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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 37 records · Page 2

Grid-responsive hydrogen production: Capital utilization and current density vs. efficiency in variable electricity markets

To achieve low-cost hydrogen production from water electrolyzers, grid tied electrolysis may need to operate dynamically to minimize the cost of supplying energy to the electrolyzer stack and produce hydrogen during low-cost hours and turn off/down during high-cost hours. Operating systems in this way can decrease capital utilization (capacity factor) and electricity costs. This strategy would shift the dominant cost drivers away from electricity (and thus efficiency) to the capital costs of the system, due to the underutilized capital when operating at low-capacity factors. Increasing the operational current density of the system could, in effect, reduce the capital cost of the system while producing hydrogen at a lower efficiency on a per unit energy basis. In the variable electricity cost profiles analyzed in this paper, increasing the current density for liquid alkaline from 0.5 A/cm2 to 1.5 Ac/m2 and proton exchange membrane electrolyzers from 2 A/cm2 to 4 A/cm2 resulted in substantial reductions in the levelized cost of hydrogen. Additionally, as capacity factors and electricity costs decrease, the optimal operating current density of the electrolyzer systems analyzed increases. These findings suggest R&D efforts should focus on increasing the operational current densities, reducing the turn down ratios, and understanding the durability implications of those strategies on low-temperature liquid alkaline and proton exchange membrane electrolyzers.

08 HYDROGEN

Liquid Alkaline Water Electrolyzers: Comparing Performance across Design, Operation, and End-of-Life Scenarios

Liquid alkaline water electrolysis (LAWE) is a demonstrated technology for hydrogen production, yet a comprehensive life cycle assessment (LCA) of their deployment is lacking. Research leading to improvements to the core component, the electrochemical stack, along with auxiliary system materials and dynamic operation of stacks from variable electricity supply offers new data that allows for detailed modeling and evaluation. Here, we present an LCA of two facility designs based on the current state-of-the-art stack and an advanced stack with zero-gap between electrodes, and capture dynamic electricity use from solar, wind, and hybrid sources and stack recycling strategies. We present life cycle impact factors characterizing the production of 1 kg of hydrogen across 12 environmental, human health, and resource impact categories (TRACI and ReCiPe) in the contiguous United States. As expected, the source of electricity will drive impacts (e.g., 83-94% of carbon intensity); however, we find that operating using wind electricity can lower hydrogen leakage and the overall carbon intensity (1.03 kgCO 2 e/kgH 2 ) relative to solar electricity (2.57 kgCO 2 e/kgH 2 ) at matched 1:1 capacity between LAWE and the electricity source. The deployment of the advanced design and stack recycling lowers impacts across all life cycle stages. We highlight opportunities to further reduce potential impacts, including the balance of plant materials and operation cycles associated with the use of variable wind and solar electricity that result in hydrogen leakage.

08 HYDROGEN

Comparing Constant and Transient Membrane Transport Parameters for Use in Wave Desalination Models

Directly pressurizing seawater for desalination with reverse osmosis membranes via wave motion is a promising and sustainable method for producing freshwater in coastal regions. However, such a system could result in significant pressure fluctuations and a departure from conventional steady-state desalination operations. This study sought to assess if membrane transport parameters (apparent water and salt permeability) should be modeled as transient or constant in solution–diffusion-based modeling efforts of dynamically operated desalination systems, such as those coupled to wave power. Two approaches were used to model membrane transport parameters: one considered each parameter to be a function of the net driving pressure of the system, and the other assumed they were constant across all conditions. A pilot-scale system was used to conduct steady-state and controlled ramping experiments. Data from steady-state experiments were used to calculate transient and constant transport parameters. Parameter combinations were used in a simulation model to predict water flux and effective permeate salinity, and simulation outcomes were compared against experimental ramping results. The transient relationships for both water and salt permeability produced the most accurate results for water flux and comparable results for effective permeate salinity. Development of such relationships would be unique to a specific system but could be valuable in modeling wave-driven desalination systems across the wide range of operating conditions they experience.

