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Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Opportunities and Challenges for Nuclear-Renewable Hybrid Energy Systems

Nuclear-renewable hybrid energy systems (also known as integrated nuclear-renewable systems) are conceptual systems that have two or more energy inputs and produce two or more products. They maximize profitability, and usually equipment utilization, by adjusting between the products depending upon the availability of resources and market value. For example a nuclear-renewable hybrid energy system that produces electricity and hydrogen would maximize sales of electricity when its price is high and shift to hydrogen production when the electricity price is low. This presentation summarizes the results of several economic analyses of nuclear-renewable hybrid energy systems and they key overall conclusions from those analyses.

economic analysis↗

Robust palladium hydride catalyst for electrocatalytic formate formation with high CO tolerance

Palladium is unique in the electrocatalytic reduction of CO 2 to formate because of its low or even near-equilibrium onset potential. However, the inevitably produced CO molecules poison and deactivate the catalyst surface, resulting in an insufficient operating lifetime (<30 min) for conventional and optimized Pd catalysts. In this work, we present a hydrogen-rich Palladium hydride catalyst (PdH0.5/C) derived from a one-step solvothermal synthesis. This catalyst showed a 93.1 % faradaic efficiency towards formate at – 0.4 V (vs RHE). The working lifetime reached a record of 4 h, which was ~15 times longer than a commercial Pd catalyst and outperformed all previous Pd-based electrocatalysts for CO 2 -HCOO – conversion. The high CO tolerance was attributed to the selectivity improvement induced by lattice hydrogen and the weak CO adsorption strength on diverse active sites (i.e. kink, step, and terrace). Isotopic analysis revealed a direct participation of the lattice hydrogen in the protonation of CO 2 molecules in formate formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrolyzer Supply Chain Readiness Level (SCRL)

The U.S. Department of Energy's (DOE's) Office of Manufacturing and Energy Supply Chains (MESC) is revitalizing the U.S. manufacturing base with over $20 billion of direct investment in manufacturing capacity, industrial decarbonization, and workforce development. This work will provide guidance to MESC and other government organizations as to which supply chain components to invest in to reduce material vulnerability for hydrogen electrolyzers as part of the Modeling, Mapping, and Analysis (MMAC) Consortium.

AEC↗

High Temperature Steam Electrolysis Process Performance and Cost Estimates - DOE Hydrogen Program AMR Presentation

Technology readiness levels (TRLs) of electrolysis systems have dramatically increased in recent years as the interest in clean hydrogen production and decarbonization of transportation, industrial and other sectors increases across the globe. This is especially true of high temperature steam electrolysis (HTSE) / solid oxide electrolysis cell (SOEC) systems which show promise of much higher system efficiencies than other more developed electrolysis technologies. This possibility of higher efficiencies of HTSE / SOEC systems has been previously assumed to be theoretically possible but in recent years it has become less theoretical and more realistic as an increasing amount of suppliers complete lab and pilot tests showing very promising results. Research in the areas of manufacturing techniques, material selection, electrode and electrolyte compositions, and balance of plant size and integration continues at a fast pace as an increasing number of suppliers both internationally and domestically become involved. The advantages of HTSE become more pronounced when HTSE is coupled with nuclear power plants (NPPs). This is because thermal energy produced by the nuclear reactor can be used in a series of heat transfer loops and heat exchangers to vaporize HTSE feedwater, which drastically improves the economics of the process. Idaho National Laboratory (INL) has been very involved in the research and modeling of HTSE systems for a number of years, in collaboration with other national laboratories, academia, and industry stakeholders both on the hydrogen production as well as the hydrogen demand side. The modeling completed over the years on a large variety of projects has led to a wealth of knowledge at INL including in the area of the technoeconomic assessment (TEA) of HTSE systems. TEAs include process modeling of the HTSE systems to calculate system energy requirements and equipment sizing, followed by estimation of capital and operating costs to enable calculation of the levelized cost of hydrogen (LCOH). The TEA work performed has produced incremental improvements and tuning of the methods, assumptions, models, and results of the analyses as well as providing some opportunities for validating these results. The purpose of this document is to record the current baseline HTSE analyses led by INL to show the current status of assumptions and costs of these systems. Given the rapid development of this technology, the variety of suppliers entering the space, and the increasing attention government and industry are giving to such systems, this document may be updated on a periodic basis with updated analysis and assumptions. This document compiles various analyses results and approaches completed over a period of years into a single document to be used as a baseline going forward. It represents what the INL HTSE analysis group assumes to be the internal best estimate of the current operation, costs, and landscape of the HTSE industry state of the art capability for current SOEC technology in an Nth-of-a-Kind (NOAK) plant, which in this study is defined as existence of the manufacturing capacity to support previous deployment of N = 100 count of 25 MWe modular HTSE blocks (with modular equipment component cost reductions specified as following a 95% learning curve). That said, this is a public document and as such so no proprietary data was used or included in this report. There may be HTSE suppliers that have performance specifications, and cost estimates, and test data that differ from the analysis presented in this document. This document is meant to be a best conservative estimate of the technology and not an absolute reference.

