↗

Electrochemical Reduction of Flue Gas Carbon Dioxide to Commercially Viable C2-C4 Products (Final Report)

This is the final scientific/technical report for a DOE project focused on the electrochemical conversion of CO 2 in non-aqueous solvents to novel products. Electrochemical reduction of CO 2 provides an attractive route to produce valuable fuels and chemicals that can simultaneously lower greenhouse gas emissions when powered by renewable electricity. While recent technological advances have shown the feasibility of industrial CO 2 electroreduction, many challenges remain to improve this technology and expand the list of economically viable products. The vast majority of electrochemical CO 2 reduction research has been conducted in aqueous media under neutral to alkaline conditions, leading to commonly reported products including carbon monoxide, formic acid, methane, methanol, ethylene, acetic acid, and ethanol. In comparison, non-aqueous media for CO 2 reduction has been underexplored but represents a possible avenue to yield new products and improved operating conditions. The aim of the project was to convert waste CO 2 in the form of flue gas to a multicarbon C2 - C4 chemical product in a reactor designed to achieve economically competitive values of current density and selectivity. The project strived to advance the technology readiness of an electrochemical CO 2 reduction process in alcohol solvents from the proof-of-concept stage to a device capable of meeting performance metrics for commercial viability. In the initial plan, the University of Louisville researchers were to focus on investigating the electrochemical process and improving the faradaic efficiency for novel C2 – C4 species, while also working on a parallel effort to build a practical electrolysis reactor to markedly increase the CO 2 reduction current density. The reactor development effort also aimed to engineer a dual-electrolyte feed strategy with non-aqueous catholyte and aqueous anolyte to promote water oxidation as the coupling anodic half-reaction to enable a sustainable and economical overall process. At the outset, the University of North Dakota was to investigate the feasibility of operating directly from coal-derived flue gas without separate capture and purification. The research team sought to determine impurity effects and test mitigation strategies, as well as engineer the gaseous feed system for high reactor tolerance to lower CO 2 concentration. In the last half year of the project, the focus was planned to shift to integrating the advances in the catalysis, electrochemical conditions, reactor design, and flue gas compatibility into a fully functional device and improve it for maximum current density and faradaic efficiency for C2 – C4 species. Knowledge of the full system components, constraints, and maximum performance was then to be used as the basis for a thorough technoeconomic analysis (TEA) and life cycle analysis (LCA) at the end of the project.

01 COAL, LIGNITE, AND PEAT↗

Reactions of U + with H 2 , D 2 , and HD Studied by Guided Ion Beam Tandem Mass Spectrometry and Theory

The kinetic energy-dependent reactions of the atomic actinide uranium cation (U + ) with H 2 , D 2 , and HD were examined by guided ion beam tandem mass spectrometry. An average 0 K bond dissociation energy of D 0 (U + – H) = 2.48 ± 0.06 eV is obtained by analysis of the endothermic product ion cross sections. Quantum chemistry calculations were performed for comparison with experimental thermochemistry, including high-level CASSCF–CASPT2–RASSI calculations of the spin–orbit corrections. CCSD(T) and the CASSCF levels show excellent agreement with experiment, whereas B3LYP and PBE0 slightly overestimate and the M06 approach badly underestimates the bond energy for UH + . Theory was also used to investigate the electronic structures of the reaction intermediates and potential energy surfaces. The experimental product branching ratio for the reaction of U + with HD indicates that these reactions occur primarily via a direct reaction mechanism, despite the presence of a deep-well for UH 2 + formation according to theory. The reactivity and hydride bond energy for U + are compared with those for transition metal, lanthanide, and actinide cations, and periodic trends are discussed. Furthermore, these comparisons suggest that the 5f electrons on uranium are largely core and uninvolved in the reactive chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Robustness of neutron star merger simulations to changes in neutrino transport and neutrino-matter interactions

