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At least 343 records · Page 19

Leveraging operational information from wastewater injection wells to evaluate CO 2 injection performance for carbon storage applications in the Appalachian Basin

Abstract Geologic parameters, geophysical logging, injection testing, and operational metrics from wastewater injection wells were integrated to develop a preliminary design of a carbon storage facility in the Appalachian Basin. A scattered group of 10–20 commercial wastewater injection wells dispose off produced water from oil and gas wells in the region, utilizing a sequence of stacked deep saline formations for injection zones. These wastewater injection wells provide practical benchmarks for understanding the feasibility of carbon dioxide (CO 2 ) storage. Geologic models were developed based on characterization data from the wastewater injection wells. Reservoir simulations were calibrated according to injection testing and operational data from the wastewater injection wells. Long‐term operational data on injection flow rates and pressures measured in the wastewater injection wells were especially useful to evaluate the performance of carbon storage applications. The simulations were used to estimate injection pressures, radius of CO 2 saturation, and pressure response for industrial scale CO 2 storage applications. Results were also used to provide a design basis in terms of number of injection wells, well spacing, area of review, injection system components, monitoring plan, and CO 2 pipeline distribution system. The analysis demonstrates that there is sufficient injectivity in the deep saline formations in the west‐central Appalachian Basin to store commercial volumes of anthropogenic CO 2 . The geologic system appears suitable for supporting CO 2 injection rates of 0.5–1.0 million metric tons per year at injection pressures below formation fracture pressure in a single well. The long‐term operational data of wastewater injection wells within the study area suggested a lower permeability‐thickness values than indicated by initial reservoir tests. A workflow for developing realistic permeability values for input into reservoir simulations is presented. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

Valluri, Manoj↗

Lattice Boltzmann simulation of the dissolution of slag in alkaline solution using real-shape particles

Highlights: • A dissolution numerical model was proposed to capture the real dissolution kinetics of slag in alkaline solution. • The log forward dissolution rate of Si was described as a function of NBO/T and solution pH. • A threshold solid volume fraction of 0.688 was found for a voxel in 3D, 63.8% larger than that for a pixel in 2D. • The proposed dissolution numerical model provides a reliable alternative to study the dissolution kinetics of slag. A dissolution numerical model was proposed in this study to capture the real dissolution kinetics of slag in alkaline solution. It consists of three modules, i.e. (i) simulation of the initial particle parking structure of slag in alkaline solution using real-shape particles of slag, (ii) simulation of the chemical reactions between slag and solution based on the transition state theory, and (iii) simulation of the physical transport of aqueous ions using the lattice Boltzmann method. This dissolution numerical model was verified using experimental results, showing reasonable accuracy. After verification, the dissolution numerical model was implemented to study the influences of temperature and particle shape using a proper recipe of slag in alkaline solution. This recipe was designed to avoid solid phase precipitation or gel formation via thermodynamic analysis. The simulation results showed faster dissolution kinetics of slag when using higher temperatures and more irregular particle shapes.

36 MATERIALS SCIENCE↗

Numerical Study of Coupled Water and Vapor Flow, Heat Transfer, and Solute Transport in Variably-Saturated Deformable Soil During Freeze-Thaw Cycles

