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DOE OSTI2026

Prospects for exploring non-standard neutrino properties with argon-based CEvNS experiments

Coherent elastic neutrino-nucleus scattering (CEvNS) provides a powerful frame-work for testing the Standard Model (SM) and searching for new physics at low energies. In this work, we examine the prospects for argon-based CEvNS experiments at stopped-pion sources to perform precision measurements of weak interactions and probe non-standard neutrino properties. Our study focused on the CENNS-10 and CENNS-750 detectors at the Spallation Neutron Source at Oak Ridge National Laboratory, the Coherent Captain Mills (CCM) detector at Los Alamos National Laboratory, and the proposed PIP2-BD detector at Fermilab’s Facility for Dark Matter Discovery (F2D2). Using realistic neutrino fluxes and detector configurations corresponding to these facilities, we evaluate event rates and sensitivities to a range of observables. Within the SM, argon-based CEvNS detectors enable precision tests of electroweak parameters, including the weak mixing angle, at momentum transfers well below the electroweak scale. We also investigate the sensitivity of these experiments to neutrino electromagnetic properties, such as the magnetic moment and effective charge radius, as well as to possible non-standard neutrino interactions with quarks. Together, these studies highlight the potential of argon-based CEvNS experiments as a clean and versatile platform for precision exploration of non-standard neutrino properties.

Carey, Sam [Wayne State U.] (ORCID:000900029607531↗

DOE OSTI2024

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

DOE OSTI2025

Development of Predictive Models for Advanced Reactor Autonomous Control

Advanced reactor designs including microreactors and small modular reactors will contribute to the clean production of cheap energy, and autonomous control for advanced reactors is an appealing option for reducing cost. However, there is a lack of industry experience applying autonomous control for advanced nuclear reactors. To accelerate the development and industry acceptance of autonomous control software for nuclear reactors, we aim to demonstrate autonomous control of the Purdue University research reactor (PUR-1) using INL-developed model predictive control (MPC) methods. To prepare for this demonstration, data-driven predictive models based on process data collected from PUR-1 have been developed and integrated with MPC and used to control a physics-based model of PUR-1. A data-driven dynamics model and a gated recurrent unit (GRU) network were both trained on process data from PUR-1. The dynamics model was shown to effectively control the reactor model with MPC when provided reactivity as a control variable but failed to control the model through the control rod positions. The GRU network produced more accurate predictions than the dynamics model when evaluated on operational data, and future work will include the evaluation of the GRU network in the controller.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

It's All About the Envelope: Prioritizing Envelope Upgrades for Electrification of Cold Climate Homes

Building decarbonization via electrification on a clean grid is the most promising climate solution proposed to date for the building sector. In cold climate zones, building electrification will be driven in large part by moving from natural gas space heating to cold climate heat pumps (CCHPs). CCHPs are commercially available today, including economical cold climate air source heat pumps (ccASHPs). But there's one big problem - wide-scale adoption of ccASHPs will dramatically increase winter peak electricity demand, even with the highest efficiency ccASHP products. Furthermore, cold climate space heating loads will drive unprecedented electric system peaks during the lowest periods of renewable generation and are likely to overwhelm existing distribution systems. This scenario is avoidable by coupling electrification with building envelope upgrades to reduce peak heating loads. This paper presents a model, built from home energy audit and research data sets, that quantifies the above challenges. Results demonstrate how weatherization efforts coupled with additional high-performance envelope upgrade measures can prepare the building stock for electrification and show the benefit these measures can bring to future utility operations. Much of this envelope upgrade work is cost-effective, according to conservative cost-benefit testing and program successes to date, and is coupled with substantial non-energy benefits. However, persistent market barriers have made scaling of envelope retrofit work challenging for decades, suggesting additional policy support is required. Lessons learned from previous policy experience, combined with new technology and administrative support, create exciting potential for this decarbonization climate solution.

air sealing↗

DOE OSTI2025

Using X-ray radiography to study oxygen flow in a proton exchange membrane electrolyzer operating under balanced pressure conditions

