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At least 253 records · Page 14

Extension of Plant Dynamics Code Capabilities for Simulation of TerraPower Pascal Reactor

Argonne National Laboratory has been developing the Plant Dynamics Code (PDC) for design and transient analysis of supercritical carbon dioxide (sCO 2 ) Brayton cycles. In previous analyses with PDC, only indirect sCO 2 cycles, where the heat is being added through a heat exchanger, such as sodium-to-CO 2 HX, were analyzed. Under the U.S. Department of Energy Technology Commercialization Fund (TCF), Argonne cooperated with TerraPower to bring the Plant Dynamics Code to commercial market. The main focus of the TCF project is to extend the application base and the code usability by developing the capabilities to be able to simulate reactor systems with direct sCO 2 cycles. These new PDC capabilities have been developed in application to the TerraPower’s Pascal reactor concept. This report documents the Pascal reactor modeling with the PDC, including simulation of the Pascal split-expansion cycle, the development of the reactor module in the PDC, modeling of the Pascal’s shutdown heat removal system in PDC, and other updates to the code. The report also describes the results of the steady state and transient demonstration of the newly developed code features.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Contrasting Community Assembly Forces Drive Microbial Structural and Potential Functional Responses to Precipitation in an Incipient Soil System

Microbial communities in incipient soil systems serve as the only biotic force shaping landscape evolution. However, the underlying ecological forces shaping microbial community structure and function are inadequately understood. We used amplicon sequencing to determine microbial taxonomic assembly and metagenome sequencing to evaluate microbial functional assembly in incipient basaltic soil subjected to precipitation. Community composition was stratified with soil depth in the pre-precipitation samples, with surficial communities maintaining their distinct structure and diversity after precipitation, while the deeper soil samples appeared to become more uniform. The structural community assembly remained deterministic in pre- and post-precipitation periods, with homogenous selection being dominant. Metagenome analysis revealed that carbon and nitrogen functional potential was assembled stochastically. Sub-populations putatively involved in the nitrogen cycle and carbon fixation experienced counteracting assembly pressures at the deepest depths, suggesting the communities may functionally assemble to respond to short-term environmental fluctuations and impact the landscape-scale response to perturbations. We propose that contrasting assembly forces impact microbial structure and potential function in an incipient landscape; in situ landscape characteristics (here homogenous parent material) drive community structure assembly, while short-term environmental fluctuations (here precipitation) shape environmental variations that are random in the soil depth profile and drive stochastic sub-population functional dynamics.

16S amplicon sequencing↗

Land cover and space use influence coyote carnivory: evidence from stable-isotope analysis

For many species, the relationship between space use and diet composition is complex, with individuals adopting varying space use strategies such as territoriality to facilitate resource acquisition. Coyotes ( Canis latrans ) exhibit two disparate types of space use; defending mutually exclusive territories (residents) or moving nomadically across landscapes (transients). Resident coyotes have increased access to familiar food resources, thus improved foraging opportunities to compensate for the energetic costs of defending territories. Conversely, transients do not defend territories and are able to redirect energetic costs of territorial defense towards extensive movements in search of mates and breeding opportunities. These differences in space use attributed to different behavioral strategies likely influence foraging and ultimately diet composition, but these relationships have not been well studied. We investigated diet composition of resident and transient coyotes in the southeastern United States by pairing individual space use patterns with analysis of stable carbon (δ 13 C) and nitrogen (δ 15 N) isotope values to assess diet. During 2016–2017, we monitored 41 coyotes (26 residents, 15 transients) with GPS radio-collars along the Savannah River area in the southeastern United States. We observed a canopy effect on δ 13 C values and little anthropogenic food in coyote diets, suggesting 13 C enrichment is likely more influenced by reduced canopy cover than consumption of human foods. We also observed other land cover effects, such as agricultural cover and road density, on δ 15 N values as well as reduced space used by coyotes, suggesting that cover types and localized, resident-like space use can influence the degree of carnivory in coyotes. Finally, diets and niche space did not differ between resident and transient coyotes despite differences observed in the proportional contribution of potential food sources to their diets. Although our stable isotope mixing models detected differences between the diets of resident and transient coyotes, both relied mostly on mammalian prey (52.8%, SD = 15.9 for residents, 42.0%, SD = 15.6 for transients). Resident coyotes consumed more game birds (21.3%, SD = 11.6 vs 13.7%, SD = 8.8) and less fruit (10.5%, SD = 6.9 vs 21.3%, SD = 10.7) and insects (7.2%, SD = 4.7 vs 14.3%, SD = 8.5) than did transients. Our findings indicate that coyote populations fall on a feeding continuum of omnivory to carnivory in which variability in feeding strategies is influenced by land cover characteristics and space use behaviors.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Rail Decarbonization Alternatives: Framework and Application

The Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework is a comprehensive industry-oriented tool for simulating the deployment of new energy technologies including biofuels, e-fuels, battery-electric, and hydrogen locomotives. By classifying fuel types into two categories based on deployment requirements, the associated optimal charging/fueling facility location and sizing problem are solved with a five-step framework. Life-cycle analysis (LCA) and techno-economic analysis (TEA) are used to estimate carbon reduction, capital investments, cost of carbon reduction, and operational impacts, enabling sensitivity analysis with operational and technological parameters. Here, the framework is illustrated on lower-carbon drop-in fuels as well as battery-electric technology deployments for the US Eastern and Western Class I railroad networks. Drop-in fuel deployments are modeled as admixtures with diesel in existing locomotives, while battery-electric deployments are shown for varying technology penetration levels and locomotive ranges. When mixed in a 50% ratio with diesel, results show biodiesel’s capacity to reduce emissions at 36% with a cost of $\$$ 0.13 per kilogram of CO 2 reduced, while e-fuels offer a potential reduction of 50% of emissions at a cost of $\$$ 0.22 per kilogram of CO 2 reduced. Battery-electric results for 50% deployment over all ton-miles highlight the value of future innovations in battery energy densities as scenarios assuming 800-mi range locomotives show an estimated emissions reduction of 46% with a cost of $\$$ 0.06 per kilogram of CO 2 reduced, compared with 16% emissions reduction at a cost of $\$$ 0.11 per kilogram of CO 2 reduced for 400-mi range locomotives. The NUFRIEND framework provides a systematic method for comparing different alternative energy technologies and identifying potential challenges and benefits in their future deployments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Wellbore injectivity response to step-rate CO 2 injection: Coupled thermo-poro-elastic analysis in a vertically heterogeneous formation

Safe and permanent carbon geological storages require an elaborate analysis of geomechanical stability. Subsurface injection of CO 2 changes the local temperature and pore pressure and, further, alters the stress due to thermo-poro-elastic responses. A permanent CO 2 storage testing was conducted in the water leg of Cranfield reservoir in Mississippi, USA, where hosted CO 2 enhanced-oil recovery activities. During CO 2 injection, the injection rate was ramped up twice but the bottom-hole pressure did not increase with the imposed injection rates as expected. This unexpected field observation suggests the possibility of an open-mode fracture development at the injector. However, the injector response and potential fracture development have not been rigorously interpreted with detailed near-wellbore temperature and pore pressure change upon the CO 2 injection. In this study, we performed history matching of CO 2 injection using coupled thermo-poro-elastic reservoir simulation to examine the possibility of fracturing. We built a reservoir model including vertical heterogeneity in both petrophysical and geomechanical properties estimated from well-logging analysis and laboratory experiments. The simulation results show that CO 2 injection changes stresses and support the hypothesis of development of an open-mode fracture at the injector during the Cranfield test. The near-injector region exhibits a large temperature reduction up to 55 °C with ensuing effective horizontal stress reduction up to 9.1 MPa. However, a caprock integrity issue is unlikely because of the horizontal stress contrast within layers and low hydraulic communication with the injection zone. This work indicates that the injectant temperature should be considered in the design of high-rate CO 2 injector.

58 GEOSCIENCES↗

XPS analysis of molecular contamination and sp 2 amorphous carbon on oxidized (100) diamond

The efficacy of oxygen (O) surface terminations on diamond is an important factor for the performance and stability for diamond-based quantum sensors and electronics. Given the wide breadth of O-termination techniques, it can be difficult to discern which method would yield the highest and most consistent O coverage. Furthermore, the interpretation of surface characterization techniques is complicated by surface morphology and purity, which if not accounted for will yield inconsistent determination of the oxygen coverage. We present a comprehensive approach to consistently prepare and analyze oxygen termination of surfaces on (100) single-crystalline diamond. We report on x-ray photoelectron spectroscopy (XPS) characterization of diamond surfaces treated with six oxidation methods that include various wet chemical oxidation techniques, photochemical oxidation with UV illumination, and steam oxidation using atomic layer deposition (ALD). Our analysis entails a rigorous XPS peak-fitting procedure for measuring the functionalization of O-terminated diamond. The findings herein have provided molecular-level insights on oxidized surfaces in (100) diamond, including the demonstration of clear correlation between the measured oxygen atomic percentage and the presence of molecular contaminants containing nitrogen, silicon, and sulfur. We also provide a comparison of the sp 2 carbon content with the O1s atomic percentage and discern a correlation with the diamond samples treated with dry oxidation which eventually tapers off at a max O1s atomic percentage value of 7.09 ± 0.40%. Given these results, we conclude that the dry oxidation methods yield some of the highest oxygen amounts, with the ALD water vapor technique proving to be the cleanest technique out of all the oxidation methods explored in this work.