As climate change intensifies, soil water flow, heat transfer, and solute transport in the active, unfrozen zones within permafrost and seasonally frozen ground exhibit progressively more complex interactions that are difficult to elucidate with measurements alone. For example, frozen conditions impede water flow and solute transport in soil, while heat and mass transfer are significantly affected by high thermal inertia generated from water-ice phase change during the freeze-thaw cycle. To assist in understanding these subsurface processes, the current study presents a coupled two-dimensional model, which examines heat conduction-convection with water-ice phase change, soil water (liquid water and vapor) and groundwater flow, advective-dispersive solute transport with sorption, and soil deformation (frost heave and thaw settlement) in variably saturated soils subjected to freeze-thaw actions. This coupled multiphysics problem is numerically solved using the finite element method. The model's performance is first verified by comparison to a well-documented freezing test on unsaturated soil in a laboratory environment obtained from the literature. Then based on the proposed model, we quantify the impacts of freeze-thaw cycles on the distribution of temperature, water content, displacement history, and solute concentration in three distinct soil types, including sand, silt and clay textures. The influence of fluctuations in the air temperature, groundwater level, hydraulic conductivity, and solute transport parameters was also comparatively studied. The results show that (a) there is a significant bidirectional exchange between groundwater in the saturated zone and soil water in the vadose zone during freeze-thaw periods, and its magnitude increases with the combined influence of higher hydraulic conductivity and higher capillarity; (b) the rapid dewatering ahead of the freezing front causes local volume shrinkage within the non-frozen region when the freezing front propagates downward during the freezing stage and this volume shrinkage reduces the impact of frost heave due to ice formation. This gradually recovers when the thawed water replenishes the water loss zone during the thawing stage; and (c) the profiles of soil moisture, temperature, displacement, and solute concentration during freeze-thaw cycles are sensitive to the changes in amplitude and freeze-thaw period of the sinusoidal varying air temperature near the ground surface, hydraulic conductivity of soil texture, and the initial groundwater levels. Our modeling framework and simulation results highlight the need to account for coupled thermal-hydraulic-mechanical-chemical behaviors to better understand soil water and groundwater dynamics during freeze-thaw cycles and further help explain the observed changes in water cycles and landscape evolution in cold regions.

54 ENVIRONMENTAL SCIENCES↗

Silicate coprecipitation reduces green rust crystal size and limits dissolution-precipitation during air oxidation

Green rusts (GR) are mixed-valence iron (Fe) hydroxides which form in reducing redox environments like riparian and wetland soils and shallow groundwater. In these environments, silicon (Si) can influence Fe oxides’ chemical and physical properties but its role in GR formation and subsequent oxidative transformation have not been studied starting at initial nucleation. Green rust sulfate [GR(SO 4 )] and green rust carbonate [GR(CO 3 )] were both coprecipitated from salts by base titration in increasing % mol Si (0, 1, 10, and 50). The minerals were characterized before and after rapid (24 h) aqueous air-oxidation by x-ray diffraction (XRD), scanning electron microscopy (SEM), Fe extended x-ray absorption fine structure spectroscopy (EXAFS), and N 2 -BET surface area. Results showed that only GR(SO4) or GR(CO3) was formed at every tested Si concentration. Increasing % mol Si caused decreased plate size and increased surface area in GR(CO3) but not GR(SO4). GR plate basal thickness was not changed at any condition indicating a lack of Si interlayering. Air oxidation of GR(SO4) at all % mol Si contents transformed by dissolution and reprecipitation into lepidocrocite and goethite, favoring ferrihydrite with higher % Si content. Air oxidation of GR(CO3) transformed into magnetite and goethite but increasing Si caused GR to oxidize while retaining its hexagonal plate structure via solid-state oxidation. Our results indicate that Si has the potential to cause GR to form in smaller particles and upon air oxidation, Si can either stabilize the plate structure or alter transformation to ferrihydrite.

36 MATERIALS SCIENCE↗

Chemical abrasion: the mechanics of zircon dissolution

Chemical abrasion is a technique that combines thermal annealing and partial dissolution in hydrofluoric acid (HF) to selectively remove radiation-damaged portions of zircon crystals prior to U–Pb isotopic analysis, and it is applied ubiquitously to zircon prior to U–Pb isotope dilution thermal ionization mass spectrometry (ID-TIMS). The mechanics of zircon dissolution in HF and the impact of different leaching conditions on the zircon structure, however, are poorly resolved. We present a microstructural investigation that integrates microscale X-ray computed tomography (µCT), scanning electron microscopy, and Raman spectroscopy to evaluate zircon dissolution in HF. We show that µCT is an effective tool for imaging metamictization and complex dissolution networks in three dimensions. Acid frequently reaches crystal interiors via fractures spatially associated with radiation damage zoning and inclusions to dissolve soluble high-U zones, some inclusions, and material around fractures, leaving behind a more crystalline zircon residue. Other acid paths to crystal cores include the dissolution of surface-reaching inclusions and the percolation of acid across zones with high defect densities. In highly crystalline samples dissolution is crystallographically controlled with dissolution proceeding almost exclusively along the c axis. Increasing the leaching temperature from 180 to 210 °C results in deeper etching textures, wider acid paths, more complex internal dissolution networks, and greater volume losses. How a grain dissolves strongly depends on its initial radiation damage content and defect distribution as well as the size and position of inclusions. As such, the effectiveness of any chemical abrasion protocol for ID-TIMS U–Pb geochronology is likely sample-dependent. We also briefly discuss the implications of our findings for deep-time (U-Th)/He thermochronology.