Of the various water electrolyzer technologies, the proton exchange membrane electrolyzer (PEMWE) is one of the best solutions for producing clean hydrogen without releasing CO 2 . In order to allow for widespread use of clean hydrogen, it is necessary to decrease its cost, which is intrinsically related to system operation. Current PEMWE plants operate in differential mode, directly pressurizing hydrogen and benefiting from thermodynamic compression, which increases overall system efficiency. However, high differential pressure above 30 bar can cause membrane stress, resulting in membrane creeping and failure. Pressurizing the water and operating at balanced pressure allows hydrogen to be produced at higher pressures while preserving the integrity of the membrane and porous layers. Nevertheless, the impact of pressurizing water on PEMWE performance must be better understood to maximize performance under balanced pressure conditions. Here, this study examined the impact of water pressure on two-phase flow. A high-pressure electrolyzer setup was developed to perform operando X-ray radiography and examine oxygen transport with high temporal resolution. The imaging segmentation process, developed to capture bubble properties in the channel, was applied to a specific experiment. The results clearly showed that as pressure increased up to 30 bars, the initial bubbly flow transitioned to slug flow, which led to channel saturation with oxygen. This work demonstrates that two-phase flow in an electrolyzer can be studied using X-ray radiography, which has the advantages of fast measurements and the ability to probe dense materials, such as those required for pressurized electrolyzers.

Balanced high pressure operation↗

DOE OSTI2020

Evaluation of Hybrid FPOG Applications in Regulated and Deregulated Markets Using HERON

Recent changes in the U.S. energy market, such as low natural gas prices and increased electricity production for variable renewable energy (VRE) sources, have led to an economic crisis for existing light-water reactor (LWR) nuclear power plants (NPP). Many owners and operators of LWRs have elected to decommission these plants rather than continue using them as consistent sources of clean baseload power. This has led to exploration of various possibilities to increase the economic viability of these units, including market restructuring to monetize benefits LWRs already provide to the grid through ancillary markets, load following and economic dispatch, and possible integration of secondary systems directly to the NPP for production of additional products through technologies such as hydrogen electrolysis or water desalination. Previous studies have considered the technologies associated with these Integrated Energy Systems (IES) activities, and the analysis of markets for these secondary products. To analyze the economic viability of various system configurations including IES, especially given the uncertainty surrounding load demand, electricity prices, and the availability of VRE resources, the stochastic technoeconomic analysis package HERON (Heuristic Energy Resource Optimization Network) was released earlier this year as an extension of the risk analysis framework RAVEN (Risk Analysis Virtual Environment). HERON focuses foremost on making the complex uncertainty quantification analysis tools approachable for energy systems analysts, also providing general dispatch optimization algorithms for those workflows. HERON continues to be improved and tested as a significant part of the IES viability analyses performed in this work. HERON is not a capacity expansion model. To consider market and grid energy system development in a variety of scenarios, HERON is best used in coupling with modelling tools such as US-REGEN, which sacrifice some of the uncertainty analysis and resolution of HERON's modelling for the ability to efficiently predict the change in the grid energy system's profile due to economic drivers over decades. HERON can then use this information to explore the economic viability of introducing changes to the predicted outcomes, such as the introduction of an IES. In this work, experts at EPRI using US-REGEN provide six projection scenarios for use in HERON stochastic technoeconomic analysis (STEA) in considering the options available for increasing LWR economic viability through introduction of a hydrogen-centric IES using a high-temperature steam electrolysis plant (HTSE), hydrogen storage, and a constant-rate contracted hydrogen consumer. The results obtained are differential in nature; they do not report expected profits for any configuration, but rather report on the possible increase in the NPV of a configuration with respect to a baseline no-IES configuration. Due to the uncertainty captured in the variable net load of the systems, there is likewise uncertainty in the mean values reported. We consider this viability both in terms of a regulated market, where the energy producers and IES are owned and operated by single entity, as well as a deregulated market, where the IES chooses its bid for electricity generation and is then dispatched by the grid system operator. Results indicate that for deregulated markets, the inclusion of the IES is often statistically beneficial. This is especially true in policies that are not favorable towards nuclear, as nuclear is less often dispatched and is forced to deal with frequent idle capacity. In the nominal case as well as the case of carbon tax policies, inclusion of the IES clearly benefited the economic performance of the NPP. In the regulated case, however, there was a trend towards minimizing the IES, likely due to the optimal sizing performed by US-REGEN of the NPP within the system as well as the lack of penalty for idle capacity at the NPP in the regulated market analyses.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice

Abstract. Accurate modeling of cryospheric surface albedo is essential for our understanding of climate change as snow and ice surfaces regulate the global radiative budget and sea-level through their albedo and mass balance. Although significant progress has been made using physical principles to represent the dynamic albedo of snow, models of glacier ice albedo tend to be heavily parameterized and not explicitly connected with physical properties that govern albedo, such as the number and size of air bubbles, specific surface area (SSA), presence of abiotic and biotic light absorbing constituents (LACs), and characteristics of any overlying snow. Here, we introduce SNICAR-ADv4, an extension of the multi-layer two-stream delta-Eddington radiative transfer model with the adding–doubling solver that has been previously applied to represent snow and sea-ice spectral albedo. SNICAR-ADv4 treats spectrally resolved Fresnel reflectance and transmittance between overlying snow and higher-density glacier ice, scattering by air bubbles of varying sizes, and numerous types of LACs. SNICAR-ADv4 simulates a wide range of clean snow and ice broadband albedo (BBA), ranging from 0.88 for (30 µm) fine-grain snow to 0.03 for bare and bubble-free ice under direct light. Our results indicate that representing ice with a density of 650 kg m−3 as snow with no refractive Fresnel layer, as done previously, generally overestimates the BBA by an average of 0.058. However, because most naturally occurring ice surfaces are roughened “white ice”, we recommend modeling a thin snow layer over bare ice simulations. We find optimal agreement with measurements by representing cryospheric media with densities less than 650 kg m−3 as snow and larger-density media as bubbly ice with a Fresnel layer. SNICAR-ADv4 also simulates the non-linear albedo impacts from LACs with changing ice SSA, with peak impact per unit mass of LACs near SSAs of 0.1–0.01 m2 kg−1. For bare, bubble-free ice, LACs actually increase the albedo. SNICAR-ADv4 represents smooth transitions between snow, firn, and ice surfaces and accurately reproduces measured spectral albedos of a variety of glacier surfaces. This work paves the way for adapting SNICAR-ADv4 to be used in land ice model components of Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Neutron Skin Measurement of 208Pb and 48Ca Using Parity Violating Electron Scattering

Parity-violating electron scattering experiments (PVES) provides a clean probe of neutron densities that is model independent and free from strong interaction uncertainties in interpretation. The PREX-2 and CREX experiments were run in 2019 and 2020 at Jefferson laboratory measured the nucleon skin thickness, the difference between the r.m.s. neutron radius Rn and the r.m.s. proton radius Rp, of 208Pb and 48Ca via parity violating electroweak asymmetry in the elastic scattering of longitudinally polarized electrons. PREX-2 experiment was performed with 950 MeV electrons scattered at a 5¿ angle with Q2 = 0.00616 ± 0.00004 (GeV/c)2, while CREX used 2182 MeV electrons at the same angle with Q2 = 0.0297 ± 0.0002 (GeV/c)2. For PREX-2 the measured asymmetry was AP V = 550 ± 16 (stat.) ± (syst.) ppb, which corresponds to Rskin = 0.278 ± 0.078 (exp.) ± 0.012 (theo.) fm. The CREX asymmetry was AP V = 2668 ± 106 (stat.) ± 40 (syst.) ppb, which corresponds to Rskin = 0.121 ± 0.026 (exp.) ±0.024 (model) fm. One of the crucial systematic uncertainty that PREX-2 and CREX were sensitive to was the non-parity violating asymmetries that resulted from the helicity correlated false asymmetries in the polarized electron beam. There was a lot of work put towards understanding and suppressing the asymmetries arising from these effects. The parity violating asymmetry measurement required a very precise determination of the electron beam polarization. To accurately determine the beam polarization, a Compton polarimeter was used during both PREX-2 and CREX. A careful alignment of the laser to the Fabry-Perot cavity, data analysis and systematic control was employed to get a precise beam polarization result for the experiments. The PREX-2 measurement has broad implications for increasing our knowledge about neutron star structure and the equation of state of nuclear matter. The combined PREX and CREX results will have implications for future energy density functional calculations and the theory of nuclear structure.