13 HYDRO ENERGY

Sintering protonic zirconate cells with enhanced electrolysis stability and Faradaic efficiency

The emerging applications of steam electrolysis and electrochemical synthesis at 300–600 °C set stringent requirements on the stability of protonic ceramic cells, which cannot be met by Ce-rich electrolytes. A promising candidate is Ce-free BaZr 0.8 Y 0.2 O 3–δ , but its usage has long been hindered due to the high sintering temperatures required for protonic devices. Here we resolved the issue through a co-sintering process, in which the shrinkage stress of a readily sinterable support layer helps to densify the pure BaZr 0.8 Y 0.2 O 3–δ electrolyte membrane at low temperatures. This approach eliminates Ce and harmful sintering aids in the dense zirconate electrolyte membrane, thereby enhancing the Faradaic efficiency and electrochemical stability, especially under harsh operating conditions. Here, the protonic zirconate cells have exceptional performance and demonstrate stable high-steam pressure electrolysis up to 0.7 atm steam pressure, –2 A cm –2 current density and over 800 h of dynamic operation at 600 °C. Our processing breakthrough enables stabilized protonic cells for demanding applications in future energy infrastructure.

25 ENERGY STORAGE

End-to-end microgrid protection using distributed data-driven methods

This paper introduces an end-to-end microgrid protection framework that offers real-time system monitoring, fault-related decision making, and circuit breaker control. This is achieved through the design of distributed data-driven techniques based on the support vector machine method, where each relay is responsible for distributed data collection, fault detection, fault localization, and fault isolation. Local communication is established among neighboring relays, fostering cooperative fault localization and isolation. This decentralized design not only reduces the computational and communication requirements but also enables the adaptability of each relay under varying operational dynamics. The proposed end-to-end protection framework was validated using MATLAB/Simulink simulations on a 100% renewable microgrid, achieving an accuracy of 93.1% with response time of 0.0523 s, in protecting against a range of fault scenarios that are characterized by various types, locations, impedances, load conditions, photovoltaic power levels, and microgrid operating modes.

24 POWER TRANSMISSION AND DISTRIBUTION

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)

Optimizing Renewable Ammonia Production for a Sustainable Fertilizer Supply Chain Transition

Local renewable ammonia production using electrolytic hydrogen is an emerging approach to alleviate emissions attributed to synthetic nitrogen fertilizer production while also insulating against fluctuations in fertilizer prices and mitigating transportation costs and emissions. However, replacing ammonia currently produced using fossil fuels will not be immediate. To this end, we develop a supply chain transition model, which first optimizes the design and hourly operation of new renewable ammonia facilities to minimize production costs and then optimizes the annual installation timing, production scale, and location of these new renewable facilities along with ammonia transportation to meet county resolution demands. The objective is to augment and eventually replace conventional ammonia market imports in an economically competitive manner. We performed a case study for Minnesota's ammonia supply chain and found that a full transition to in-state renewable production by 2032 is optimal. This is incentivized by the U.S. federal government's clean hydrogen production credits. This transition results in 99 % reduction in carbon intensity along with stable supply costs below $475 per metric tonne. New renewable production facilities are an order of magnitude smaller than existing conventional plants. They use both wind and solar resources and operate dynamically to minimize expensive battery and hydrogen storage capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Role of Mg:Al ratio and Pt promotion on mitigating the deactivation of Ni-based methane steam reforming catalysts

Ni-based catalysts for CH 4 steam reforming require fine-tuning to withstand deactivation under dynamic operation conditions relevant to emerging H 2 -driven technologies. This study investigates the impact of the Mg:Al ratio and Pt presence in catalyst composition on the activity and stability of industrially relevant Ni-based mono- and bimetallic catalysts during simulated daily start-up and shut-down cycles in various gas atmospheres. The evolution of the catalyst structure during extensive testing procedures was investigated in detail by complementary electron microscopy, in situ/operando XAS and XRD. The results obtained revealed that catalyst deactivation is promoted at high Mg:Al ratios and especially affects the monometallic catalysts. By converting CH 4 at lower temperatures, Pt regulates the extent of Ni oxidation and its incorporation into MgO lattice. Further prevention of catalyst deactivation was achieved by optimizing the reactor shut-down procedure to minimize the simultaneous exposure to high temperatures and H 2 O vapors. By flushing the reactor with N 2 only around the reaction extinction temperature, a fraction of Ni species is maintained in metallic state, which is beneficial for the long-term activity and reaction operation economy.

