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

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At least 217 records · Page 12

Investigations into the Ternary NaF-KF-UF4 Salt System – Phase A

A knowledge gap exists in the data and understanding of fresh fuel salt and irradiated multicomponent fuel salt systems thermophysical properties. Quantifying these properties is necessary for the design and construction of test reactors, as well as the licensing of future commercial molten-salt reactors. To facilitate thermal property determination on a proposed fuel salt composition for Seaborg Technologies, several samples containing depleted uranium tetrafluoride (UF4), sodium fluoride (NaF), and potassium fluoride (KF) were blended, and a melt temperature analysis was performed. From the melting temperature analysis, it was determined that sample Seaborg-7, a ternary salt composition of 26.4UF4-24.7KF-48.9NaF (mol%), was very near a ternary eutectic point. Therefore, thermal properties such as melting temperature, salt stability, density, heat capacity, thermal diffusivity, and viscosity were experimentally determined on the Seaborg-7 salt. These measurements document the baseline properties of fresh fuel salt as a function of temperature, where future experiments on irradiated fuel salt will provide a holistic perspective on the change of thermophysical properties during reactor operations. Several precision instruments were used to collect property data, and instrument calibrations and data collection were performed and documented in a standardized and reproducible manner with meticulous detail. This process ensured that the measurement procedures and resulting data can readily be duplicated elsewhere. The Seaborg-7 salt was shown to be stable at temperatures up to 900°C, as no mass change was observed upon repeated heating and cooling. The peak melting temperature was determined to be 547°C (557°C endset). The enthalpy of fusion (??H?_fus^o) was determined to be 167.5 ± 2.7 J/g while the enthalpy of crystallization (??H?_c^o) was determined to be -147.8 ± 13.3 J/g. In addition to the eutectic melting peak, upon heating, several pre eutectic peaks were observed, occurring at 470°C (onset) and 499°C (peak). Specific heat capacity measurements showed a slightly increasing trend with respect to temperature in the solid phase, while the liquid-specific heat capacity showed a somewhat flat trend with an average value of 106.1 ± 1.24 J/mol·K between 600 to 800°C. Three independent trials using the Seaborg-7 salt determined the density to be ?(T) = 4.908 – 0.000363·T(°C), validated between 32 to 200°C, and ?(T) = 4.808 – 0.00113·T(°C), validated between ~575 to 850°C. Thermal diffusivity was determined for the liquid state and is represented by the linear equation y = 0.1581 + 0.000207·T(°C) between 550 to 850°C. The viscosity was determined from 600 to 800°C and is represented by the exponential fit equation, ? (mPa·s) = 736.58e^(-0.006·T(°C)). This report documents the conclusion of fuel salt thermophysical property measurements for the Seaborg SPP, Phase A project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Biogeochemical Responses and Microbial Community Dynamics Responding to Experimental Hydrogen Storage Conditions

Hydrogen has been identified as a flexible energy carrier with zero or negative carbon emission across multiple energy sectors. There is tremendous capacity for deep geologic storage of H2 but many aspects of feasibility, reliability, safety and the potential for unintended consequences need to be examined. As part of a larger programmatic effort to address the knowledge gaps, we aim to gain a better understanding of reservoir microbial communities and their metabolic and biogeochemical responses to hydrogen storage conditions. In this study we collected and characterized reservoir brine from candidate hydrogen storage sites in the southwestern U.S. for use in a temporal reactor series under blended storage conditions (40% H2, 40% CH4, 20% CO2) at reservoir temperature (60°C).

hydrogen storage↗

PUFFIn Software Modeling for Quality Management

PUFFIn (PENELOPE User Friendly Fast Interface) was designed as a fast and simple Monte Carlo simulation tool for the transport of photons and electrons, with a primary purpose as a learning and education tool for a broad range of static configurations in the radiation processing industry. Development of the PUFFIn software is funded by the Office of Radiological Security (ORS) within the United States National Nuclear Security Administration (NNSA). PUFFIn helps fill the education and knowledge gaps in the industry, as identified in reports by Fermilab (2017) and the IAEA (2020). PUFFIn uses the PENELOPE (NEA-2023) physics engine to perform simulations on static configurations. PUFFIn has support for multiple geometry types from simple, single material simulations to full 3D configurations created from CAD input files or images from X-Ray Tomography scans. PUFFin was designed to be easy for the novice user, it will generate the input and geometry files required by PENLOPE and will display the output plots within the PUFFIn interface. PUFFin is distributed for free but requires a free workshop so users can be adequately trained in its use. Workshops have been presented in the past at Texas A&M university, the Aerial-CRT facility in Strasbourg France and Jakarta Indonesia. PUFFIn simulations have been validated by 10 MeV ebeam experiments done at Aerial-CRT in France (Radiation Physics and Chemistry 222 (2024) 111774). Further user experimental comparisons were made at the medical product hands on workshop at Texas A&M in October 2024.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Direct Radiative Effects of Aerosols at the ARM SGP and TWP Sites (DOE ASR Final Report)