Premathilake, Sachinthani↗

DOE OSTI2023

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

This report documents the benchmarks being developed and simulations performed using tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, utilizing MSRE experimental data. In FY23, three main work scopes were investigated under the NEAMS MSR work package at ANL. The first scope investigated the Griffin-SAM coupling model for simulating the pump startup transient experiment of MSRE. The analyses start with a simple model (single-channel, single-lattice), gradually adding more details (multi-channel, full-core) into the model. The results show that the reactivity loss curve is very sensitive to the axial boundary conditions and the radial core discretization. The simple model can predict a similar reactivity trend as that of the more sophisticated model, which is likely due to error cancellation. Accurately modeling the axial boundary condition may further improve the reactivity trend but would require significant efforts to generate the mesh of the MSRE inlet and upper plenum. The core channel radial discretization for the Griffin-SAM coupled model also depends on the flow distribution. Given the complex geometry in the inlet plenum, the flow distribution needed to be calculated from CFD analysis, which was performed using the NekRS code. This analysis employed a MSRE CAD model developed by Copenhagen Atomics. The CAD model was disassembled to keep the inlet plenum region only, which was subsequently cleaned and modified so that the mesh generated is under the memory limit. The results are merged to a few radial regions to show that the flow rate is highest in the central region. This would be useful for future improvement of the Griffin-SAM coupling model of the MSRE core. The last task investigated is tritium transport modeling using the standalone SAM code. This task aimed to initiate the effort to demonstrate and validate the tritium transport model implemented in SAM. The preliminary investigation employed an MSRE model consisting of the primary loop. Three tritium transport pathways were examined including the retention in the graphite, the permeation through the HX tube wall, and the removal from the off-gas system. The results compare well with the MSRE data, but improvements are still needed on the initial conditions (i.e., the present state may not have reached equilibrium), the boundary conditions, the off-gas system modeling, and a better numerical strategy to reach the equilibrium state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Optimizing Aluminum Bonding: Exploring Surface Roughness and Contact Angle Effects through Plasma and Acid Etching Contrasts

The use of adhesives to replace traditional techniques like welding and riveting has been on the rise in various industries as increasingly complex geometries and situations for bonding is required. It’s well known in the scientific community that an adhesive bond is only as efficient as the surface preparation used beforehand. Plasma treatments have been shown to gently clean the surface by only removing the top-most layer from the adherend and “charging” the surface instead of berating it. Whereas chemical treatments “etch” the surface in hopes of increasing surface area by increasing surface roughness. This method can be difficult to control quantitatively and can generate waste leading to serious environmental concerns. This study aims to address the encountered differences between plasma treatments and acid etching on aluminum substrates for adhesive bonding. Treating the surface of adherends plays a crucial role in promoting a good bond between adhesive and adherend. In this study, the effects of plasma and acid treatments are categorized using surface roughness measurements as well as contact angle which have been shown to correlate to mechanical strength. When evaluating different surface treatments, it is notable to mention that not only surface roughness and contact angle play a role in determining which method is most effective but also the consequences of the treatment itself. It was found that although chemical etching was the most effective in increasing roughness and decreasing contact angle, it generates a large amount of waste and is not sustainable compared to plasma work which uses a renewable process. The results from this work provide a deeper understanding of the relationship between surface treatments and surface roughness/contact angle and how this relates to a stronger adhesive bond.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Optimizing Aluminum Bonding: Exploring Surface Roughness and Contact Angle Effects through Plasma and Acid Etching Contrasts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Development of Nanocomposite Coatings for Future Large-Scale Time Projection Chambers