XPS↗

Energy and Techno-Economic Analysis of Bio-Based and Low-Carbon Chemicals and Fuels Production Processes

This presentation will highlight that to decarbonize the fuel and chemicals industry, we must reduce energy usage and decarbonize process heating, which also extends to bio-based and low-carbon chemicals and fuel production processes. Two examples will be given. The first is to compare separation technologies to concentrate 2,3-butanediol (BDO), a biomass-derived intermediate for producing sustainable aviation fuel for commercial aviation decarbonization. The other example shows that decarbonizing methanol production offers numerous beneficial routes toward industrial decarbonization as it is a versatile compound, finding utility as both a fuel and a chemical intermediate. Techno-economic and life cycle analyses provide integrated analysis technical approaches to evaluate the R&D that enables industrial decarbonization.

BIOMASS FUELS↗

Using Image Processing Techniques to Identify and Quantify Spatiotemporal Carbon Cycle Extremes

Rising atmospheric carbon dioxide due to human activities through fossil fuel emissions and land use changes have increased climate extremes such as heat waves and droughts that have led to and are expected to increase the occurrence of carbon cycle extremes. Carbon cycle extremes represent large anomalies in the carbon cycle that are associated with gains or losses in carbon uptake. Carbon cycle extremes could be continuous in space and time and cross political boundaries. Here, we present a methodology to identify large spatiotemporal extremes (STEs) in the terrestrial carbon cycle using image processing tools for feature detection. We characterized the STE events based on neighborhood structures that are three-dimensional adjacency matrices for the detection of spatiotemporal manifolds of carbon cycle extremes. We found that the area affected and carbon loss during negative carbon cycle extremes were consistent with continuous neighborhood structures. In the gross primary production data we used, 100 carbon cycle STEs accounted for more than 75% of all the negative carbon cycle extremes. This paper presents a comparative analysis of the magnitude of carbon cycle STEs and attribution of those STEs to climate drivers as a function of neighborhood structures for two observational datasets and an Earth system model simulation.

Sharma, Bharat↗

Intramolecular carbon isotope signals reflect metabolite allocation in plants

Abstract Stable isotopes at natural abundance are key tools to study physiological processes occurring outside the temporal scope of manipulation and monitoring experiments. Whole-molecule carbon isotope ratios (13C/12C) enable assessments of plant carbon uptake yet conceal information about carbon allocation. Here, we identify an intramolecular 13C/12C signal at tree-ring glucose C-5 and C-6 and develop experimentally testable theories on its origin. More specifically, we assess the potential of processes within C3 metabolism for signal introduction based (inter alia) on constraints on signal propagation posed by metabolic networks. We propose that the intramolecular signal reports carbon allocation into major metabolic pathways in actively photosynthesizing leaf cells including the anaplerotic, shikimate, and non-mevalonate pathway. We support our theoretical framework by linking it to previously reported whole-molecule 13C/12C increases in cellulose of ozone-treated Betula pendula and a highly significant relationship between the intramolecular signal and tropospheric ozone concentration. Our theory postulates a pronounced preference for leaf cytosolic triose-phosphate isomerase to catalyse the forward reaction in vivo (dihydroxyacetone phosphate to glyceraldehyde 3-phosphate). In conclusion, intramolecular 13C/12C analysis resolves information about carbon uptake and allocation enabling more comprehensive assessments of carbon metabolism than whole-molecule 13C/12C analysis.

54 ENVIRONMENTAL SCIENCES↗

Core Analysis E-Reports Produced for the Southwest Regional Partnership on Carbon Sequestration for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, Texas

The submission is three electronic reports (e-reports) produced by Terra Tek, a former Schlumberger company, for and under the oversight of the Southwest Regional Partnership on Carbon Sequestration (SWP). The SWP designed and implemented a coring and core analysis program in conjunction with the previous field operator Chaparral Energy, L.L.C. The main SWP contacts who oversaw the coring and core analysis program, including geologic core descriptions and sample selection for testing by the Terra Tek, are listed below in the Authors section. The three reports are for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, TX, a site of the SWP's CO2 storage and enhanced oil recovery project. The e-reports include many data types that are not listed in full detail here, but may include: geomechanical, geochemical, and petrophysical measurements; white light and UV core photos; spectral gamma logs on the core; and Heterogeneous Rock Analysis logs. Fracture core review reports are included for Wells 13-14 and 32-8. The three e-reports each have many subfolders with the various types of data in spreadsheets, pdfs, image files, or other formats. The main e-reports for each well are listed by the well name. The sub-folder “E-Report” for each well has a Report.html file, which, when opened, will have hyperlinks to the various data sets and information. The files in the zipped folder will need to be extracted for the Report.html files to work properly. These authors thank Joseph Hall, a geologist formerly of Chaparral Energy, L.L.C., for assistance in designing the coring program, his geologic expertise of the Farnsworth Unit, and his assistance with characterizing the core. Christopher Gillespie, of Terra Tek at the time, managed the myriad geomechanical, geochemical, and petrophysical measurements provided by Terra Tek for this project. The core from which the samples were collected for this project are housed at the Subsurface Data and Core Libraries of the New Mexico Bureau of Geology and Mineral Resources, Socorro, New Mexico, USA. Funding for this project is provided by the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) through the Southwest Regional Partnership on Carbon Sequestration (SWP) under Award No. DE-FC26-05NT42591. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. These e-reports describe objective technical results and analysis. Any subjective views or opinions that might be expressed in the reports do not necessarily represent the views of the US Department of Energy or the United States Government.

