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

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Life cycle greenhouse gas emissions of different CO 2 supply options for an algal biorefinery

This paper characterizes the greenhouse gas (GHG) emissions from the provision of CO 2 for twelve hours of the day from a range of sources operating on a twenty-four-hour basis. Twelve CO 2 supply cases spanning from fossil fuel power plant stack gases to direct air capture (DAC) systems are modeled. The results are compared in a life cycle assessment (LCA) framework. The CO 2 supply from the combustion or gasification of biomass has GHG emissions of –1.62 gCO 2 eq./g CO 2 delivered and is the case with the lowest carbon footprint for supplied CO2. The emissions for all the CO 2 supply cases were found to be negative, either because of capturing more CO 2 from the atmosphere than is released from the CO 2 production process, or because of production of excess electricity that is exported to the grid (replacing emissions from grid electricity). A purpose-built Natural Gas Combined Cycle (NGCC) power plant CO 2 source has the highest GHG emissions of -0.40 gCO 2 eq./gCO 2 delivered of the cases considered because of nighttime emissions and natural gas supply chain losses. The impact of a diurnal cycle can be mitigated by using capture and refrigeration systems as part of the CO 2 management system. The results are sensitive to the GHG emissions of the grid electricity, which is imported or exported in different cases. The results provide a benchmark for the comparison of different CO 2 supply options for the establishment of a sustainable algal biorefinery.

42 ENGINEERING↗
DOE OSTI2022

Electrochemical Ammonia Compression

An electrochemical (EC) compressor is a solid-state compression device. For decades, researchers have been studying EC compressors for applications for a variety of energy systems. As the world transitions away from fossil fuel energy sources, EC compression emerges as a promising technique for energy storage, specifically energy stored in the form of pressurized ammonia. Ammonia is also a commonly used refrigerant. The present studies examine the viability of EC compression for ammonia storage and refrigeration. EC ammonia compression increases the concentration of an ammonia-hydrogen mixture via the input of electrical energy and a series of chemical reactions. A polymer electrolyte membrane separates the low-concentration side from the high-concentration side of the device. On the low-pressure (anode) side hydrogen atoms oxidize and react with ammonia molecules, forming positively charge ammonium ions. The ions traverse the membrane electrolytically. The ammonium ions are reduced and revert back to hydrogen and ammonia upon reaching the high-pressure (cathode). An external circuit provides the current needed to sustain the reactions. In this project, we studied the performance of the ammonia EC compressor under a variety of different conditions. We replicated preliminary data and using a small cell with 5 cm2 of active area. We demonstrated the operation of larger cells with 100 cm2 of active area. Further, we used a commercially available hydrogen EC compressor stack to analyze the scaled-up compressor performance. While previous experiments examined only the transient EC compressor performance, we developed test facilities that allowed the compressor to reach steady state. We analyzed the effects of pressure and current on the EC compressor performance. We measured the flow rates of gas leaving the compressors and analyzed the composition using gas chromatography. We tested methods of separating ammonia from the effluent vapor, which contained hydrogen and water vapor. We found that back diffusion adversely affected the performance, especially when we maintained high pressure lifts.

25 ENERGY STORAGE↗
DOE OSTI2026

Cybersecurity Workforce Training for SMR Integration into Distribution Grids: A Competency Framework and Containerized Hands-On Lab for the SMR/DER/Microgrid Boundary

Small modular reactors (SMRs) and microreactors are entering the U.S. distribution grid as synchronous generation on feeders designed for loads and inverter-based distributed energy resources (DERs). No existing cybersecurity training program addresses this intersection of nuclear operations, DER management, and operational technology security. As subcontractor to Iowa State University on the CyDERMS Center, Argonne analyzed the relevant standards and training landscape, translated the resulting gaps into a twelve-objective competency framework across distribution-operator and graduate-analyst role tracks, and built a containerized training lab using a ∼400-bus composite grid model behind a realistically simulated Modbus TCP SCADA stack. The analysis isolates the balance-of-plant / energy-management-system (BOP/EMS) boundary as the critical jurisdictional seam where, as of March 2026, neither NRC nor NERC CIP cleanly claims cybersecurity responsibility for distribution-connected SMRs. The framework maps each objective across NIST CSF 2.0, ISA/IEC 62443, NIST NICE Task–Knowledge–Skill statements, and NRC RG 5.71 awareness-and-training controls. The training lab implements operator-recognition assessment scenarios spanning grid-side disturbances and telemetry-layer anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Terahertz Chiral Metamaterials Enabling Broadband Polarization Conversion Using Polarization Guiding Effect

