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NASA NTRS2012

Hydrocarbons on Saturns Satellites: Relationship to Interstellar Dust and the Solar Nebula

To understand the origin and evolution of our Solar System, and the basic components that led to life on Earth, we study interstellar and planetary spectroscopic signatures. The possible relationship of organic material detected in carbonaceous meteorites, interplanetary dust particles (IDPs), comets and the interstellar medium have been the source of speculation over the years as the composition and processes that governed the early solar nebula have been explored to understand the extent to which primitive material survived or became processed. The Cassini VIMS has provided new data relevant to this problem. Three of Saturn's satellites, Phoebe, Iapetus, and Hyperion, are found to have aromatic and aliphatic hydrocarbons on their surfaces. The aromatic hydrocarbon signature (C-H stretching mode at 3.28 micrometers) is proportionally significantly stronger (relative to the aliphatic bands) than that seen in other Solar System bodies (e.g., comets) and materials (Stardust samples, IDPs, meteorites) and the distinctive sub-features of the 3.4 micrometer aliphatic band (CH2 and CH3 groups) are reminiscent of those widely detected throughout the diffuse ISM. Phoebe may be a captured object that originated in the region beyond the present orbit of Neptune, where the solar nebula contained a large fraction of original interstellar ice and dust that was less processed than material closer to the Sun. Debris from Phoebe now resident on Iapetus and Hyperion, as well as o Phoebe itself, thus presents a unique blend of hydrocarbons, amenable to comparisons with interstellar hydrocarbons and other Solar System materials. The dust ring surrounding Saturn, in which Phoebe is embedded, probably originated from a collision with Phoebe. Dust ring particles are the likely source of the organic-bearing materials, and perhaps the recently identified small particles of Fe detected on Saturn's satellites. Lab measurements of the absolute band strengths of representative aliphatic and aromatic molecules, together with measurements from the VIMS data, allow us to calculate the number of C atoms to find the relative abundances of C atoms in the two kinds of organic molecules. The strength of the prominent aromatic C-H stretch band relative to the aliphatic band complex in Phoebe and Iapetus indicates that the relative abundance of aromatic to aliphatic carbon is very large (greater than 200). In contract, the aromatic band is nearly imperceptible in spectra of interplanetary dust particles (IDP), returned samples from comet 91P/Wild 2, insoluable carbonaceous material in most meteorites, and the diffuse interstellar dust (DISM) (although aromatics are known in all these materials-here we consider only the spectroscopic signature)

Cruikshank, D. P.↗

DOE OSTI2025

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

CERF↗

DOE OSTI2025

Using leaf and stomatal traits to predict biomass production and water use efficiency in Populus

Climate change is reshaping ecosystems, driving plants to adapt through leaf-trait plasticity that reflects strategies for growth and water use. Predicting biomass production and intrinsic water use efficiency (iWUE) remains challenging because of genetic, taxonomic, and environmental variability. Here, we used eastern cottonwood and Populus hybrids as a model system to test whether easily measurable leaf traits can serve as reliable predictors of performance, and whether adding stomatal and biochemical traits improves predictive power. Across two field sites in Mississippi, leaf mass per area (LMA), biomass production, iWUE, leaf area, and foliar nitrogen ( N %) differed significantly among taxa and sites, while other traits were conserved. Factorial analysis of mixed data (FAMD) revealed distinct clustering of taxa and sites, indicating coordinated variation among leaf and stomatal traits. Pairwise correlations highlighted fundamental trade-offs, with biomass positively related to LMA and petiole length but negatively associated with iWUE, N %, and carbon isotopic ratios (δ 13 C). Leaf temperature and leaf angle varied among taxa and were significantly correlated with LMA and petiole length, suggesting mechanisms of heat dissipation and leaf movability that link simple traits to gas exchange and productivity. Weighted multiple linear regression models explained 80%–91% of variation in biomass production and iWUE. Models using only LMA, petiole length, and stomatal metrics performed nearly as well as those incorporating N %, and δ 13 C, with complex traits adding approximately 10% explanatory power. These results demonstrate that simple morphological traits capture integrated functional trade-offs, while complex traits refine predictions. This tiered approach provides an efficient framework for selecting high-yielding, water-efficient genotypes of Populus and other hardwood species, offering practical pathways to enhance carbon uptake and iWUE under climate change.