In the context of this award we tested the performance of thin high-resistivity coatings for their potential usage as field shaping systems in future large scale xenon Time Projection Chambers (TPC). A successful implementation of such thin coatings would likely simplify the design of potential future detectors, allowing to overcome some of the challenges observed with traditional systems constituted by massive discrete electrodes. We studied a wide range of materials and characterized their optical and electrical performances as functions of temperature and wavelength. The measurement campaign indicated that uniform coatings covering the full PTFE substrate (usually used as reflector in LXe TPCs) impact too severely on the light collection performance of such detectors when used with deep UV light. Despite tuning the composition and thicknesses of nanocomposite coatings, we were not able to identify a single coating, properly working at LXe temperature, that would simultaneously fulfill the resistance and optical requirements. Following the risk mitigation strategy identified in the proposal we moved the focus of the R&D to identify proper materials that, when coated with grid-like patterns on PTFE, would not alter meaningfully its optical properties (with respect to bare PTFE panels) but would still serve as effective field shaping systems, properly containing the drift field in TPC detectors. Among the various materials we identified germanium as the most promising one, providing a good adhesion to PTFE and the proper range of sheet resistivity. The Ge-patterned coating tested within a small scale LXe TPC showed good performance as a field shape system and, as desired, did not reduce the detector light yield. These results are encouraging and such technology should further be investigated as a potential alternative to more traditional field shaping electrodes. Incidentally, in the context of this R&D, we stumbled upon an unexpected behavior suggesting that some of the treatments performed on the PTFE panels, in preparation of the coatings, meaningfully boosted the PTFE reflectivity. The most probable candidate is the O2 plasma cleaning procedure. This hypothesis will be tested in the near future by operating the small scale TPC at UChicago first with regular PTFE panels and then with panels bombarded with O2 plasma (but no coatings). This finding, if confirmed, might open up the possibility of further boosting UV light collection in future large detectors by performing such a treatment on the PTFE surfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Co-synthesis of Hydrogen and High-Value Carbon Products from Methane Pyrolysis

The ARPA-E Methane Pyrolysis Project successfully developed a scalable technology for hydrogen production with low-CO x emission through methane pyrolysis, co-producing high-value carbon nanotubes (CNTs). The project focused on optimizing reactor design, enhancing catalyst performance, and assessing techno-economic feasibility to create a commercially viable and environmentally sustainable process. The fluidized bed reactor achieved over 90% methane (CH 4 ) conversion by using a 5% CO 2 co-feed, which stabilizes carbon yields and minimizes catalyst deactivation. This setup allowed for continuous operation across ten cycles, each consisting of a 14-minute pyrolysis phase followed by a 10-minute dislodging phase to remove a fraction of the accumulated carbon, resulting in stable performance and high-quality CNT production. In parallel, monolith reactors coated with Fe demonstrated a sustained methane conversion of 73% while producing CNTs with high crystallinity. Although promising for continuous operation, monolith reactors face challenges in coating durability and scalability, highlighting areas for further optimization in commercial applications. Catalyst formulation played a key role in enhancing process efficiency. The core catalyst used was 5%Fe/Al 2 O 3 (wt%), optimized through wet impregnation, which improved CNT morphology, yielding longer and more uniform CNTs. The catalyst's performance was further enhanced by adding promoters: 2.5 wt% Ni increased methane conversion close to the thermodynamic limit, while 2.5 wt% Mn improved CNT alignment and crystallinity, and 1.5 wt% NaCl boosted CNT morphology but slightly lowered methane conversion. These adjustments allowed the reactor to maintain high methane conversion while producing high-quality CNTs, enabling stable performance over multiple cycles. To address carbon buildup and ensure uninterrupted operation, a pneumatic conveying tube was implemented for effective carbon dislodging in the fluidized bed configuration. CO 2 and H 2 O co-feeds were also introduced to enhance carbon removal, with CO 2 boosting CNT yield by approximately 15%. This setup enabled stable reactor operation across multiple cycles, preventing clogging and minimizing catalyst wear, making the process suitable for industrial scaling. Techno-economic analysis (TEA) projected hydrogen production costs between $\$$1.00 and $\$$1.64 per kilogram, with CNT values assumed at $\$$375/ton and $\$$100/ton. The life cycle assessment showed that CO 2 emissions could be as low as 0.64 kg CO 2 e/kg H 2 at 95% methane conversion assuming an electricity input of 50 kg CO 2 e/MWh. Even at 50% methane conversion, emissions remained below 1 kg CO 2 e/kg H 2 , demonstrating the process's low-emission potential and making it a viable alternative to traditional steam methane reforming. Overall, the results from this project demonstrate the feasibility of a pyrolysis process where carbon is continuously removed from the catalyst surface and hydrogen is continuously produced until a catalyst regeneration step is required to fully clean the catalyst surface and renew catalyst performance. Major open challenges are related to avoiding the loss of catalyst material in the dislodged carbon during fluidized bed conditions, since our best result demonstrated a carbon purity of ~70 wt. % (rest being iron and alumina). A monolith reactor was used to favor dislodgement of carbon compared to fluidized bed conditions but our results do not demonstrate an advantage of the monolith configuration. Catalyst performance was similar to fluidized bed conditions with slower deactivation rates overall, but we could not observe carbon dislodging in any of the tens of experiments that were run at Stanford. Our results show that the most relevant areas of improvement are related to the fundamental understanding of the iron-carbon interface for dislodging, and the development of catalyst that can produce CNTs via a base-growth mechanism such that catalyst is not lost in the dislodgement steps. The final report documents all findings and methodologies in detail, providing a valuable resource for the scientific community. By building on these results, researchers can further advance methane pyrolysis technology, moving toward a more sustainable, scalable pathway for hydrogen production. This work lays the foundation for future research and commercial efforts to reduce emissions in hydrogen production while generating valuable carbon products.