Polarization control plays a vital role in terahertz (THz) photonics, enabling a wide range of applications from imaging and spectroscopy to sensing and wireless communication. However, conventional polarization control methods at THz frequencies are limited by narrow operational bandwidths and excessive absorption losses. In this work, we present a broadband THz polarization control based on the polarization guiding effect. We design and fabricate a THz polarization rotator capable of rotating incident linear polarization by 90°. The device consists of 24 twistingly stacked silicon–air metagrating layers that introduce a large degree of form birefringence, with each metagrating layer being 280 µm thick and sequentially twisted by 3.75°. Numerical simulations using the Berreman 4 × 4 method predict broadband operation of the device. Experimental validation using THz time-domain spectroscopy confirms efficient and broadband 90° polarization rotation from 0.2 to 1.25 THz. Based on this concept, we further propose THz Q-plates for the generation of broadband structured vector beams with radial and azimuthal polarization states. This work offers a scalable, material-agnostic platform for advanced THz polarization manipulation and vector beam engineering, opening new pathways for next-generation THz photonic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Detection of False Data Injection Attacks in Battery Stacks Using Input Noise-Aware Nonlinear State Estimation and Cumulative Sum Algorithms

Grid-scale battery energy storage systems (BESSs) are vulnerable to false data injection attacks (FDIAs), which could be used to disrupt state of charge (SoC) estimation. Inaccurate SoC estimation has negative impacts on system availability, reliability, safety, and the cost of operation. In this article a combination of a Cumulative Sum (CUSUM) algorithm and an improved input noise-aware extended Kalman filter (INAEKF) is proposed for the detection and identification of FDIAs in the voltage and current sensors of a battery stack. The series-connected stack is represented by equivalent circuit models, the SoC is modeled with a charge reservoir model and the states are estimated using the INAEKF. Further, the root mean squared error of the states’ estimation by the modified INAEKF was found to be superior to the traditional EKF. By employing the INAEKF, this article addresses the research gap that many state estimators make asymmetrical assumptions about the noise corrupting the system. Additionally, the INAEKF estimates the input allowing for the identification of FDIA, which many alternative methods are unable to achieve. The proposed algorithm was able to detect attacks in the voltage and current sensors in 99.16% of test cases, with no false positives. Utilizing the INAEKF compared to the standard EKF allowed for the identification of FDIA in the input of the system in 98.43% of test cases.

25 ENERGY STORAGE↗
DOE OSTI2025

Deep learning model for fast, science-based forecasting of fluid migration along faults in geologic carbon storage scenarios

Effective long-term geologic storage depends on robust site selection and credible, science-based forecasting of subsurface behavior to ensure storage integrity. For this work, we develop a deep learning–based reduced-order model (ROM) to quantify potential carbon dioxide (CO₂) and brine migration through geological faults. The ROM combines a Transformer model for binary classification and a Stacked Ensemble for regression, trained on a comprehensive dataset generated from 1400 physics-based reservoir simulations. Key geologic and operational parameters—including fault geometry, reservoir structure, and injection conditions—were systematically varied to capture a wide range of fluid migration scenarios. The ROM accurately predicts the onset of migration, cumulative migration volumes of both CO₂ and brine, and associated migration rates, as compared to an independent set of validation simulations, while significantly reducing computational cost compared to traditional simulation methods. Model performance was evaluated across diverse fault configurations, revealing that shallow reservoir geometry and fault angle are among the most influential factors governing migration behavior. Sensitivity analysis using SHapley Additive exPlanations (SHAP) provided interpretability, revealing distinct patterns in how geological and operational features drive transient versus cumulative migration outcomes. The ROM’s ability to rapidly simulate fault migration scenarios enables efficient sensitivity analyses, scenario evaluations, and decision support for site selection and monitoring design. This approach enhances the safety, scalability, and long-term operational performance of geologic carbon storage (GCS) systems by providing a robust, interpretable tool for predicting subsurface fluid migration and assessing fault-related migration potential.