biomass production↗

DOE OSTI2020

3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling

Driving range and fast charge capability of electric vehicles are heavily dependent on the 3D microstructure of lithium-ion batteries (LiBs) and substantial fundamental research is required to optimise electrode design for specific operating conditions. Here we have developed a full microstructure-resolved 3D model using a novel X-ray nano-computed tomography (CT) dual-scan superimposition technique that captures features of the carbon-binder domain. This elucidates how LiB performance is markedly affected by microstructural heterogeneities, particularly under high rate conditions. The elongated shape and wide size distribution of the active particles not only affect the lithium-ion transport but also lead to a heterogeneous current distribution and non-uniform lithiation between particles and along the through-thickness direction. Building on these insights, we propose and compare potential graded-microstructure designs for next-generation battery electrodes. To guide manufacturing of electrode architectures, in-situ X-ray CT is shown to reliably reveal the porosity and tortuosity changes with incremental calendering steps.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Advocating Feedback Control for Human-Earth System Applications

This paper proposes a feedback control perspective for Human-Earth Systems (HESs) which essentially are complex systems that capture the interactions between humans and nature. Recent attention in HES research has been directed towards devising strategies for climate change mitigation and adaptation, aimed at achieving environmental and societal objectives. However, existing approaches heavily rely on HES models, which inherently suffer from inaccuracies due to the complexity of the system. Moreover, overly detailed models often prove impractical for optimization tasks. We propose a framework inheriting from feedback control strategies the robustness against model errors, because inaccuracies are mitigated using measurements retrieved from the field. The framework comprises two nested control loops. The outer loop computes the optimal inputs to the HES, which are then implemented by actuators controlled in the inner loop. Potential fields of applications are also identified and a numerical example is provided.

biological system modeling↗

DOE OSTI2021

Detecting forest response to droughts with global observations of vegetation water content

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analogue of the pressure-volume curve, the non-linear relationship between 44 average leaf or branch water potential and water content commonly used in plant hydraulics. The 45 sources of variability in these ecosystem-scale pressure-volume curves and their relationship to 46 forest response to water stress are discussed. We further show to what extent diel, seasonal, and 47 decadal dynamics of VWC reflect variations in different processes relating the tree response to 48 water stress. VWC can also be used for inferring belowground conditions – which are difficult to 49 impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne 50 observational system for VWC, when combined with existing datasets, can capture diel and 51 seasonal water dynamics to advance the science and applications of global forest vulnerability to 52 future droughts.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1995

CFD assessment of the pollutant environment from RD-170 propulsion system testing

Computational Fluid Dynamics (CFD) technology has been used to assess the exhaust plume pollutant environment of the RD-170 engine hot-firing on the F1 Test Stand at Marshall Space Flight Center. Researchers know that rocket engine hot-firing has the potential for forming thermal nitric oxides (NO(x)), as well as producing carbon monoxide (CO) when hydrocarbon fuels are used. Because of the complicated physics involved, however, little attempt has been made to predict the pollutant emissions from ground-based engine testing, except for simplified methods which can grossly underpredict and/or overpredict the pollutant formations in a test environment. The objective of this work, therefore, has been to develop a technology using CFD to describe the underlying pollutant emission physics from ground-based rocket engine testing. This resultant technology is based on a three-dimensional (3D), viscous flow, pressure-based CFD formulation, where wet CO and thermal NO finite-rate chemistry mechanisms are solved with a Penalty Function method. A nominal hot-firing of a RD-170 engine on the F1 stand has been computed. Pertinent test stand flow physics such as the multiple-nozzle clustered engine plume interaction, air aspiration from base and aspirator, plume mixing with entrained air that resulted in contaminant dilution and afterburning, counter-afterburning due to flame bucket water-quenching, plume impingement on the flame bucket, and restricted multiple-plume expansion and turning have been captured. The predicted total emission rates compared reasonably well with those of the existing hydrocarbon engine hot-firing test data.

Wang, Ten-See↗

DOE OSTI2022

Ducted fuel injection with Low-Net-Carbon fuels as a solution for meeting future emissions regulations