This effort has examined and quantified aerosol direct radiative effects (DREs) and associated uncertainties at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) and Tropical Western Pacific (TWP) sites under both clear and all sky conditions by taking advantage of the advanced ARM long-term comprehensive measurements of aerosol, cloud, radiation, and atmospheric state. This effort has filled the knowledge gap in aerosol DREs at the SGP and TWP under all sky conditions based on the ARM observations.

54 ENVIRONMENTAL SCIENCES↗

U.S. Efforts in Support of Examinations at Fukushima Daiichi - September 2024 Meeting Notes

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. Commercial nuclear power plants. A collaborative U.S. and Japanese effort was initiated in 2014 by the Department of Energy Office of Nuclear Energy to identify Daiichi examination needs and evaluate recent Daiichi examination data to address these needs. This document summarizes information presented at and findings, action items, and recommendations by U.S. and Japanese experts in reactor safety and plant operations during the September 2024 Forensics Effort meeting. Significant safety insights were obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties and knowledge gaps in severe accident modeling progression, these insights continue to be used to assess whether additional updates are needed in guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional safety and economic benefits to the operating fleet and new light water reactor (LWR) and non-LWR designs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

FlowDash Geothermal Energy Enhancer: Where is Next Geothermal Resource? Machine Learning + Multiple Datasets => Geothermal Exploration Indication?

This is the presentation delivered at the 2025 GEODE Datathon competition. GEODE is a consortium of experts that addresses technology and knowledge gaps in geothermal energy, leveraging technology and best practices from the oil and gas industry. NETL team was awarded the 1st place in the engineering track. 2025 GEODE Datathon had a total of 42 teams from top universities and several major industrial companies. This awarded work is founded on a robust idea and innovative approach that uses machine learning coupled to multiple datasets to visualize geothermal “sweet” spots/indications in Great Basin based on the data provided from the GEODE Datathon. The use case also leveraged other datasets and demonstrated insightful and valuable indications for geothermal exploration.

Geothermal energy, Machine learning, Multiple Data↗

Complete Initial Studies in Microstructural Studies of Nuclear Graphite

Nuclear graphite is a critical material for the performance and safety of high-temperature reactors, making its study essential for the successful deployment of next-generation reactors in the United States. During the past year, Oak Ridge National Laboratory (ORNL) has contributed extensively to advancing the understanding of nuclear graphite’s properties, behavior, and applications; particular focus has been given to irradiation effects, oxidation mechanisms, thermal and mechanical performance, and long-term stability under reactor conditions. This report provides an update on the ongoing publications being prepared at ORNL. These studies are collectively intended to build a comprehensive knowledge base on nuclear graphite. The studies focus on key aspects such as microstructural characterization, oxidation behavior, advanced analytical techniques, molten salt infiltration, technique development, and billet-to-billet variability. By summarizing the progress of these publications, this report outlines ORNL’s contributions to the field, identifies knowledge gaps, and proposes future research directions. The findings presented in these studies will help enhance the understanding of nuclear graphite’s behavior, support the qualification of nuclear graphite materials, further the development of new techniques and guidelines for using microscopy techniques, and improve reactor safety and performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Measuring Vibronic Coupling and Ultrafast Charge Delocalization on Nanocrystal Surfaces Using Ligand-Specific Vibrational Probes