42 ENGINEERING↗
DOE OSTI2025

AutoUncertainties: A Python Package for Uncertainty Propagation

Propagation of uncertainties is of great utility in the experimental sciences. While the rules of (linear) uncertainty propagation are straightforward, managing many variables with uncertainty information can quickly become complicated in large scientific software stacks. Often, this requires programmers to keep track of many variables and implement custom error propagation rules for each mathematical operator and function. The Python package AutoUncertainties, described here, provides a solution to this problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Resilience Design Patterns: A Structured Approach to Resilience at Extreme Scale (V.2.0)

Reliability is a serious concern for future extreme-scale high-performance computing (HPC) systems. Projections based on the current generation of HPC systems and technology roadmaps suggest the prevalence of very high fault rates in future systems. The errors resulting from these faults will propagate and generate various kinds of failures, which may result in outcomes ranging from result corruptions to catastrophic application crashes. Therefore, the resilience challenge for extreme-scale HPC systems requires coordination between various hardware and software technologies that are capable of handling a broad set of fault models at accelerated fault rates. Also, due to practical limits on power consumption in future HPC systems, they are likely to embrace innovative architectures, increasing the levels of hardware and software complexities. Therefore, the techniques that seek to improve resilience must navigate the complex trade-off space between resilience and the overheads to power consumption and performance. While the HPC community has developed various resilience solutions, application-level techniques as well as system-based solutions, the solution space of HPC resilience techniques remains fragmented. There are no formal methods to integrate the various HPC resilience techniques into composite solutions, nor are there methods to holistically evaluate the adequacy and efficacy of such solutions in terms of their protection coverage, and their performance & power efficiency characteristics. Additionally, few implementations of current resilience solutions are portable to newer architectures and software environments that will be deployed on future systems. We developed a new structured approach to the management of HPC resilience using the concept of resilience-based design patterns. In general, a design pattern is a repeatable solution to a commonly occurring problem. We identified the well-known solutions that are commonly used to deal with faults, errors and failures in HPC systems. In the initial design patterns specification (version 1.0), we described the various solutions, which address specific problems in the design of resilient HPC environments, in the form of patterns. Each pattern describes a problem caused by a fault, error or failure event in an HPC environment, and then describes the core of the solution of the problem in such a way that this solution may be adapted to different systems and implemented at different layers of the system stack. The catalog of these resilience design patterns provides designers with a collection of design elements. To construct complete resilience solutions using combinations of various patterns, we defined a framework that enhances HPC designers' understanding of the important constraints and the opportunities for the design patterns to be implemented and deployed at various layers of the system stack. The design framework is also useful for establishing interfaces and mechanisms to coordinate flexible fault management across hardware and software components, as well as to consider the trade-off between performance, resilience, and power consumption when constructing a solution. The resilience design patterns specification version 1.1 included more detailed explanations of the pattern solutions, the context in which the patterns are applicable, and the implications for hardware or software design. It also provided several additional examples and detailed case studies to demonstrate the use of patterns to build realistic solutions. In version 1.2 of the specification document, we have improved the pattern descriptions, including graphical representations of the pattern components. These improvements are largely based on critical comments, feedback and suggestions received from pattern experts and readers of the previous versions of the specification. The pattern classification has been modified to further clarify the relationships between pattern categories. This version of the specification also introduces a pattern language for resilience design patterns. The pattern language presents the patterns in the catalog as a network, revealing the relations among the resilience patterns. The language provides designers with the means to explore alternative techniques for handling a specific fault model that may have different efficiency and complexity characteristics. Using the pattern language also enables the design and implementation of comprehensive resilience solutions as a set of interconnected resilience patterns that can be instantiated across layers of the system stack. The overall goal of this work is to provide hardware and software designers, as well as the users and operators of HPC systems, a systematic methodology for the design and evaluation of resilience technologies in HPC systems that keep scientific applications running to a correct solution in a timely and cost-efficient manner despite frequent faults, errors, and failures of various types. Version 2.0 expands the resilience design pattern classification and catalog to include self-stabilization patterns and reliability, availability and performance models for each structural pattern.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Electrochemical Compression for Ammonia Storage and Refrigeration System (Phase 2)

In this project, we studied the performance of the ammonia EC compressor under a variety of different conditions. We replicated preliminary data and using a small cell with 5 cm 2 of active area. We demonstrated the operation of larger cells with 100 cm 2 of active area. Further, we used a commercially available hydrogen EC compressor stack to analyze the scaled-up compressor performance. While previous experiments examined only the transient EC compressor performance, we developed test facilities that allowed the compressor to reach steady state.

25 ENERGY STORAGE↗
DOE OSTI2022

Best Practices for Energy Management Information Systems Metadata Schemas

The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of Energy Management Information Systems (EMIS) at federal facilities. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. The use of standard naming conventions and a metadata schema, which may be referred to as 'data tags,' improves the ability of the EMIS to consistently analyze, visualize, and derive value from operational data. To help address these issues, this fact sheet highlights best practices for use of metadata in an EMIS stack, which can significantly reduce the initial time required to deploy an EMIS.