Several studies have proven how ducted fuel injection (DFI) reduces soot emissions for compression-ignition engines. Nevertheless, no comprehensive study has investigated how DFI performs over a load range in combination with low-net-carbon fuels. In this study, optical-engine experiments were performed with four different fuels—conventional diesel and three low-net-carbon fuels—at low and moderate load, to measure emissions levels and performance. The 1.7-liter single-cylinder optical engine was equipped with a high-speed camera to capture natural luminosity images of the combustion event. Conventional diesel and DFI combustion were investigated at four different dilution levels (to simulate exhaust-gas recirculation effects), from 14 to 21 mol% oxygen in the intake. At a given dilution level, with commercial diesel fuel, DFI reduced soot by 82% at medium load, and 75% at low load without increasing NO x . The results further show how DFI with dilution reduces soot and NO x without compromising engine performance or other emission types, especially when combined with low-net-carbon fuels. DFI with the oxygenated low-net-carbon blend HEA67 simultaneously reduced soot and NO x by as much as 93 % and 82 %, respectively, relative to conventional diesel combustion with commercial diesel fuel. These soot and NO x reductions occurred while lifecycle CO 2 was reduced by at least 70 % when using low-net-carbon fuels instead of conventional diesel. All emissions changes were compared with future emissions regulations for different vehicle sectors to investigate how DFI can be used to facilitate achievement of the regulations. Finally, the results show how the DFI cases fall below several future emissions regulation levels, rendering less need for aftertreatment systems and giving a possible lower cost of ownership.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Microbiome Aggregated Traits and Assembly Are More Sensitive to Soil Management than Diversity

How soil is managed, particularly for agriculture, exerts stresses upon soil microbiomes, resulting in altered community structures and functional states. Understanding how soil microbiomes respond to combined stresses is important for predicting system performance under different land use scenarios, aids in identification of the most environmentally benign managements, and provides insight into how system function can be recovered in degraded soils. We use a long-established field experiment to study the effects of combined chronic (press) disturbance of the magnitude of organic carbon inputs with acute (pulse) effects of physical disturbance by tillage and chemical disturbance due to inorganic fertilization and pesticide application. We show that because of the variety of ways it can be assessed, biodiversity—here based on microbial small subunit rRNA gene phylotypes—does not provide a consistent view of community change. In contrast, aggregated traits associated with soil microbiomes indicate general loss of function, measured as a reduction of average genome lengths, associated with chronic reduction of organic inputs in arable or bare fallow soils and altered growth strategies associated with rRNA operon copy number in prokaryotes, as well as a switch to pathogenicity in fungal communities. In addition, pulse disturbance by soil tillage is associated with an increased influence of stochastic processes upon prokaryote community assembly, but fungicide used in arable soils results in niche assembly of fungal communities compared to untilled grassland. Overall, bacteria, archaea, and fungi do not share a common response to land management change, and estimates of biodiversity do not capture important facets of community adaptation to stresses adequately.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Structure and identification of the native PLP synthase complex from Methanosarcina acetivorans lysate

Many protein-protein interactions behave differently in biochemically purified forms as compared to their in vivo states. As such, determining native protein structures may elucidate structural states previously unknown for even well-characterized proteins. Here, we apply the bottom-up structural proteomics method, cryoID , toward a model methanogenic archaeon. While they are keystone organisms in the global carbon cycle and active members of the human microbiome, there is a general lack of characterization of methanogen enzyme structure and function. Through the cryoID approach, we successfully reconstructed and identified the native Methanosarcina acetivorans pyridoxal 5′-phosphate (PLP) synthase (PdxS) complex directly from cryogenic electron microscopy (cryo-EM) images of fractionated cellular lysate. We found that the native PdxS complex exists as a homo-dodecamer of PdxS subunits, and the previously proposed supracomplex containing both the synthase (PdxS) and glutaminase (PdxT) was not observed in cellular lysate. Our structure shows that the native PdxS monomer fashions a single 8α/8β TIM-barrel domain, surrounded by seven additional helices to mediate solvent and interface contacts. A density is present at the active site in the cryo-EM map and is interpreted as ribose 5-phosphate. In addition to being the first reconstruction of the PdxS enzyme from a heterogeneous cellular sample, our results reveal a departure from previously published archaeal PdxS crystal structures, lacking the 37-amino-acid insertion present in these prior cases. This study demonstrates the potential of applying the cryoID workflow to capture native structural states at atomic resolution for archaeal systems, for which traditional biochemical sample preparation is nontrivial.