Caprock↗

Comparative Analysis of Radial and Random Microstructures of Mesophase Pitch Carbon Fibers

Carbon fibers (CF) with radial and random microstructures are produced. Here, these fibers are subjected to identical treatment before being mechanically tested and analyzed with Weibull analysis, with the results revealing a statistically significant difference in tensile strengths of 2.23 GPa for random CF and 1.69 GPa for radial CF. Raman mapping probed the crystalline structure perpendicular to the fiber axis and found a uniform structure, while wide‐angle X‐ray diffraction showed a significant difference of 7.5 Å in the crystallites’ basal lengths parallel to the fiber. Small‐angle X‐ray scattering is completed parallel to the fiber for the first time. A cross‐section Guinier plot of the 1D azimuthal integration is generated assuming symmetric scattering, and the parallel scatterers are found to have a similar length scale to the crystallite's length, validating the testing method. Finally, transmission electron microscopy is completed on the longitudinal cross‐section of each fiber. The radial carbon fiber is found to have a core–shell structure, as evidenced further by fast Fourier transform images. Through all studies, it is shown that the structure developed during mesophase pitch spinning altered the microstructure, thus impacting the mechanical properties, confirming a direct relationship between processing, structure, and properties.

Scherschel, Alexander [Univ. of Virginia, Charlott↗

Cement and concrete as carbon sinks: Transforming a climate challenge into a carbon storage opportunity

Cement and concrete, while traditionally recognized as the main contributors to anthropogenic CO 2 emissions, also have untapped capacity to serve as substantial and scalable carbon sinks. This perspective examines how engineered mineral carbonation can transform cement-based materials into functional carbon storage systems, generating both environmental and economic value. We review the fundamental mechanisms of CO 2 uptake in cementitious systems, highlighting current limitations in reaction kinetics, phase control, and durability under varying environmental conditions. Emphasis is placed on the utilization of alkaline industrial residues and emerging magnesium-based cements, which offer synergistic pathways for carbon sequestration and circular resource use. We further assess the performance trade-offs associated with CO 2 uptake and the feasibility of deploying these technologies on industrial scales. A strategic roadmap is proposed that integrates scientific innovation, regulatory alignment, and carbon accounting in the life cycle to accelerate the adoption of carbon-storing concrete. This perspective provides a comprehensive framework to advance cement and concrete as engineered carbon sinks and supports the transition to a climate-positive construction industry.

Carbon storage↗

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

An Exploratory Approach Using Regression and Machine Learning in the Analysis of Mass Absorption Cross Section of Black Carbon Aerosols: Model Development and Evaluation

Mass absorption cross-section of black carbon (MAC BC ) describes the absorptive cross-section per unit mass of black carbon, and is, thus, an essential parameter to estimate the radiative forcing of black carbon. Many studies have sought to estimate MAC BC from a theoretical perspective, but these studies require the knowledge of a set of aerosol properties, which are difficult and/or labor-intensive to measure. We therefore investigate the ability of seven data analytical approaches (including different multivariate regressions, support vector machine, and neural networks) in predicting MAC BC for both ambient and biomass burning measurements. Our model utilizes multi-wavelength light absorption and scattering as well as the aerosol size distributions as input variables to predict MAC BC across different wavelengths. We assessed the applicability of the proposed approaches in estimating MAC BC using different statistical metrics (such as coefficient of determination (R 2 ), mean square error (MSE), fractional error, and fractional bias). Overall, the approaches used in this study can estimate MAC BC appropriately, but the prediction performance varies across approaches and atmospheric environments. Based on an uncertainty evaluation of our models and the empirical and theoretical approaches to predict MAC BC , we preliminarily put forth support vector machine (SVM) as a recommended data analytical technique for use. We provide an operational tool built with the approaches presented in this paper to facilitate this procedure for future users.

54 ENVIRONMENTAL SCIENCES↗

CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]

Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.

Badgett, Alex↗