54 ENVIRONMENTAL SCIENCES

Excited state dynamics of azanaphthalenes reveal opportunities for the rational design of photoactive molecules

Abstract Various photoactive molecules contain motifs built on aza-aromatic heterocycles, although a detailed understanding of the excited state photophysics and photochemistry in such systems is not fully developed. To help address this issue, the non-adiabatic dynamics operating in azanaphthalenes under hexane solvation was studied following 267 nm excitation using ultrafast transient absorption spectroscopy. Specifically, the species quinoline, isoquinoline, quinazoline, quinoxaline, 1,6-naphthyridine, and 1,8-naphthyridine were investigated, providing a systematic variation in the relative positioning of nitrogen heteroatom centres within a bicyclic aromatic structure. Our results indicate considerable differences in excited state lifetimes, and in the propensity for intersystem crossingvsinternal conversion across the molecular series. The overall pattern of behaviour can be explained in terms of potential energy barriers and spin-orbit coupling effects, as demonstrated by extensive quantum chemistry calculations undertaken at the SCS-ADC(2) level of theory. The fact that quantum chemistry calculations can achieve such detailed and nuanced agreement with experimental data across a full set of six molecules exhibiting subtle variations in their composition provides an excellent example of the current state-of-the-art and is indicative of future opportunities for rational design of photoactive molecules.

Chemistry

Heat load measurements for the PIP-II pHB650 cryomodule

Phase-3 testing of the pHB650 cryomodule at the PIP-II Injector Test Facility was conducted to evaluate the effectiveness of heat load mitigations performed after earlier phases of testing and to continue pinpointing any sources of unexpectedly high heat loads.. The programme measured HTTS, LTTS, and 2 K isothermal/non-isothermal loads under "standard", "linac", and "simulated dynamic" operating modes, recording data both inside the cryomodule and across the bayonet can circuits. Thermal-acoustic oscillations were eliminated by replacing the original G10 cooldown-valve stem with a stainless-steel stem fitted with wipers. A newly developed Python script automated acquisition of ACNET data, performed real-time heat-load calculations, and generated plots and tables that were posted to the electronic logbook within minutes, vastly reducing manual effort and accelerating feedback between SRF and cryogenics teams. Analysis showed that JT heat-exchanger effectiveness and temperature stratification in the two-phase and relief piping strongly influence the observed loads and helped isolate sources of excess heat. The campaign demonstrates that rigorous pre-test planning, real-time diagnostics, and automated reporting can improve both accuracy and efficiency, providing a template for future PIP-II cryomodule tests and for implementing targeted heat-load mitigations.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.] (ORCID:

OODG (OnlineOptDynaGrid) [SWR-24-07]

This is a repository for the code developed by NREL under the DynaGrid project. It is a Julia package for running a model-free real-time OPF algorithm to operate dynamic networked microgrids given network configuration results from the Maximal Load Delivery (MLD) problem in the PowerModelsONM.jl package. See Example.jl for a working example on how to use the package. Note: Julia package PowerModelsONM.jl is needed.

Poolla, Bala Kameshwar [National Renewable Energy

Desal.jl

SAND2026-22942O Desal.jl is a Julia software package for lightweight reverse-osmosis desalination simulation. It supports static and dynamic operation of power-limited desalination systems without requiring optimization dependencies. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Michelen Strofer, Carlos [Sandia National Lab. (SN

Geographically Distributed Co-Simulation for the Interplay of Integrated Energy Systems and Power Grid

The increased penetration of renewable generation induces unbalanced demand-supply on a power grid, while integrated energy systems (IES) can provide high part-load efficiency and high flexibility to support grid resilience. To study the transients and improve dynamic operability, it’s important to investigate the interplay between IES and power grid concurrently using real-time co-simulation approaches. In this presentation, we showed the previous co-simulation test between NETL and INL and discussed how this co-simulation can be beneficial for both IES and power grid research. In addition, we gave an overview about the SuperLab2.0 project, which was a federated national platform to address future power grid challenges. (Virtual presentation to the MILLENNIUM CLEAN and SUSTAINABLE POWER workshop 2025).

Co-simulation

Underground Hydrogen Storage: Transforming Subsurface Science into Sustainable Energy Solutions

As the global economy moves toward net-zero carbon emissions, large-scale energy storage becomes essential to tackle the seasonal nature of renewable sources. Underground hydrogen storage (UHS) offers a feasible solution by allowing surplus renewable energy to be transformed into hydrogen and stored in deep geological formations such as aquifers, salt caverns, or depleted reservoirs, making it available for use on demand. This study thoroughly evaluates UHS concepts, procedures, and challenges. This paper analyzes the most recent breakthroughs in UHS technology and identifies special conditions needed for its successful application, including site selection guidelines, technical and geological factors, and the significance of storage characteristics. The integrity of wells and caprock, which is important for safe and efficient storage, can be affected by the operating dynamics of the hydrogen cycle, notably the fluctuations in pressure and stress within storage formations. To evaluate its potential for broader adoption, we also examined economic elements such as cost-effectiveness and the technical practicality of large-scale storage. We also reviewed current UHS efforts and identified key knowledge gaps, primarily in the areas of hydrogen–rock interactions, geochemistry, gas migration control, microbial activities, and geomechanical stability. Resolving these technological challenges, regulatory frameworks, and environmental sustainability are essential to UHS’s long-term and extensive integration into the energy industry. This article provides a roadmap for UHS research and development, emphasizing the need for further research to fully realize the technology’s promise as a pillar of the hydrogen economy.