08 HYDROGEN↗

Radiation-Induced Interfacial Hydroxyl Transformation on Boehmite and Gibbsite Basal Surfaces

Understanding the radiolytic reactivity of aluminum oxyhydroxide phases widely present in stored nuclear wastes is essential to develop reliable processing approaches. Recent experiments using vibrational sum frequency generation (VSFG), a surface sensitive technique, have shown that rehydration of γ-irradiated boehmite (010) and gibbsite (001) surfaces does not recover the initial hydroxyl density prior to irradiation. In this study, using density functional theory and nudged elastic band calculations, we examine dehydration and rehydration of these surfaces and attendant proton transfer mechanisms. While dehydration of both surfaces is predicted to be energetically unfavorable, rehydration of boehmite (010) is favorable after overcoming an energy barrier of 0.52 eV that relates to the orientation of surface hydroxyls controlling the hydrogen bonding network of adsorbed water. In the case of gibbsite (001), for which the experimental results suggest that rehydration mainly involves the reformation of interlayer hydroxyls, we found that a two-proton transfer mechanism is more likely than a one-proton transfer mechanism, and that it prevents the reorientation of interlayer hydroxyls into intralayer hydroxyls consistent with experimental VSFG findings. A detailed analysis of the effect of surface hydrogen vacancy on the strength of hydrogen bond interactions was performed, which indicates that H 2 and H 2 O are the energetically most favorable product species to form from radiation-induced surface H and/or OH defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

H2@Scale CRADA: CA Research Consort. (Ref. Station, Fueling Perf. Test Device, Station Cap Model)

Heavy-duty (HD) hydrogen stations are an essential part of building a clean energy infrastructure by lowering greenhouse gas emissions and criteria pollutants from the trucking industry. Clean fuel at HD stations also supports energy, environmental, and social justice by preventing pollution near the stations and on truck routes while strengthening U.S. manufacturing and providing pathways to private sector uptake. The goal of the CA Research Consortium is to continue the research partnership between national laboratories, DOE, and California public agencies for the advancement of hydrogen fueling infrastructure for HD vehicles. This cooperative work directly impacts California's transition to Zero Emission Trucks and will provide tools and information that lead to more efficient design, acceptance, and commissioning of these larger capacity, higher flow rate stations serving HD hydrogen trucks such as class 8 trucks in long haul applications.

AMR↗

Two-phase flow numerical analysis of electrode geometry for alkaline water electrolyzers

Hydrogen is a promising component of a future energy-secure and efficient economy, but its competitiveness depends on reducing production costs. One strategy is to operate alkaline water electrolyzers at higher current densities to increase output. However, this intensifies performance losses due to gas bubble accumulation, which blocks transport pathways and deactivates electrochemically active surfaces. Enhancing bubble evacuation through electrode design is therefore essential. Previous studies have explored various approaches — such as modifying surface morphology, applying sonication or pressure modulation, and introducing surfactants — but these efforts have addressed a limited range of conditions due to the complexity of two-phase flow and electrode geometries. Experiments have also largely been focused on either cell level improvements, which lack the information necessary to isolate each contributing factor, or on modified geometries that are not relevant to practical cell operation. From a modeling perspective, conventional Eulerian multiphase models do not track the complex gas–liquid interfacial dynamics and often neglect surface tension and contact angle effects, reducing their predictive accuracy. To provide insights on the effects of different electrode geometries on the performance of alklaine water electrolyzers this work employs an immersed boundary volume-of-fluid method to simulate bubble behavior in 3D porous electrodes. Multiple base electrode geometries, typically used in practice, with varying porosity are evaluated under a constant surface gas generation rate. Simulation data is analyzed to quantify electrode gas coverage, bubble size dynamics and other relevant metrics. Results show that porosity strongly influences bubble accumulation on electrode surfaces, with higher porosity reducing gas coverage, and its not strictly dependent on the electrode geometry. However, the electrode’s base geometry significantly affects gas accumulation at the separator gap, independent of porosity. A foam electrode geometry resulted in the lowest gas coverage of all electrodes with a median volumetric gas coverage of 11%, but at the cost of a 70% reduction in active area compared with the largest surface area electrode, while gyroid electrodes showed the best trade-off between gas coverage, particularly at the separator surface, and electrochemically active area. In conclusion, the results highlight the need for holistic electrode design strategies.