The primary goal of this proposal was to measure and quantify how vibronic ligand-exciton interactions at the inorganic-organic interface of semiconductor nanocrystals (NCs) govern femtosecond non-radiative relaxation and charge delocalization mechanisms as a function of nanocrystal and ligand structures – including NC size, shape, and ligand identity. Molecular-scale chemical and physical properties and interactions of surface ligands dictate nanocrystal exciton dynamics on the femto-to-microsecond timescales. Improvements in synthesis, experimental, and theoretical characterizations have enhanced our understanding of NC photophysics. However, quantitative descriptions of complex ligand-exciton interactions at the NC surface have remained elusive, which limits elucidation of relaxation mechanisms that determine overall carrier transfer dynamics at the exciton-ligand interface. Thus, the central motivation for this proposal was to fill a significant knowledge gap for judicious selection of ligand-functionalized nanocrystals for targeted isolation and capture of charge carriers to drive selective organic photocatalytic transformations in NC photocatalysts and NC-assembled photonic materials. Our unique two-pronged experimental approach combining nanocrystal synthesis and ligand-specific nonlinear spectroscopy has resulted in (i) four peer-reviewed publications; (ii) 12+ invited and contributed posters and talks at national and international scientific meetings and seminars, (iii) two completed PhD theses, (iv) training of two postdoctoral researchers, three PhD students, and two undergraduate students, and (v) two manuscripts under preparation.

36 MATERIALS SCIENCE↗

Decision Tree for Variable Selection vs. Impact on Durability for Biomass and Biochar Burial Pathways [Slides]

Quantifying durability for lower-TRL BiCRS pathways has been challenging as limited data are available from real-world projects and long-term experiments, resulting in an overall lack of scientific consensus. We develop a decision tree that aims to summarize the current scientific understanding and state-of-the-art project experience. The decision tree can be used to (1) guide the selection of key variables and evaluate their relative impact on durability, (2) identify data and knowledge gaps for future research.

09 BIOMASS FUELS↗

Transforming Aeration Energy in Water Resource Recovery Facilities (WRRFs) through Suboxic Nitrogen Removal (Final Report)

The objective of this project was to advance two key technological components—aeration control strategies and process design methodologies—to support the development and broader adoption of suboxic biological nitrogen removal (SBNR). The project focused on achieving the following three goals: • Enhance Model Predictive Control (MPC) Technology: Advance the DO/Nmaster MPC platform from its initial 2018 pilot deployment at the Chico Water Resource Recovery Facility in California to full-scale integration. This included partnering with a blower technology commercialization partner and incorporating machine learning (ML) capabilities to enable nationwide deployment. • Bridge Knowledge Gaps in SBNR Process Design: Address fundamental gaps in SBNR process understanding through controlled pilot-scale testing at a dedicated pilot facility. These efforts supported the development of robust kinetic models to inform reliable SBNR control, operational strategies, and design frameworks. • Demonstrate Full-Scale Implementation of Low DO/SBNR with ML: Transition low dissolved oxygen (DO)/SBNR coupled with ML from pilot-scale trials to full-scale demonstration in flow-through biological nutrient removal (BNR) systems, with the goal of enabling scalable, nationwide adoption in activated sludge treatment processes. The project included demonstration of SBNR at the pilot scale as performed by Hampton Roads Sanitation District (HRSD) and at the full-scale as performed by the Los Angeles County Sanitation Districts' (LACSD) Pomona Water Reclamation Plant (POWRP).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report

The Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report outlines key insights and actionable recommendations for accelerating the scale-up of disruptive chemical manufacturing technologies. Convened in October 2024, the workshop brought together approximately fifty experts from academia, industry, national laboratories, and government agencies to address the barriers and solutions for maturing technologies from proof-of-concept to commercialization. The report identifies seven critical themes for enabling faster scale-up. These themes were explored through general discussions and breakout sessions focused on three specific chemical manufacturing technologies—electrochemical, thermochemical, and biological conversion processes. The findings emphasize the importance of interdisciplinary collaboration, robust funding mechanisms, and shared resources to overcome technical barriers and accelerate technology deployment. The report also highlights technology-specific challenges and opportunities, including the need for advanced materials, scalable manufacturing processes, and integrated testing environments. For electrochemical manufacturing processes, durability and material optimization are key priorities, while thermochemical processes require novel reactor designs and better supply chain integration. Biological conversion processes face hurdles in strain engineering, reactor design, and process integration. Across all technologies, the workshop emphasized the importance of leveraging computational tools, standardized protocols, and collaborative networks to address knowledge gaps and technical barriers. By acting on these insights, stakeholders can reduce the timeline for scaling up critical chemical manufacturing technologies, ensuring their timely impact on manufacturing competitiveness, and environmental sustainability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

QUCODE: End-to-End Qubit Co-Design

The design of a quantum computer can be broken down into different steps, e.g., the material science aspect of designing qubits and devices, considerations of controlling the state of the qubits and their environment, the computer science aspects of mapping algorithms to the available primitives of the quantum computer, and the programming of an application in terms of the available algorithms. Research in these areas is currently fairly isolated, and there is framework for an end-to-end design approach where a desired application informs the choice of materials for the qubits and their environment, and vice versa.We identify knowledge gaps and opportunities for research that builds on existing PNNL capabilities.