EMIS↗
DOE OSTI2022

Investigation of long-term light stability of negative charge injected into oxide-nitride-oxide passivation stack of crystalline silicon solar cells

A negatively charged oxide-nitride-oxide stack for field-effect passivation of crystalline silicon solar cells is discussed. The negative charge was injected into the stack by a plasma charge injection technology. Charge stability was studied by exposing samples to AM1.5 simulation visible light and full-spectrum light at temperatures ranging from 55 to 78 °C for up to 300 h. Charge injection and loss were quantified based on shifts in the flatband voltage of capacitance–voltage curves measured with a mercury probe. The most probable mechanism of charge loss was found to be diffusion of negative charged hydrogen atoms through nitride and bottom oxide. The optimum recipe for each layer of the stack was investigated to minimize the loss of injected charge. The flatband voltage decay of the optimized stack was found to fit a power-law trend, suggesting the dispersive transport of hydrogen atoms with a dispersion parameter of ~0.06–0.07. The optimized stack is projected to maintain a negative charge density of about 3.6 × 10 12 cm –2 or more after 25 years of field operation in an environment such as Arizona, which would be sufficient for field-effect passivation under one-sun illumination. Furthermore, the high stability of the negative injected charge makes the plasma charging technology a safer and lower cost alternative to Al 2 O 3 -passivation technology commonly used to passivate p-type surfaces.

14 SOLAR ENERGY↗
DOE OSTI2026

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗
DOE OSTI2021

High-order algorithmic developments and optimizations for large-scale GPU-accelerated simulations (Milestone CEED-MS36)

The goal of this milestone was to improve the high-order software ecosystem for CEED-enabled ECP applications by making progress on efficient matrix-free kernels targeting forthcoming ECP architectures. These kernels included matrix-free preconditioning and the development of new set of CEED solver bake-off problems. As part of this milestone, we also released the next version of the CEED software stack, CEED-4.0, reported on results from several application collaborations, and documented the efforts of porting to AMD GPUs for Frontier and other modern architectures, such as Fugaku. The specific tasks addressed in this milestone were: (1) Port and run CEED benchmarks/miniapps on Frontier EA systems; (2) Demonstrate performant libCEED integration in MFEM, Nek and applications; (3) Matrix-free preconditioning of high-order operators; (4) Benchmark problems for fast high-order solvers on GPU platforms; and (5) Public release of CEED-4.0. The artifacts delivered include the next version of the CEED software stack, CEED-4.0, the next libCEED release, libCEED-0.8, and a number of developments integrated within applications to improve their GPU and CPU performance and capabilities. See the CEED website, https://ceed.exascaleproject.org and the CEED GitHub organization, https://github.com/ceed for more details.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Spectral Effects on the Energy Harvesting Efficiency of Two- and Four-Terminal Tandem Photovoltaics

In this work, the effect of a varying spectral irradiance and top cell bandgap on the energy harvesting efficiency of two-terminal (2T) and four-terminal (4T) perovskite//silicon tandem solar cells under outdoor operating conditions is investigated. For the comparison, an optoelectronic model employing a 1 year outdoor data set for a 4T mechanical stacked gallium arsenide (GaAs) on crystalline silicon (Si) tandem device is first validated. Then, the verified model is used to simulate perovskite//silicon tandem devices with a varying perovskite top cell bandgap for a location in Golden, Colorado, USA. Here, a spectral binning method to efficiently reduce and improve the visualization of the 1 min-resolved environmental data while maintaining the simulation accuracy is introduced. The findings reveal that, for a device that is current matched under standard testing conditions, the annual spectral deviation reduces the energy harvesting efficiency by only 2% rel . When additional realistic losses for the 4T are taken into account, 2T devices are shown to have an energy-harvesting efficiency that is at parity or higher. Deviations in the top cell bandgap are more than 0.1 eV from current matching result in a reduced energy harvesting efficiency of more than 5% rel for the 2T tandem device.

14 SOLAR ENERGY↗
DOE OSTI2025

Towards non-blinking and photostable perovskite quantum dots

Surface defect-induced photoluminescence blinking and photodarkening are ubiquitous in lead halide perovskite quantum dots. Despite efforts to stabilize the surface by chemically engineering ligand binding moieties, blinking accompanied by photodegradation still poses barriers to implementing perovskite quantum dots in quantum emitters. To date, ligand tail engineering in the solid state has rarely been explored for perovskite quantum dots. We posit that attractive intermolecular interactions between low-steric ligand tails, such as π-π stacking, can promote the formation of a nearly epitaxial ligand layer that significantly reduces the quantum dot surface energy. Here, we show that single CsPbBr 3 quantum dots covered by stacked phenethylammonium ligands exhibit nearly non-blinking single photon emission with high purity (~98%) and extraordinary photostability (12 hours continuous operation and saturated excitations), allowing the determination of size-dependent exciton radiative rates and emission line widths of CsPbBr 3 quantum dots at the single particle level.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hydrogen-powered Electrochemically-driven CO 2 Removal from Air Containing 400 to 5000 ppm CO 2