58 GEOSCIENCES↗

Study of Ionic Mass Transport in Non-Conventional Electrolytes for Energy Storage and Carbon Capture Applications

In the field of energy storage, electrolytes are the materials or liquids used to transport ions or redox active chemicals to facilitate an electrochemical process. Conventional electrolytes are the most common form of electrolyte used and consist of salts dissolved in a liquid solvent medium. While conventional electrolytes are generally inexpensive and work well with lithium-ion batteries, they have many shortfalls however, such as corrosion of the cell, flammability, toxicity, price, and incompatibility with other metals. This project investigates the fundamental properties in nonconventional electrolyte systems with an initial focus on eutectics being made. Using electrochemical methods ( Cyclic Voltammetry (CV), Impedance, Conductance, etc.), we are studying the study of electrolyte systems containing ions used for thermal, chemical, or electrochemical energy storage such as Li + , Mg 2+ , Na + , K + , Al 3+ , CO 3 2- , Cl - , and O 2- . This research looks at how ion mobility effects the electrochemical characteristics and properties in green energy applications.

25 ENERGY STORAGE↗

AWSD Reactive Burn Model for the HMX‐Based High Explosive LX‐04

An Arrhenius–Wescott–Stewart–Davis (AWSD) reactive burn model is applied to describe shock initiation and detonation properties of the HMX-based high explosive LX-04. The parameters in the model are calibrated to data from multiple sources. The thermodynamic equations of state used in the model are calibrated to a combination of thermochemical calculations for HMX and LX-04 as well as experimentally-measured cylinder expansion results for LX-04. The kinetic parameters are calibrated to velocity data from gas gun experiments performed using EDC-32—a high explosive with the same chemical composition as LX-04 but different structural properties, and scaled rate stick data for PBX 9012. The AWSD model is shown to accurately describe the shock initiation and propagation of LX-04. Very good agreement is observed between the available experimental data and the AWSD model output. The presented results constitute an accurate LX-04 reactive burn model for use in engineering-scale models and simulations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Electrolyte Design for Silicon-Based Li-Ion Battery Guided by Chemical Reactivity of Solvents with a Model Silicon Anode

Here, the use of a model compound trimethylsilyllithium was demonstrated to study the chemical reactions of electrolyte with as a principal guide to design electrolyte for silicon-based Li-ion battery. Me 3 Si - anion initiates ring-opening polymerization of EC leading to the formation of poly(ethylene ether carbonate), which subsequently defragments into oligomers and dissolves in electrolyte. FEC was found to react differently, generating LiF and vinylene carbonate (VC). Further reaction of VC with Me 3 SiLi generated poly(hydroxymethylene), which is a nonsoluble polymer and the critical SEI component. The insights from this study have guided the new electrolyte design for the Si-based battery.

25 ENERGY STORAGE↗

Ultraviolet Photooxidation of Smectite-Bound Fe(II) and Implications for the Origin of Martian Nontronites

Clay minerals detected with orbital and in situ instruments in ancient Martian terrains constrain Mars' climate and aqueous alteration history. Early in its history, Mars experienced an atmospheric redox change and iron-bearing clay minerals may preserve the effects of that transition. Ferrous smectites, the thermodynamically predicted product of chemical weathering of basalts under anoxic conditions, may have undergone oxidation by exposure to chemical oxidants in the atmosphere or regolith, or by direct photooxidation at the surface. To assess these potential oxidation pathways, ferrous trioctahedral smectites of varying initial iron content were synthesized and subjected to oxidation by ultraviolet (UV) irradiation. Experimental UV irradiation under an anoxic atmosphere equivalent to approximately 7 years of flux on the Martian surface caused partial oxidation of smectite-bound Fe (Fe 3+ /ΣFe = 16–18%) and octahedral sheet contraction. Metal-OH vibrational bands in visible/near infrared (VNIR) reflectance spectra of oxidized smectites changed in band depth and asymmetry with higher iron content. X-ray diffraction patterns of UV irradiated samples indicate the formation of a mixed di- and trioctahedral smectite or a secondary nontronite phase, possibly on the surfaces of higher iron content smectites. Furthermore, these experiments suggest that UV irradiation is able to oxidize structurally bound iron in smectites without the presence of other chemical oxidants. Photooxidation may have influenced the mineralogy, both syndepositionally and postdepositionally, of Martian alteration assemblages formed near the surface and this process needs not be limited to one part of their formation history.