Binary neutron star mergers play an important role in nuclear astrophysics: Their gravitational wave and electromagnetic signals carry information about the equation of state of cold matter above nuclear saturation density, and they may be one of the main sources of r-process elements in the Universe. Neutrino-matter interactions during and after merger impact the properties of these electromagnetic signals and the relative abundances of the produced r-process elements. Existing merger simulations are, however, limited in their ability to realistically model neutrino transport and neutrino-matter interactions. Here, we perform a comparison of the impact of the use of state-of-the art two-moment or Monte Carlo transport schemes on the outcome of merger simulations, for a single binary neutron star system with a short-lived neutron star remnant [(5–10) ms]. We also investigate the use of different reaction rates in the simulations. While the best transport schemes generally agree well on the qualitative impact of neutrinos on the system, differences in the behavior of the high-density regions can significantly impact the collapse time and the properties of the hot tidal arms in this metastable merger remnant. The chosen interaction rates and transport algorithm as well as recent improvements by Radice et al. to the two-moment algorithms can all contribute to changes at the (10–30)% level in the global properties of the merger remnant and outflows. Furthermore, the limitations of previous moment schemes fixed by Radice et al. also appear sufficient to explain the large difference that we observed in the production of heavy-lepton neutrinos in a previous comparison of Monte Carlo and moment schemes in the context of a low-mass binary neutron star system.

79 ASTRONOMY AND ASTROPHYSICS↗

Inclusive production cross sections at N 3 LO

We present for the first time the inclusive cross section for associated Higgs boson production with a massive gauge boson at next-to-next-to-next-to-leading order in QCD. Furthermore, we introduce n3loxs, a public, numerical program for the evaluation of inclusive cross sections at the third order in the strong coupling constant. Our tool allows to derive predictions for charged- and neutral-current Drell-Yan production, gluon- and bottom-quark-fusion Higgs boson production and Higgs boson associated production with a heavy gauge boson. We discuss perturbative and parton distribution function (PDF) uncertainties of the aforementioned processes. We perform a comparison of global PDF sets for a variety of process including associated Higgs boson production and observe 1σ deviations among predictions for several processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Life Cycle Assessment of Pasture-based Agrivoltaic Systems: Emissions and Energy Use of Integrated Rabbit Production

Agrivoltaic systems, which deliberately maximize the utility of a single parcel of land for both solar photovoltaic (PV) electricity production and agriculture, have been demonstrated as a viable technology that can ameliorate competing land uses and meet growing energy and food demands efficiently. The goal of this study is to assess the environmental impacts of a novel pasture-based agrivoltaic concept: co-farming rabbits and solar PV. A life cycle assessment (LCA) quantified the impacts of 1) the integrated agrivoltaic concept in comparison to conventional practices including 2) separate rabbit farming and PV production and 3) separate rabbit farming and conventional electricity production. The impact assessment methods employed to determine the environmental impacts were IPCC 2013 global warming potential 100a V1.03 and fossil energy demand V1.11. The results indicate that the pasture-based agrivoltaic system produces the least amount of greenhouse gas emissions (3.8 million kg CO₂ equivalent) and demands the least amount of fossil energy (46 million MJ) per functional unit of cumulative MWh output of electricity and cumulative kg of meat over 30 years in comparison to the two other scenarios under study. The pasture-based agrivoltaic system features a dual synergy that consequently produces 69.3% less emissions and demands 82.9% less fossil energy compared to non-integrated production. The potential for agrivoltaic systems to significantly reduce environmental impacts revealed by this LCA, which was limited to emissions and fossil energy demand, demonstrates that integrated solar and pasture-based agricultural systems are superior to conventional practices in terms of their comparatively lower emission and energy intensity. These findings provide empirical support for increased agrivoltaic system development more broadly.