25 ENERGY STORAGE

Reservoir Dynamics in Proposed Operational Scenarios Where CO 2 -EOR Fields are Transitioned From CO 2 -Flood Enhanced Oil Recovery to Dedicated Carbon Storage: A Field Case Study

This study models the transition of CO 2 -enhanced oil recovery (CO 2 -EOR) fields to dedicated carbon storage using a generalized reservoir model informed by real field data, SACROC. Through scenario-based simulations, the work evaluates how reservoir depletion levels, boundary conditions, fluid properties, and domain size affect pressure buildup, CO 2 plume migration, and long-term containment performance. The results inform practices for repurposing oil fields into reliable CO 2 storage sites.

02 PETROLEUM

Predicting nonequilibrium Green’s function dynamics and photoemission spectra via nonlinear integral operator learning

Understanding the dynamics of nonequilibrium quantum many-body systems is an important research topic in a wide range of fields across condensed matter physics, quantum optics, and high-energy physics. However, numerical studies of large-scale nonequilibrium phenomena in realistic materials face serious challenges due to intrinsic high-dimensionality of quantum many-body problems and the absence of time-invariance. The nonequilibrium properties of many-body systems can be described by the dynamics of the correlator, or the Green's function of the system, whose time evolution is given by a high-dimensional system of integro-differential equations, known as the Kadanoff–Baym equations (KBEs). The time-convolution term in KBEs, which needs to be recalculated at each time step, makes it difficult to perform long-time numerical simulation. In this paper, we develop an operator-learning framework based on recurrent neural networks (RNNs) to address this challenge. We utilize RNNs to learn the nonlinear mapping between Green's functions and convolution integrals in KBEs. By using the learned operators as a surrogate model in the KBE solver, we obtain a general machine-learning scheme for predicting the dynamics of nonequilibrium Green's functions. Besides significant savings per each time step, the new methodology reduces the temporal computational complexity from $O(N_t^3)$ to $O(N_t)$ where N t is the number of steps taken in a simulation, thereby making it possible to study large many-body problems which are currently infeasible with conventional KBE solvers. Through various numerical examples, we demonstrate the effectiveness of the operator-learning based approach in providing accurate predictions of physical observables such as the reduced density matrix and time-resolved photoemission spectra. Moreover, our framework exhibits clear numerical convergence and can be easily parallelized, thereby facilitating many possible further developments and applications.

97 MATHEMATICS AND COMPUTING

Electromagnetic Transient Modeling of Large Data Centers for Grid-Level Studies

The magnitude and complexity of electricity usage patterns from large data centers are having significant impacts on the operation and dynamics of the power grid; grid operators and planners require a range of specialized data center models to properly evaluate these impacts and specify technical solutions as needed. Towards addressing this need, Pacific Northwest National Laboratory (PNNL) has developed a library of electromagnetic transient (EMT) models for grid-level studies of data centers called the data center model library (DML). This report describes how the DML was created and how it may properly be used. The models present in the DML are generic models; subject matter expertise and additional technical data are needed to modify these models before they can represent any real data center. However, they will significantly reduce the level of effort required to develop site-specific models and can serve as a common starting point to guide industry towards a more refined consensus. Most of the models within DML are dedicated to representing the power electronics interfaces commonly used in modern data centers, such as double-conversion uninterruptible power supplies and single-phase power factor correction converters. These models are intended for use in grid-level studies and are a simplified aggregation of many small components. That said, background material on the physical and electrical design of large data centers is provided as companion material so that users can be aware of many of the details which have been omitted or streamlined as a matter of practical necessity. Additionally, guidance on the application of EMT analysis for data center interconnection studies is provided, which aids users in identifying when the DML is necessary and what sort of additional model development may be necessary for conducting real-world studies.

24 POWER TRANSMISSION AND DISTRIBUTION