58 GEOSCIENCES↗

Stochastic machine learning via sigma profiles to build a digital chemical space

This work establishes a different paradigm on digital molecular spaces and their efficient navigation by exploiting sigma profiles. To do so, the remarkable capability of Gaussian processes (GPs), a type of stochastic machine learning model, to correlate and predict physicochemical properties from sigma profiles is demonstrated, outperforming state-of-the-art neural networks previously published. The amount of chemical information encoded in sigma profiles eases the learning burden of machine learning models, permitting the training of GPs on small datasets which, due to their negligible computational cost and ease of implementation, are ideal models to be combined with optimization tools such as gradient search or Bayesian optimization (BO). Gradient search is used to efficiently navigate the sigma profile digital space, quickly converging to local extrema of target physicochemical properties. While this requires the availability of pretrained GP models on existing datasets, such limitations are eliminated with the implementation of BO, which can find global extrema with a limited number of iterations. A remarkable example of this is that of BO toward boiling temperature optimization. Holding no knowledge of chemistry except for the sigma profile and boiling temperature of carbon monoxide (the worst possible initial guess), BO finds the global maximum of the available boiling temperature dataset (over 1,000 molecules encompassing more than 40 families of organic and inorganic compounds) in just 15 iterations (i.e., 15 property measurements), cementing sigma profiles as a powerful digital chemical space for molecular optimization and discovery, particularly when little to no experimental data is initially available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental and Computational Studies of the Production of 1,3-Butadiene from 2,3-Butanediol Using SiO2-Supported H3PO4 Derivatives

Silica-supported phosphoric acid and metal phosphate catalyzed 1,3-butadiene (BDE) production from 2,3-butanediol (2,3-BDO) was studied using experimental and computational techniques. The catalyst was initially tested in a continuous flow reactor using commercially available 2,3-BDO, leading to maximum BDE yields of 63C%. Quantum chemical mechanistic studies revealed 1,2-epoxybutane is a kinetically viable and thermodynamically stable intermediate, supported by experimental demonstration that this epoxide can be converted to BDE under standard reaction conditions. Newly proposed E2 and SN2' elementary steps were studied to rationalize the formation of BDE and all detected side-products. Additionally, using quantum mechanics/molecular mechanics (QM/MM) calculations, we modeled silica-supported phosphate catalysts to study the effect of the alkali metal center. Natural population analysis showed that phosphate oxygen atoms are more negatively charged in CsH2PO4/SiO2 than in H3PO4/SiO2. In combination with temperature-programmed desorption experiments using CO2, the results of this study suggest that the improved selectivity achieved when adding the metal center is related to an increase in the basicity of the catalyst.

butadiene↗

Laminar flame speed measurements of a gasoline surrogate and its mixtures with ethanol at elevated pressure and temperature

Laminar Flame speed measurements of a gasoline surrogate and mixtures of it with ethanol were conducted using a heated, constant-volume vessel. A spherical propagating flame was observed using a high-speed camera, and laminar flame speed was determined therefrom. Here, the gasoline surrogate, which serves as the baseline for the current study, consisted of four components, namely, iso-octane, n-heptane, toluene, and 1-hexene. Different mixtures of the gasoline surrogate and ethanol were studied, governed by the ethanol percentage in the mixture. That is, E0, E30, E50, and E85 mixtures represent 0%, 30%, 50%, and 85% ethanol in the gasoline surrogate mixture by liquid volume, respectively. Initial temperatures of 335, 359, and 408 K and initial pressures of 1 and 3 bar were investigated. The findings of this study are compared to results in the literature, which show good agreement for E0 but some deviation for the E30 blend. In general, the study showed an increase in laminar flame speed as the ethanol percentage increases in the mixture. Similarly, increasing the initial temperature with fixed ethanol percentage resulted in an increase in laminar flame speed, as expected. In contrast, increasing the initial pressure with fixed Ethanol percentage showed a decrease in laminar flame speed. Finally, the results are compared to an existing chemical kinetics model designed for ethanol and gasoline. Although agreement between the model and data is reasonable and mostly within about 10%, some improvement to the kinetics model is needed to uniformly lower the calculated flame speeds.