36 MATERIALS SCIENCE↗

Collaborative Proposal: Improving understanding of the internal structure and dynamics of deep convection using ARM observations and large eddy simulations

Recent observational and large eddy simulation (LES) modeling studies have nearly unanimously supported the view of deep cumulus convection being composed of a series of quasi-spherical bubbles of buoyant air, known as moist thermals. Despite the prevalence of moist thermals in deep convection, a comprehensive theory for the dynamics of these structures is lacking. Most current conceptual models for cumulus convection are based on canonical scaling theories for dry thermals or plumes; however, there is considerable evidence that the behavior of moist thermals differs markedly from these theories. Furthermore, the theoretical basis for most cumulus parameterizations originates from the plume conceptual model, and therefore these parameterizations are inconsistent with the real structure of moist convection. Motivated by the aforementioned knowledge gaps, this “end-to-end” research effort use theory, observations, numerical simulations, and direct improvements to the Zhang-McFarlane (ZM) convection scheme in the global climate Community Atmosphere Model (CAM) to address the following research questions: What key environmental parameters determine whether or not shallow convection will transition into deep convection, in the context of thermal-like updrafts? What factors regulate the size of thermals within cumulus updrafts? How does vertical wind shear influence thermal behavior, and as a consequence, vertical velocity and mass flux profiles and the shallow-to-deep convective transition? What are the critical processes that determine updraft vertical velocities and their connection to the vertical mass flux profile for thermal-like updrafts? Idealized LES modeling will be used in conjunction with theoretical models for the core properties of thermal-like updrafts to better understand key processes that regulate thermal ascent rates and entrainment properties. Thermal-tracking procedures will be used to characterize the behavior of thermals within the LES, and recently developed direct measures of entrainment and detrainment will be used to quantify entrainment/detrainment rates. Building from these results, we will analyze the structure of moist thermals from hemispheric range-height indicator scans taken during the Atmospheric Radiation Measurement Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign, and from “real case” LES of CACTI events. This combined modeling and observational analysis will provide essential validation for the existing body of research on moist thermal dynamics, which is based primarily on modeling studies. With the insight gained from the aforementioned activities, we will modify the Zhang-McFarlane convection scheme to improve its representation of updraft vertical velocity and entrainment rate profiles. These process-level changes will be tested in the Community Atmosphere Model to assess the impact on global climate simulations.

54 ENVIRONMENTAL SCIENCES↗

Large-scale offshore wind farm effects on weather and climate in Puerto Rico (Final Technical Report)

Puerto Rico’s current electricity generation heavily relies on imported fossil fuels. This results in an average cost of electricity higher than the U.S. mainland average in all sectors (residential, commercial, and industrial), despite abundant local offshore wind resources, which have the potential to provide secure, low-cost energy generation and consequent economic prosperity. However, effects on atmospheric and oceanic circulation resulting from large-scale deployments of offshore wind farms have not been previously studied at tropical latitude. This project addressed this knowledge gap through a computational modeling effort designed to capture the coupled dynamics of the atmosphere and the ocean in presence of offshore wind farms. Results indicate that wind farm wakes can alter wind stress, generate Ekman-driven vertical transport, and potentially affect nutrient distribution. While full model coupling remains challenging, progress in parameterization and large-eddy simulations provides a foundation for future research. The project contributes to DOE’s Earth System modeling efforts and supports STEM workforce development.

17 WIND ENERGY↗

Demonstrate new plasticity models for doped UO 2 that capture dislocation mechanisms

In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

CarbStor: Development, Analysis and Modification of Carbon Storing Model Soil Communities