14 SOLAR ENERGY↗

Cosmogenic neutron production in water at SNO+

Accurate measurement of the cosmogenic muon-induced neutron yield is crucial for constraining a significant background in a wide range of low-energy physics searches. Although previous underground experiments have measured this yield across various cosmogenic muon energies, SNO+ is uniquely positioned due to its exposure to one of the highest average cosmogenic muon energies at 364 GeV. Using ultrapure water, we have determined a neutron yield of 𝑌 𝑛 = (3.3⁢8$^{+0.23}_{−0.30}$) × 10 −4 cm 2 g −1 𝜇 −1 at SNO+. Comparison with simulations demonstrates clear agreement with the FLUKA neutron production model, highlighting discrepancies with the widely used GEANT 4 model. Furthermore, this measurement reveals a lower cosmogenic neutron yield than that observed by the SNO experiment, which used heavy water under identical muon flux conditions. This result provides new evidence that nuclear structure and target material composition significantly influence neutron production by cosmogenic muons, offering fresh insight with important implications for the design and background modeling of future underground experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

tapir: A tool for topologies, amplitudes, partial fraction decomposition and input for reductions

The demand for precision predictions in the field of high energy physics has dramatically increased over recent years. Experiments conducted at the LHC, as well as precision measurements at the intensity frontier such as Belle II require equally precise theoretical predictions to make full use of the acquired data. To match the experimental precision, second-, third- and, for certain quantities, even higher-order calculations in perturbative quantum field theory are required. To facilitate such calculations, computer software automating as many steps as possible is required. Yet, each calculation poses different challenges and thus, a high level of configurability is required. In this context we present tapir: a tool for identification, manipulation and minimization of Feynman integral families. It is designed to integrate in toolchains based on the computer algebra system FORM, the use of which is common practice in the field. tapir can be used to reduce the complexity of multi-loop problems with cut-filters, topology mapping, partial fraction decomposition and alike. Program Title:tapir CPC Library link to program files:https://doi.org/10.17632/ptc9t46xyn.1 Developer's repository link:https://gitlab.com/tapir-devs/tapir Licensing provisions: GPLv3 Programming language:python 3, C++ Nature of problem: Multi-loop computations require the automatization of a large number of different tasks related to Feynman integral topologies. Among them are the identification and minimization of integral topologies, partial fraction decomposition of topologies in the case of linearly dependent propagators as well as mapping scalar products of loop momenta to scalar functions. Solution method: The minimization of topologies is performed by comparison of their respective Nickel indices [1], even further minimization utilizes Pak's algorithm [2]. To efficiently map scalar products of loop momenta to scalar functions FORM [3] code is generated. Additional comments including restrictions and unusual features: Minimization based on Pak's algorithm slows down for many lines and scales. A coarser minimization using the Nickel indices, however, is still possible. [1]B. Nickel, D. Meiron, G.A.J. Baker, Compilation of 2-pt and 4-pt graphs for continuous spin model, Report, University of Guelph, 1977.[2]A. Pak, J. Phys. Conf. Ser. 368 (2012) 012049, https://doi.org/10.1088/1742-6596/368/1/012049, arXiv:1111.0868.[3]B. Ruijl, T. Ueda, J. Vermaseren, FORM version 4.2, arXiv:1707.06453, 7 2017.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multivariate degradation modeling using generalized cauchy process and application in life prediction of dye-sensitized solar cells

Recently, the Generalized Cauchy (GC) process has been applied to capture a Long Memory (LM) phenomenon in product degradation modeling and life prediction. Compared with the traditional fractional Brownian motion that captures the LM using a single Hurst parameter, the GC process has two free parameters (Hurst and fractal dimension parameters) that flexibly capture both global LM and local irregularity. However, all existing GC-based degradation models are for a single Degradation Characteristic (DC). In this article, motivated by a real degradation problem of dye-sensitized solar cells that jointly exhibits multiple DCs, global LM, local irregularity and DC-wise cross-correlation, we propose a novel GC-based Multivariate Degradation Model (GC-MDM) to simultaneously capture the aforementioned effects. A maximum likelihood estimation approach is developed to estimate parameters of the GC-MDM. Subsequently, product life prediction based on the GC-MDM is developed. The proposed GC-MDM is validated through a simulation study and a physical experiment of dye-sensitized solar cells. Furthermore, results show that the proposed GC-MDM fundamentally improves the life prediction accuracy in comparison with conventional degradation models which significantly misestimate the uncertainty of product life.