09 BIOMASS FUELS↗

Conformer-Dependent Chemistry: Experimental Product Branching of the Vinyl Alcohol + OH + O 2 Reaction

The concentration of formic acid in Earth's tropo-sphere is underestimated by detailed chemical models compared to field observations. Phototautomerization of acetaldehyde to its less stable tautomer vinyl alcohol, followed by the OH-initiated oxidation of vinyl alcohol, has been proposed as a missing source of formic acid that improves the agreement between models and field measurements. Theoretical investigations of the OH + vinyl alcohol reaction in excess O 2 conclude that OH addition to the alpha carbon of vinyl alcohol produces formaldehyde + formic acid + OH, whereas OH addition to the β site leads to glycoaldehyde + HO 2 . Furthermore, these studies predict that the conformeric structure of vinyl alcohol controls the reaction pathway, with the anti-conformer of vinyl alcohol promoting α OH addition, whereas the syn-conformer promotes β addition. However, the two theoretical studies reach different conclusions regarding which set of products dominate. We studied this reaction using time-resolved multiplexed photoionization mass spectrometry to quantify the product branching fractions. Our results, supported by a detailed kinetic model, conclude that the glycoaldehyde product channel (arising mostly from syn-vinyl alcohol) dominates over formic acid production with a 3.6:1.0 branching ratio. Additionally, this result supports the conclusion of Lei et al. that conformer-dependent hydrogen bonding at the transition state for OH-addition controls the reaction outcome. As a result, tropospheric oxidation of vinyl alcohol creates less formic acid than recently thought, increasing again the discrepancy between models and field observations of Earth's formic acid budget.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.

Sadayappan, Kayalvizhi↗

Unconventional low temperature decomposition of a saturated hydrocarbon over atomically-dispersed titanium-aluminum-boron catalyst

Sonochemically-synthesized atomically-dispersed titanium-aluminum-boron nanopowder (TiAlB NP) exhibits a remarkable low-temperature catalytic activation of aliphatic C-H bonds at 750 K followed by C-C bond activation thus emerging as a potent low-cost alternative to expensive platinum group metals. Here, the model saturated hydrocarbon, exo-tetrahydrodicyclopentadiene (C10H16), undergoes catalytic decomposition on TiAlB NPs in a chemical microreactor to produce 1,3-cyclopentadiene (c-C5H6), cyclopentene (c-C5H8), and molecular hydrogen (H2) as detected in situ via isomer-selective, single-photon ionization time-of-flight mass spectrometry. Extensive electronic structure theory calculations on model clusters of the catalyst decode a unique synergy among the atomic constituents of the catalyst and chemical bonding in this stepwise, retro Diels Alder reaction: Ti, although insensitive to C-H activation in its metallic state, initiates the catalysis via chemisorption of the hydrocarbon, adjacent B centers readily abstract hydrogen atoms and store them during the catalytic cycle, while Al stabilizes the catalyst structure yet providing space for critical docking sites for the departing hydrocarbons.

Biswas, Souvick↗

Machine learning predictions of high-Curie-temperature materials

Technologies that function at room temperature often require magnets with a high Curie temperature, $T$ C , and can be improved with better materials. Discovering magnetic materials with a substantial $T$ C is challenging because of the large number of candidates and the cost of fabricating and testing them. Using the two largest known datasets of experimental Curie temperatures, we develop machine-learning models to make rapid $T$ C predictions solely based on the chemical composition of a material. We train a random-forest model and a k -NN one and predict on an initial dataset of over 2500 materials and then validate the model on a new dataset containing over 3000 entries. The accuracy is compared for multiple compounds' representations (“descriptors”) and regression approaches. A random-forest model provides the most accurate predictions and is not improved by dimensionality reduction or by using more complex descriptors based on atomic properties. Further, a random-forest model trained on a combination of both datasets shows that cobalt-rich and iron-rich materials have the highest Curie temperatures for all binary and ternary compounds. An analysis of the model reveals systematic error that causes the model to over-predict low-$T$ C materials and under-predict high-$T$ C materials. For exhaustive searches to find new high-$T$ C materials, analysis of the learning rate suggests either that much more data is needed or that more efficient descriptors are necessary.