Alkaline↗

Role of Intermolecular Interactions in Deep Eutectic Solvents for CO 2 Capture: Vibrational Spectroscopy and Quantum Chemical Studies

Recent research and reviews on CO 2 capture methods, along with advancements in industry, have highlighted high costs and energy-intensive nature as the primary limitations of conventional direct air capture and storage (DACS) methods. In response to these challenges, deep eutectic solvents (DESs) have emerged as promising absorbents due to their scalability, selectivity, and lower environmental impact compared to other absorbents. However, the molecular origins of their enhanced thermal stability and selectivity for DAC applications have not been explored before. Therefore, the current study focuses on a comprehensive investigation into the molecular interactions within an alkaline DES composed of potassium hydroxide (KOH) and ethylene glycol (EG). Combining Fourier transform infrared (FT-IR) and quantum chemical calculations, the study reports structural changes and intermolecular interactions induced in EG upon addition of KOH and its implications on CO 2 capture. Experimental and computational spectroscopic studies confirm the presence of noncovalent interactions (hydrogen bonds) within both EG and the KOH-EG system and point to the aggregation of ions at higher KOH concentrations. Additionally, molecular electrostatic potential (MESP) surface analysis, natural bond orbital (NBO) analysis, quantum theory of atoms-in-molecules (QTAIM) analysis, and reduced density gradient-noncovalent interaction (RDG-NCI) plot analysis elucidate changes in polarizability, charge distribution, hydrogen bond types, noncovalent interactions, and interaction strengths, respectively. Evaluation of explicit and hybrid models assesses their effectiveness in representing intermolecular interactions. This research enhances our understanding of molecular interactions in the KOH-EG system, which are essential for both the absorption and desorption of CO 2 . The study also aids in predicting and selecting DES components, optimizing their ratios with salts, and fine-tuning the properties of similar solvents and salts for enhanced CO 2 capture efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impacts of hydrogen bonding interactions with Np(v/vi)O 2 Cl 4 complexes: vibrational spectroscopy, redox behavior, and computational analysis

The neptunyl (Np(V)O 2 + /Np(VI)O 2 2+ ) cation is the dominant form of 237 Np in acidic aqueous solutions and the stability of the Np(V) and Np(VI) species is driven by the specific chemical constituents present in the system. Hydrogen bonding with the oxo group may impact the stability of these species, but there is limited understanding of how these intermolecular interactions influence the behavior of both solution and solid-state species. In the current study, we systematically evaluate the interactions between the neptunyl tetrachloride species and hydrogen donors in coordination complexes and in the related aqueous solutions. Both Np(V) compounds (N 2 C 4 H 12 ) 2 [Np(V)O 2 Cl 4 ]Cl (Np(V)pipz) and (NOC 4 H 10 ) 3 [Np(V)O 2 Cl 4 ] (Np(V)morph) exhibit directional hydrogen bonding to the neptunyl oxo group while Np(VI) compounds (NC 5 H 6 ) 2 [Np(VI)O 2 Cl 4 ] (Np(VI)pyr) and (NOC 4 H 10 ) 4 [Np(VI)O 2 Cl 4 ]·2Cl (Np(VI)morph) assemble via halogen interactions. Here, the Raman spectra of the solid-state phases indicate the activation of vibrational bands when there is asymmetry of the neptunyl bond, while these spectral features are not observed within the related solution phase spectra. Density functional theory calculations of the Np(V)pipz system suggest that activation of the ν 3 asymmetric stretch and other combination modes lead to additional complexity within the solid-state spectra. Electrochemical analyses of complexes in the solution phases are consistent with the results of the crystallization experiments as the voltammetric potentials of Np(V)/Np(VI) complexes in the presence of protonated heterocycles differ from the potentials of pure Np(V) and may correlate with the hydrogen bonding interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