14 SOLAR ENERGY↗

Cool flame chemistry of diesel surrogate compounds: n -Decane, 2-methylnonane, 2,7-dimethyloctane, and n -butylcyclohexane

Elucidating the formation of combustion intermediates is crucial to validate reaction pathways, develop reaction mechanisms and examine kinetic modeling predictions. While high-temperature pyrolysis and oxidation intermediates of alkanes have been thoroughly studied, comprehensive analysis of cool flame intermediates from alkane autoxidation is lacking and challenging due to the complexity of intermediate species produced. Here, jet-stirred reactor autoxidation of four C 10 alkanes: n -decane, 2-methylnonane, 2,7-dimethyloctane, and n -butylcyclohexane, as model compounds of diesel fuel, was investigated from 500 to 630 K using synchrotron vacuum ultraviolet photoionization molecular beam mass spectrometry (SVUV-PIMS). Around 100 intermediates were detected for each fuel. The classes of molecular structures present during the autoxidation of the representative paraffinic functional groups in transport fuels, i.e., n -alkanes, branched alkanes, and cycloalkanes were established and were found to be similar from the oxidation of various alkanes. A theoretical approach was applied to estimate the photoionization cross sections of the intermediates with the same carbon skeleton as the reactants, e.g., alkene, alkenyl keto, cyclic ether, dione, keto-hydroperoxide, diketo-hydroperoxide, and keto-dihydroperoxide. These species are indicators of the first, second, and third O 2 addition reactions for the four C 10 hydrocarbons, as well as bimolecular reactions involving keto-hydroperoxides. Chemical kinetic models for the oxidation of these four fuels were examined by comparison against mole fraction of the reactants and final products obtained in additional experiments using gas chromatography analysis, as well as the detailed species pool and mole fractions of aforementioned seven types of intermediates measured by SVUV-PIMS. This works reveals that the models in the literature need to be improved, not only the prediction of the fuel reactivity and final products, but also the reaction network to predict the formation of many previous undetected intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In situ deformation of antigorite-olivine two-phase mixtures: Implications for dynamics and seismic anisotropy in the mantle wedge

Water released from hydrous minerals in subducting slabs reacts with the overlying plate, resulting in widespread serpentinization in the mantle wedge. Deformation of serpentinized peridotites has been invoked to explain forearc seismic anisotropy, yet studies of the mechanical properties and deformation behaviors of serpentine-bearing multiphase aggregates remain limited. Here we deformed olivine-antigorite mixtures containing 70, 50, and 20 vol.% of antigorite at 2.5 – 7.6 GPa, 673 K and strain rates of ∼10 –5 –10 –4 s –1 . Elasto-viscoplastic self-consistent simulations, constrained by synchrotron X-ray diffraction (XRD) data, were used to estimate lattice strain, stress–strain partitioning, crystallographic preferred orientations (CPO) development, and aggregate strength. Selected run products were also analyzed by electron backscatter diffraction for comparison with the CPO results obtained from XRD experiments. We found olivine transitions from A- or B-type to C-type when antigorite fraction drops to 20 vol.%, coinciding with a microstructural change from interconnected weak layers to a load-bearing framework (LBF). An additional run on a sample Atg50/Ol50 with preexisting microstructures suggested the formation of LBF was promoted by these microstructures, although the preexisting antigorite CPO has been overprinted at 20.8 % strain and could be erased completely by subsequent deformation in nature. Estimated viscosity of the two-phase mixtures suggests that low-degree serpentinization (≤20 %) in the mantle wedge may increase the strength of olivine-rich peridotite and hinder slab-mantle decoupling, whereas high-degree serpentinization (≥50–70 %) weakens the peridotite and favors decoupling if sufficient viscosity contrast (>10) develops. Seismic anisotropy shows a nonlinear dependence on antigorite fraction: antigorite CPO governs the anisotropy of the mixtures with ≥50 vol.% antigorite, whereas olivine CPO dominates at low fractions (∼20 vol.%). The presence of pre-existing microstructures reduces seismic anisotropy of the deformed mixtures, however the persistence of pre-existing CPO in actively subducting slabs remains uncertain, making their significance over geological timescales questionable.