08 HYDROGEN↗

DOE OSTI2024

Hydrokinetic tidal energy resource assessment following international electrotechnical commission guidelines

Marine renewable energy can be used as a viable energy source to alleviate the impact of the climate crisis and have a carbon-free electricity sector in the future. Especially the energetic tidal streams are an attractive source of clean energy due to the periodic occurrence of high tidal flows daily. However, before any deployment of tidal turbine farms, it is essential to perform a resource assessment depending on the scope and scale of the project. Here, the International Electrotechnical Commission has developed a technical standard for assessing the tidal stream resource "IEC 62600-201 TS" to aid in this effort: determine a particular site's feasibility and perform the project layout design. In this study, we implemented and validated a high-resolution three-dimensional numerical model and provided results following the IEC TS for a project layout design in a highly energetic tidal channel, Tacoma Narrows of Puget Sound, in the State of Washington, USA. Implementation of the guidelines has helped adequately identify the undisturbed theoretical and technical resources with less bias, where the latter included energy extraction from the flow field arranging a hypothetical tidal energy converter (TEC) array. Also, following the standard, we carefully assessed the changes to channel flow properties from TECs, such as the kinetic energy flux and annual energy production (AEP), to provide the detailed information required for a larger project layout design. Ultimately, this work has shown the important role of IEC TS in tidal stream resource assessment, which can simultaneously act as a benchmark for other studies worldwide.

13 HYDRO ENERGY↗

DOE OSTI2024

NEAMS Burnup Extension Accomplishments and Remaining Modeling Gaps

The economic viability of light-water reactors (LWRs) in the United States is declining in heavily subsidized markets, and as a result, the nuclear industry is looking for opportunities to enhance the economic competitiveness of nuclear power. This is not a foreign concept to the nuclear industry: in the mid-2000s, the nuclear industry set out to achieve zero fuel failures by 2010. The goal in this effort was to drive down the cost of reactor shut down by replacing a pin or bundle in response to fuel rod failure. 2010 brought about the initiative to deliver the nuclear promise to reduce operating cost by 30% to improve nuclear energy’s economic competitiveness before 2020. The emergence of accident-tolerant fuel also offers the nuclear industry an opportunity to build on these past successes and deliver affordable, clean energy. Accident-tolerant fuel has been shown to provide superior performance compared to traditional Zircaloy/UO2 fuel concepts, offering the unique ability to remove operational limitations that inhibit the economic viability of nuclear power. This has led the industry to begin building a technical case to extend the peak rod average burnup beyond 62 GWd/tU to extend pressurized water reactor cycle lengths to 24 months and to develop more efficient boiling water reactor core designs. The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program mission is to develop advanced modeling and simulation tools and capabilities to accelerate the deployment of advanced nuclear energy technologies. The primary safety concern inhibiting the nuclear industry from extending burnup is related to high-burnup fuel fragmentation, relocation, and dispersal. Therefore, the NEAMS program developed a targeted 5-year plan to support the industry’s efforts to extend burnup. This milestone report summarizes the 5-year plan that was enacted in FY20, followed by a discussion of the ongoing activates required to fulfill the 5-year plan, as well as the approach to address the current modeling gaps. Additionally, an LWR stakeholder meeting was held to communicate work performed in the NEAMS program over the past three years, to assess the LWR community’s perspective on the impact of the program, and to identify remaining significant gaps in the NEAMS suite of capabilities. This engagement will be documented by the Electric Power Research Institute and used by NEAMS to redirect current LWR scope as needed and to develop the next phase for LWR research and development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Wind Energy Accomplishments and Year-End Performance Report: Fiscal Year 2022