The performance of a hydrogen-powered, electrochemically-driven CO 2 separator (EDCS) was demonstrated at cathode inlet CO 2 concentrations from 400 ppm to 5,000 ppm. The impact of current density and CO 2 concentration were evaluated to predict operating windows for various applications. The single-cell data was used to scale a 100 cm 2 , multi-cell stack using a shorted-membrane design for four applications: direct air capture (DAC), hydroxide exchange membrane fuel cell (HEMFC) air pretreatment, submarine life support, and space habitation. For DAC, a 339-cell EDCS stack (7.7 L, 17 kg) was projected to remove 1 tonne CO 2 per year. The addition of the EDCS in HEMFC systems would result in nearly a 30% increase in volume, and therefore further improvements in performance would be necessary. A module containing five 338-cell EDCS stacks (38 L, 85 kg) in parallel can support a 150 person crew at 2.1% of the volume of the liquid amine system employed in submarines. For space habitation, a 109-cell EDCS stack (3.2 L, 10 kg) is adequate for 6 crewmembers, and is less than 1% the size and 5% the weight of the current CO 2 removal system installed on the International Space Station.

25 ENERGY STORAGE↗
DOE OSTI2020

Validation of an Advanced High-Pressure PEM Electrolyzer and Composite Hydrogen Storage

One of the challenges associated with transitioning our nation’s transportation economy to any alternative fuel is bringing fuel production, storage, transportation, and end-customer delivery infrastructure online. There are challenges associated with planning and implementing hydrogen fueling stations at locations relevant to the parallel effort of bringing the related transportation vehicles into the market. There are additional challenges associated with the operation of hydrogen fueling stations and reducing operating costs through energy reduction. Through calculation and design efforts it was concluded that elevating the pressure of a PEM cell stack and further developing hydrogen processing equipment that support elevated pressures while maintaining similar characteristics to their current production counterparts will yield in energy savings and by extension cost reductions. In this report, the design of a 57-bar (827-psig) electrolysis system and electrolysis cell stack is described. Furthermore, the fabrication, component verification, and integrated testing are summarized. Prior to this development effort, Proton had demonstrated thousand of hours of durability on 30-bar (435-psig) differential pressure PEM electrolysis hardware. Proton has sold and installed many of these 30-bar devices at customer sites. Through this project, Proton has developed and tested 57-bar PEM electrolysis, thereby extending the proven capability of PEM electrolysis as a hydrogen generation and electrochemical compression device. A design and validation effort to arrange hydrogen processioning equipment for refueling OEM vehicles was also undertaken within this project. By arranging equipment within two 6-meter ISO shipping containers and further developing NFPA 2 Hydrogen Technologies Code to support containerized hydrogen equipment, efforts to site, install, and commission, and approve hydrogen fueling stations were reduced and now provide a groundwork for future installations.

08 HYDROGEN↗
DOE OSTI2022

CO 2 to Fuels Through Novel Electrochemical Catalysis (Final Report)

Electrochemical upgrading of CO 2 into hydrocarbon fuels via CO 2 –H 2 O co-electrolysis using solid oxide electrolysis cells (SOECs) presents an encouraging approach to cost-effective storage of renewable power. In this study, we harness the unique property of protonic ceramic electrolysis cells (PCEC) and demonstrate direct electro-catalytic production of CH 4 from CO 2 –H 2 O in a unit-cell stack configuration. The unit-cell stack was developed to evaluate the scalability and the applicability of PCECs from a broader system-level viewpoint. Tradeoffs between operating conditions and performance metrics were explored and thoroughly characterized. An exceptional CH 4 -yield ratio of 34.6% from only CO 2 –H 2 O reactants was achieved under an electrolysis current of 1 A cm –2 at 450 °C. With exhaust-H 2 recycle, this value was boosted to greater than 70%. In addition, the electrochemical co-conversion of CO 2 –H 2 O offers a higher CH 4 -yield ratio compared to traditional thermo-catalytic conversion of CO 2 –H 2 under certain operating conditions, indicating possible electrochemical promotion of catalytic CO 2 methanation. The demonstrated good performance is a promising result for further scale-up and for the practical utilization of electrochemical CO 2 upgrade using PCECs. Techno-economic analyses reveal operating conditions that yield cost-competitive levelized cost of fuel production.

01 COAL, LIGNITE, AND PEAT↗