36 MATERIALS SCIENCE↗

Automated tabletop exfoliation and identification of monolayer graphene flakes

Over the past two decades, graphene has been intensively studied because of its remarkable mechanical, optical, and electronic properties. Initial studies were enabled by manual “Scotch Tape” exfoliation; nearly two decades later, this method is still widely used to obtain chemically pristine flakes of graphene and other 2D van der Waals materials. Unfortunately, the yield of large, pristine flakes with uniform thickness is inconsistent. Thus, significant time and effort are required to exfoliate and locate flakes suitable for fabricating multilayer van der Waals heterostructures. Here, we describe a relatively affordable tabletop device (the “eXfoliator”) that can reproducibly control key parameters and largely automate the exfoliation process. In a typical exfoliation run, the eXfoliator produces 3 or more large (≥ 400 μm 2 ) high-quality graphene monolayer flakes, allowing new users to produce such flakes at a rate comparable to manual exfoliation by an experienced user. Furthermore, we use an automated mapping system and a computer vision algorithm to locate candidate flakes. Our results provide a starting point for future research efforts to identify more precisely which parameters matter for the success of exfoliation and to optimize them.

47 OTHER INSTRUMENTATION↗

Development of an Open-source Alloy Selection and Lifetime Assessment Tool for Structural Components in CSP

Lack of sufficient data on high temperature mechanical and corrosion behavior of structural materials is a huge barrier in the technological maturity of current and future Concentrating Solar Power (CSP) technologies. Rapid development and selection of materials cannot be achieved by expensive and time-consuming acquisition of experimental data. The goal of the proposed work is development of an open-source alloy selection and lifetime prediction tool that will integrate validated physics-based models to describe influence of temperature, alloy composition, environment and component geometry (thickness) on mechanical and corrosion behavior of Ni and Fe-based alloys employed in molten salts/sCO 2 heat exchangers. This one-year project leveraged the extensive dataset on the creep\corrosion behavior of candidate materials generated at ORNL through past projects and input from current collaborations with industrial partners. Based on previous experience and the feedback provided by industry (Brayton Energy and Echogen), three candidate materials of interest, Ni-based alloys 740H, 282 and 625 and application-specific operating conditions (max. temperature of 730 °C and stress of 150 MPa) were identified for the heat exchanger. An extensive corrosion and creep dataset was assimilated for the relevant operating conditions and was supported by detailed characterization of about 100 metallographic cross-sections. The corrosion dataset consisted of scanning electron microscopy images (secondary electron and backscatter electron), measured concentration profiles of alloying elements using energy dispersive X-ray spectroscopy (EDS), widths of denuded zones (dissolution of strengthening phases) and depths of attack in molten KCl-MgCl 2 mixtures using image analyses. The creep dataset comprised of creep rupture data and creep strain curves (for 740H and 282). Coupled thermodynamic-kinetic microstructure-based models were employed to predict the stress-corrosion induced compositional and phase evolutions in the alloy during operation under the identified operating conditions. Reduced order models were developed from advanced physics-based models and were integrated in a user-friendly alloy selection tool. The corrosion model was able to predict the time to a critical Cr concentration at the oxide/alloy interface (chemical lifetime) within ±10% (1 standard deviation) of typical statistical variation in corrosion tests and EDS measurement errors (±0.5 wt%). The initial scope of the project was limited to predict creep rupture times (Larson-Miller parameter). Based on the input provided by industry, the mechanical lifetime of the heat exchanger is governed by accumulated creep strains (2%) rather than creep rupture. To be able to predict the times to specific creep strains, a more extensive creep model development was undertaken largely beyond the initial scope of the project. The continuum damage mechanics creep model was able to predict times to 2% creep strain, t 2% with an accuracy of ±500h. Ultimately, a screening protocol for SiC was generated to demonstrate the pathway for integration of one of the currently immature materials from a commercial adoption standpoint in the current material evaluation tool. The modeling tool developed here is accessible to the science community and stakeholders and lays the foundation for methods that will enable a rapid evaluation of optimum materials for CSP applications and reliable prediction of material degradation thereby considerably reducing operational costs, improving reliability and increasing overhaul intervals. However, the complete potential of such a tool to include a wider range of materials and test conditions can only be realized with a more concentrated combined experimental-characterization-computation effort.

14 SOLAR ENERGY↗