Soil microbial communities carry out a number of key processes including plant growth promotion, bioremediation and cycling of nutrients. Carbon cycling is among the most important of these nutrients that are metabolized and processed by the soil microbial community. Many of the carbon inputs are converted to alternative organic forms of carbon that can be used by plants or act as biomass for microbial growth. However, inorganic forms of carbon can also be produced by soil microbial communities including calcium carbonate (CaCO 3 ). Production of calcium carbonate is beneficial for the ecosystem in several ways: it can stabilize soils and improve soil health, especially denser soils with high clay content, it can act as a method of bioremediation, it can serve as an alternative carbon source for plants and it can be a way to store carbon in soil in a stable, inorganic manner for the long term. While the chemistry surrounding individual species carrying out this process is well known what is lacking is an understanding of how species interact in a community to drive carbonate production. As all microbial species in soil exist in a community setting gaining this knowledge is critical to our predicting and controlling this microbial phenotype to greatly improve soil health. The CarbStor project is focused on developing, analyzing and modifying defined microbial soil consortia that express phenotypes at both the species and community level to convert carbon into recalcitrant stable sources such as precipitated carbonate or microbial necromass. To take full advantage of the soil community for this process we will need to fill several key knowledge gaps (KG), three of which are the focus of CarbStor. KG1: Whether and to what degree microbial communities can be developed that produce precipitated carbon via microbial metabolism. KG2: What interspecies interactions drive the individual member phenotypes in defined communities that lead to carbon precipitation. KG3: How can these interactions be modified to enhance carbon sequestration beyond what native communities are capable of. We hypothesize that in a carbon sequestering community only a subset of species will express phenotypes related to carbon storage processes. We also hypothesize that these phenotypes are expressed as a result of interactions with other species in the community that are not involved in carbon storage processes and that these interactions can be harnessed to enhance community carbon sequestration.

54 ENVIRONMENTAL SCIENCES↗

R&D Effort of Geologic Hydrogen Production at the National Renewable Energy Lab (NREL)

Geologic hydrogen (geoH2) is an emerging technology with massive current market interest and distinct potential to change the paradigm of hydrogen production. Two major subsurface processes influence the amount of geoH2 that are available for energy extraction: 1) geochemical reactions of H2O and Fe2+-bearing rocks which can produce hydrogen in the subsurface environment, where 2) various active microbial communities consume hydrogen as an energy source before the hydrogen reaches the surface. The net gain of hydrogen from these two competing processes dictates the production rate of geoH2. A recent study (Templeton et al., 2024) suggested that for most natural geoH2 systems, five orders of magnitude of production rate enhancement are needed to make geoH2 production economical in the near term. Effective enhancement of the production rate requires an in-depth understanding of the two geoH2 processes, in order to promote the H2-generating geochemical processes and suppress the H2-consuming microbial processes. However, current significant knowledge gaps in these two processes hinders the efforts to formulate strategies to enhance geoH2 production. The National Renewable Energy Laboratory (NREL) is a U.S. Department of Energy National Laboratory with the core mission of leading research, innovation, and strategic partnership to deliver solutions for a clean energy based economy. NREL's extensive research portfolio in hydrogen, bioenergy, geothermal, industrial decarbonization, and energy analysis makes us well positioned to conduct interdisciplinary research and facilitate technology deployment in the geoH2 space. In this presentation, we will discuss ongoing geoH2 research and engagement efforts at NREL, including: 1) geochemical investigation to understand the reaction mechanisms and production rate and potential of different source minerals and rocks, 2) microbiological investigation to understand methanogenesis and acetogenesis in the subsurface geoH2 environment, and identify effective inhibitors for these microbial processes, and 3) preliminary analysis for geoH2 production in the State of Minnesota, where abundant Fe-rich rocks for stimulated geoH2 production and ample opportunity to utilize geoH2 in transforming iron and steel industries are currently available.

08 HYDROGEN↗

Solid Amine CO2 Adsorbent Degradation: Insights from Experiments and Atomistic Simulations

Direct air capture (DAC) has received significant attention this decade as a viable solution to limit global warming, although large-scale deployment is currently not economically feasible. To reach the ambitious cost target set by the U.S. of $100/ton CO2 captured and stored, significant improvements must be made to sorbent lifetime and capacity. Aminosilanes grafted onto silica supports are promising candidates for deployment in DAC systems due to their relatively high oxidative stability and low regeneration temperature. Despite myriad advancements in the field, there still exists a fundamental knowledge gap relating sorbent structure to performance. In this work, we grafted various aminosilanes onto the highly porous silica SBA-15 and characterized both oxidative stability and CO2 capacity. Material properties systematically investigated included amine moiety (primary vs. secondary), silane group structure, number of linkages to the silica support, and co-addition of impregnated amines (e.g., PEI), among others. A fixed bed system was used to execute accelerated degradation studies in the presence of humidity and varying temperatures to simulate realistic operating conditions. Atomistic simulations were combined with the experimental results to gain mechanistic insight, ultimately informing the design of next-generation materials

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