Methanosarcina acetivorans↗

NASA NTRS2009

High-Temperature Modal Survey of a Hot-Structure Control Surface

NASA Dryden is directing a program to test a Carbon-Silicon Carbide (C/SiC) Ruddervator Subcomponent Test Article (RSTA). The RSTA is a truncated version of the full-scale X-37 hot-structure control surface incorporating all major features including the metallic spindle and five major C/SiC quasi isotropic lay-up components secured with C/SiC fasteners. As part of NASA's Aeronautics Research Mission Directorate Hypersonics program, the RSTA will undergo thermal-structural testing to develop an extensive database for future structural design and analysis methodology validation. Ground Vibration Tests (GVTs) are routinely conducted for model validation in supporting flutter analysis for subsonic and supersonic vehicles; however, for hypersonic vehicle applications, GVT techniques are not well-established. New fabrication technologies, high-temperature materials systems, and sensors offer new opportunities to develop techniques for performing GVTs at elevated temperatures. The RSTA is comprised of materials whose stiffness both increases and decreases with increasing temperature. The impact of this type of material system interaction must be understood as it will ultimately affect hypersonic flutter analysis. The test objectives are to perform room-temperature GVTs, develop the capability to conduct high-temperature GVTs and to compare and generate an understanding of the modal characteristics which capture RSTA's material interaction when subjected to temperature varying conditions.

Spivey, Natalie D.↗

DOE OSTI2024

THD-C Sheet: A Novel Nonbenzenoid Carbon Allotrope with Tetra-, Hexa-, and Dodeca-Membered Rings

Here, we propose a novel two-dimensional carbon-based structure with tetra-, hexa-, and dodeca-membered rings, which we refer to by the abbreviated name, THD-C. The structure presents a mixture of sp–sp 2 hybridization and can potentially be synthesized by the topological assembly of 4-ethynyldiphenylacetylene molecules. By employing first-principles calculations, the stability and ease of synthesis of the sheet are investigated and compared with various C-allotropes. We predict its metallic behavior and excellent kinetic and dynamic stability. Due to the crystal structure of the sheet, a strong mechanical anisotropy is observed. The effects of functionalization on the electronic properties of the material are also studied, and different semiconducting systems are obtained. The potential of THD-C for energy storage in metal-based batteries, hydrogen storage, and catalysis is also investigated, and we find a superior performance in comparison to graphite and other allotropes. The quantum confinement effect is investigated by constructing nanoribbons and nanotubes of various sizes. For ribbons, we find that tailor-made electronic and magnetic properties can be obtained and explored in potential spintronic devices. Additionally, we observe that nanotubes are conducting irrespective of their chirality and can potentially be used for capture, storage, and separation of industrially relevant small gas molecules.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Decovalex-2019 (Task A Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task A which was proposed by the DECOVALEX Project and coordinated by the British Geological Survey (BGS), presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. The purpose of Task A under DECOVALEX-2019 is to better understand the processes governing the advective movement of gas in both low-permeability argillaceous repository host rocks and clay-based engineered barriers. Special attention is given to the mechanisms controlling gas entry, flow and pathway sealing and their impact on the performance of the engineered clay barrier. Previous work suggests gas flow may be accompanied by the creation of dilatant pathways whose properties change temporally and spatially within the medium. Thus, new numerical representations for the quantitative prediction of gas migration fluxes through argillaceous rock formations have been developed. These provide an invaluable tool with which to assess the impact of gas flow on repository layout and therefore design of any future facility. In addition, experience gained through this task is of direct relevance to other clay-based engineering issues where immiscible gas flow is a consideration including shale gas, hydrocarbon migration, carbon capture and storage and landfill design.

58 GEOSCIENCES↗

DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗

DOE OSTI2025

Establishing an Early CO 2 Storage Complex in Kemper County, Mississippi: Project ECO 2 S (Phase III) (Final Progress Report)

“Establishing an Early CO 2 Storage Complex in Kemper County, Mississippi (Project ECO 2 S)” is an early mover project within the U.S. Department of Energy (DOE) and National Energy Technology Laboratory’s Carbon Storage Assurance Facility Enterprise, or CarbonSAFE, initiative. Phase III of Project ECO2S advanced the foundational work of Phase II, which confirmed the potential for safely, permanently, and economically storing commercial volumes of carbon dioxide (CO 2 ) in the regionally significant saline reservoir system near Mississippi Power Company’s (MPC) Kemper County Energy Facility. The primary objective of Phase III was to complete detailed site characterization necessary to obtain an Underground Injection Control (UIC) Class VI Permit to Construct from the U.S. Environmental Protection Agency. This involved transitioning from regional geologic assessments to high-resolution site-specific analyses.