Four decades ago, construction was just beginning on experimental turbines at the National Wind Technology Center (NWTC). Today, the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) facility is the centerpiece of the laboratory's Flatirons Campus, a world-class hub for renewable energy research. The nation's shift to 100% clean electricity by 2035 will require a mix of renewable energy sources and strategies - and together, wind and solar energy could account for 60% to 80% of that clean energy resource. In Fiscal Year (FY) 2022, NREL scientists, engineers, and analysts contributed to these visionary goals through their wind energy research. As wind innovations push into new areas, NREL continues to play a vital role in advancing technology and addressing deployment barriers in pursuit of more efficient, reliable, and predictable wind energy systems. FY 2022 wind research and development explored the potential for dramatic growth in land-based systems, the launch of the nation's first commercial-scale offshore installations, and transmission infrastructure buildout. Land-based wind energy is one of the most cost-effective electricity supply options - but utility-scale deployment will require up to 10 times the current number of turbines. An NREL plan addressed this need to accelerate U.S. wind technology rollout at distributed and utility scales. Another project conducted by NREL and the Pacific Northwest National Laboratory (PNNL) helps position the nation's first major offshore wind corridor for success. The WETO-funded Atlantic Offshore Wind Transmission Study is evaluating options for balancing electricity supply and demand, while supporting resilience of the grid and marine industries. WETO, NREL, and other partners are working to enable the enormous supply chain and workforce changes the U.S. wind energy industry will need to meet net-zero-carbon-emissions targets. As part of a seminal series of DOE-funded supply chain studies, NREL analysts reported on the trade-offs involved in manufacturing large volumes of wind technologies, while addressing cost, workforce, and logistics issues. All of this research is supported by NREL's outstanding research teams, tools, data, and facilities. A WETO-funded international wind energy field campaign, the American WAKE experimeNt (AWAKEN), has brought together experts from NREL, PNNL, and Sandia National Laboratories to create the world's most comprehensive set of high-resolution data on wind energy atmospheric phenomenon. This study could lead to more accurate predictions of losses from turbine-to-turbine wake interactions, eventually helping wind plants capture more energy and operators save millions of dollars. In addition, NREL researchers developed testing, modeling, and analysis tools to improve the security of power grids by identifying wind power plant dynamic stability problems. A new Stochastic Soaring Raptor Simulator (SSRS) protects golden eagles from turbine encounters by predicting flight paths. This report provides more detail on these top achievements and other accomplishments made by NREL and its partners during FY 2022 (between October 1, 2021, and September 30, 2022).

accomplishments↗

DOE OSTI2022

Hydrogen generation via ammonia decomposition on highly efficient and stable Ru-free catalysts: approaching complete conversion at 450 °C

We report Hydrogen (H 2 ) is a prospective zero-carbon and high-energy-density fuel alternative to fossil fuels for generating power and clean energy. Ammonia (NH 3 ) is a promising H 2 (17.7%) carrier, which can easily overcome the challenges associated with H 2 storage and transportation. Thermocatalytic ammonia decomposition reaction (ADR) is an effective way to produce clean H 2 but it relies on the use of expensive and rare ruthenium (Ru)-based catalysts at elevated temperatures (>500 °C), hence is not sustainable and economically feasible. Herein, we report a synergistic strategy to design a heterostructured Ru-free catalyst, consisting of CoNi alloy nanoparticles well-dispersed on a MgO–CeO 2 –SrO mixed oxide support with potassium promotion. The resulting K–CoNi alloy –MgO–CeO 2 –SrO catalyst presents 97.7% and 87.5% NH 3 conversion efficiency at 450 °C at gas hourly space velocities (GHSVs) of 6000- and 12 000-mL h -1 g cat -1 , respectively. At 500 °C, the H 2 production rate (57.75 mmol g cat -1 min -1 ) becomes comparable to that of most of the reported Ru-based catalysts. The catalyst stability has been successfully demonstrated in both a fixed-bed reactor under high pressure (120 h at 5.0 bar) and a membrane reactor prototype (600 h at 1.5 bar) at 500 °C. High-temperature in situ XPS analysis, temperature-programmed desorption/reduction, and density functional theory calculations have been carried out to elucidate the possible active sites and performance enhancement mechanisms. This work highlights the importance of constructing optimal interfaces between active metal nanoparticles and oxide support for boosting the NH 3 to H 2 conversion efficiency and long-term stability.

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