Downselection of Cladding Materials for Zirconium Hydride Moderator

This report complete Milestone M3.1.1 — “Cladding downselection: Team will report to ARPA-E on at least two down-selected cladding options—one metallic and one ceramic.” In this milestone, we systematically assess FeCrAl alloys and SiC-based cladding options for a zirconium hydride (ZrHx) moderator in terms of their neutronics, radiation stability, hydrogen permeability, chemical compatibility, and fabricability. The analysis shows that FeCrAl alloys are excellent candidate cladding materials for a ZrHx moderator given their proven radiation stability, acceptable compatibility with ZrHx, and industrially established fabricability. The relative high hydrogen permeability is manageable by introducing a thin layer of an Al 2 O 3 hydrogen permeation barrier on the external surface. The SiC-cladded ZrHx moderator is promising because of its outstanding neutronics performance, excellent radiation stability, and extremely low intrinsic hydrogen permeability. However, potential interactions of SiC and Zr and the challenge in achieving a hermetic SiC-based cladding require further investigation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Pathways to a Sustainable Aviation Ecosystem: Life Cycle Analysis with Blockchain Carbon Accounting

When linked with the National Renewable Energy Laboratory's (NREL's) rigorous life cycle assessment methodologies, blockchain technology can enable aviation stakeholders to quantify and transact on the impacts and benefits of sustainable aviation fuels and technologies. NREL can develop high-fidelity carbon modeling tools that enable apples-to-apples comparisons across technologies, fuels, companies, and jurisdictions.

aviation↗

Hydrogen and Power Co-Production Using Direct sCO 2 Power Cycles

This report presents the techno-economic analysis (TEA) results of integrating a modified autothermal reforming (ATR) hydrogen (H 2 ) production plant with a natural gas-fired, utility-scale power plant based on the direct supercritical carbon dioxide (sCO 2 ) power cycle. In this study, the H 2 production and the power plant are fully integrated in terms of heat, fuel, and carbon capture and storage (CCS). The ATR process has significant waste heat available for heat integration with a direct-fired sCO 2 power plant that benefits the power plant efficiency. The off-gas stream from the modified ATR process is primarily carbon dioxide (CO 2 ), carbon monoxide (CO), and residual H 2 . As supplemental fuel, it has beneficial heating value in the CO and H 2 that can be used in the direct sCO 2 power cycle. Finally, the direct sCO 2 power plant can isolate the CO 2 produced at the facility for CCS.

08 HYDROGEN↗

Overall protein structure quality assessment using hydrogen-bonding parameters

Atomic model refinement at low resolution is often a challenging task. This is mostly because the experimental data are not sufficiently detailed to be described by atomic models. To make refinement practical and ensure that a refined atomic model is geometrically meaningful, additional information needs to be used such as restraints on Ramachandran plot distributions or residue side-chain rotameric states. However, using Ramachandran plots or rotameric states as refinement targets diminishes the validating power of these tools. Therefore, finding additional model-validation criteria that are not used or are difficult to use as refinement goals is desirable. Hydrogen bonds are one of the important noncovalent interactions that shape and maintain protein structure. These interactions can be characterized by a specific geometry of hydrogen donor and acceptor atoms. Systematic analysis of these geometries performed for quality-filtered high-resolution models of proteins from the Protein Data Bank shows that they have a distinct and a conserved distribution. Here, it is demonstrated how this information can be used for atomic model validation.

59 BASIC BIOLOGICAL SCIENCES↗

Strategies for Achieving the DOE Hydrogen Shot Goal: Thermal Conversion Approaches

In July 2021 the United States (U.S.) Department of Energy (DOE) launched the first of a series of Department-wide Energy Earthshot goals designed to accelerate breakthroughs of more abundant, affordable, and reliable clean energy solutions within the decade. The Hydrogen Shot goal seeks to reduce the cost of clean hydrogen to $\$$1 per 1 kilogram in 1 decade ("1 1 1"). Today, thermal conversion of fossil fuels represents the predominant, lowest cost method of hydrogen production. In 2020 approximately 75 percent of global, dedicated hydrogen production was produced via fossil fuels using thermal conversion approaches such as steam reforming and gasification. However, carbon management techniques such as CO 2 capture and sequestration (CCS) and pyrolysis are not widely represented in the current fossil-based hydrogen production fleet. Lowering the cost of clean hydrogen production from commercial and advanced thermal conversion-based technologies is critical for successfully achieving the Hydrogen Shot goal. This report presents the findings from an initial screening analysis of several scenarios that explore cost drivers related to clean hydrogen production. The screening encompasses commercially available and developing thermal conversion technology alternatives as well as factors exogenous to the plant such as feedstock/byproduct pricing, CO 2 pipeline and storage infrastructure costs, and scale to assess potential pathways towards meeting the Hydrogen Shot goal. Additionally, this report presents initial Research and Development (R&D) strategies to advance thermal conversion technology towards meeting the Hydrogen Shot goal.

08 HYDROGEN↗