Crystallographic preferred orientation↗

Molecular concentration field design using closed-form steady-state solutions

Control over spatial concentration fields represents a fundamental challenge in designing synthetic biological systems and programmable soft materials. While nature creates morphogen gradients that orchestrate complex developmental processes, synthetic approaches have largely relied on empirical optimization and computationally intensive simulations. Here, we present an analytical framework for steady-state concentration fields generated by finite-sized localized sources in diffusion–degradation systems and derive closed-form solutions for one-, two-, and three-dimensional geometries. By expressing these solutions in dimensionless form, we show that gradient steepness and spatial structure are organized by the Thiele modulus, which captures the competition between diffusion and degradation length scales. The analysis reveals distinct design regimes: in degradation-dominated systems, gradient shape is governed by exponential decay and becomes dimension-independent, whereas in diffusion-dominated systems, gradient magnitude and extent follow dimension-dependent power-law scaling. Building on these results, we introduce a quantitative design strategy that uses threshold-based criteria to program concentration ranges by tuning physically accessible parameters, most directly the production rate, while holding transport and degradation properties fixed. Comparisons with numerical solutions and reported experimental systems demonstrate consistency with the predicted scaling behavior. Together, this work provides a generalizable and physically transparent framework for designing steady-state concentration fields in synthetic biological and soft matter systems, enabling predictive control of gradient-mediated organization without reliance on extensive numerical optimization.

Kim, Dong Woo [Johns Hopkins University, Baltimore↗

Nano-Engineered Catalyst Supported on Ceramic Hollow Fibers for the Utilization of CO 2 in Dry Reforming to Produce Syngas

The objective of this project was to develop a novel catalytic reactor containing nano-engineered catalysts for the utilization of CO 2 (captured from coal-fired power plants and other CO 2 emitting sources) in dry methane reforming (DMR) (CO 2 + CH 4 → 2 H 2 + 2 CO) to produce synthesis gas (syngas). The technology aims to reduce CO2 emissions by developing beneficial uses for CO 2 from coal-fired power plants. It also offers an alternative to mitigate CO 2 emissions in areas where geologic storage may not be an optimal solution and/or utilization could significantly offset the costs of carbon capture and sequestration. The nano-engineered Ni-based catalyst was prepared by atomic layer deposition (ALD). The Ni particles were as small as ~2-4 nm. The nano-engineered catalyst showed CH 4 conversion >95%, H 2 /CO ratio in the range of 0.7-1.0, and CH 4 reforming rate as high as 2,500 L/h/gNi at 850 ºC and pressure of 15-25 psia. The Ni-based ALD catalyst also showed good stability in DMR reaction during a 200-h continuous operation at 850 °C. This is due to strong bonding between the nanoparticles and substrates since the Ni nanoparticles were chemically bonded to the substrate during the ALD process. The high thermal stability maintains the high dispersion of Ni nanoparticles, which can inhibit coke formation because their step edges are small enough to limit carbon nucleation and growth. Technoeconomic analysis (TEA) indicates the levelized cost of syngas (LCOS) is $172/ton with our technology, which is lower than the equivalent (molar) cost of hydrogen produced by steam methane reforming (SMR) or autothermal reforming (ATR). The major operating cost is natural gas feed and fuel, and the levelized cost is highly sensitive to the price of natural gas and relatively insensitive to the CAPEX. Revenues from syngas could have a significant impact on the net cost of electricity (COE), depending on the cost of natural gas and the selling price of syngas, estimated at $36 per MWh if the syngas were sold at $195 per ton. Following DOE NETL’s guidance, a lifecycle analysis (LCA) was conducted to compare with SMR. The functional unit for the basis of comparison was defined as 1kg carbon monoxide in the product stream. The global warming potential (GWP) of our process was found to be 40% lower than the state-of-the-art SMR process. The sensitivity analysis confirms the emissions are most sensitive to the natural gas fuel requirements to deliver heat to the process.

01 COAL, LIGNITE, AND PEAT↗