03 NATURAL GAS↗

DOE OSTI2022

Thermal Neutron Scattering Law Evaluation for Zirconium Carbide and Critical Mass Calculations

Zirconium carbide (ZrC) is a candidate material for use in advanced high temperature reactors, including space nuclear thermal propulsion applications. Thermal neutron scattering laws (TSLs) are generated for carbon bound in ZrC, C(ZrC), and zirconium bound in ZrC, Zr(ZrC), using ab initio lattice dynamics methods. These evaluations are to be submitted for inclusion in ENDF/B-VIII.1 and use the incoherent approximation for inelastic scattering as well as the new mixed elastic scattering treatment. The application of disordered alloy theory is introduced to appropriately capture the isotopic composition of Zr and C in the elastic scattering cross section. Localized higher energy vibrations in the C(ZrC) phonon density of states that are separated from lower energy modes result in quantized oscillations in the inelastic contributions to the TSL with a significant likelihood of large energy down-scattering and up-scattering interactions, where the latter increases in probability with temperature. The quanta of energy transfer during neutron thermalization is substantially greater than classically expected within the thermal neutron energy range. MC21 critical mass calculations of ZrC mixtures with high-enriched uranium demonstrate an impact of the TSLs when compared to free-gas treatment for 235 U concentrations less than 0.2 g/cm 3 . Additional MC21 critical mass calculations with homogenous mixtures of ZrC and reactor-grade graphite also demonstrate sensitivity to the ZrC TSL for thermal spectrum driven fission systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Scaled-up fabrication of durable and porous adsorbent-coated minichannels on aluminum for CO 2 separation

A method was developed to fabricate zeolite 13X adsorbent-coated minichannels on aluminum for CO₂ adsorption applications in this study. It emphasizes the innovative use of aluminum as a substrate, which offers airtight assembly, paving the way for highly efficient adsorption systems. An optimized coating process was developed using a slurry of Zeolite 13X, yeast, sugar, and xanthan gum, resulting in durable and highly porous layers that enhance CO₂ capture performance. A PETG peeler was designed to remove the top layer of the yeast-engineered adsorbent coatings, revealing a super porous and foamy structure. The teeth of the peeler were designed and fabricated for high repeatability and rapid prototyping. Breakthrough experiments were conducted on the scaled-up adsorbent bed using gas mixtures of 80% CO₂, 20% N₂, and 20% CO₂, 80% N₂ to represent different industrial scenarios. The performance of the bed was evaluated at flow rates of 160 and 190 cm³ min -1 using a Raman Laser Gas Analyzer (RLGA), demonstrating stable adsorption without degradation across multiple cycles. Computational modeling of integral transport phenomena under the chosen experimental conditions was pursued using gPROMS ProcessBuilder™, and the modeling results were compared with those from the tests for adsorption time, which resulted in an error margin of 2% to 9% for the breakthrough time, confirming the easy reproducibility of the design through modeling. This research advances CO₂ capture technologies by providing an effective and scalable solution for producing aluminum-based adsorbent coated beds, supporting industrial carbon capture efforts.

CO2 capture↗

DOE OSTI2026

Meta-analysis of North American Arctic and boreal aboveground biomass datasets: assessing accuracy, dynamics, and similarities

The North American arctic and boreal regions (ABRs) are rapidly warming and experiencing intensifying disturbances. Accurately quantifying aboveground biomass (AGB) is critical for understanding the impacts of these changes on the carbon cycle and for designing climate change mitigation strategies. Several AGB maps have been developed for the North American ABRs, including recent contributions from National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment (ABoVE) campaign. However, these maps differ widely in training data, methodology, and resulting AGB density estimates. Presently, a comprehensive comparative evaluation is lacking, making it difficult for users to select datasets suited to their research or management needs. Here, in this study, we conducted a comparative analysis of nine AGB density datasets across North American ABRs, specifically for Alaska and Canada. We (1) summarized AGB by ecoregion and Canadian provinces, (2) evaluated their accuracy against field-based measurements, (3) analyzed spatial and temporal similarities among datasets, and (4) assessed their ability to capture disturbance (fire and harvest) impacts on AGB. We found substantial variation in regional and local AGB estimates across datasets, with overall accuracy ranging from R 2 = 0.25–0.62 and Bias% from −47.8% to 69.9% when validated against field plots. Despite these differences, most datasets have comparatively consistent spatial patterns in AGB (r > 0.8 for most cases). In contrast, agreement on the temporal patterns of AGB change is generally low. We found datasets with spatial resolutions ⩽300 m are capable of capturing disturbance impacts on AGB dynamics, though sensitivity varies across products. Our findings and dataset summary provide guidance for selecting appropriate AGB datasets for different applications within our study area. Our analysis also highlights the need to decrease map bias and increase capability to detect temporal change to decrease uncertainty of AGB datasets potentially by using training data which is representative of major plant functional types within the mapped area.

ABoVE↗