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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High-throughput oxygen chemical potential engineering of perovskite oxides for chemical looping applications

Chemical looping (CL) represents a versatile, emerging strategy for sustainable chemical and energy conversion. Designing metal oxide oxygen carriers with suitable redox properties remains one of the most critical challenges to CL due to the considerably different thermodynamic property requirements for different applications. Here, taking SrFeO 3–δ as a base-structure, this study seeks to rationally substitute its A- and/or B-site cations to tailor the equilibrium oxygen partial pressure over 20 orders of magnitude. 2401 Sr x A 1–x Fe y B 1–y O 3–δ perovskite-phase structures were investigated using high-throughput density functional theory (DFT) and 227, 273 high-entropy perovskites were screened via machine learning (ML). This significantly expands the materials design space. While most of the compositions predicted are new and nonobvious, 19 previously reported oxygen carriers, with excellent redox properties, were correctly identified by the algorithm. Moreover, we experimentally demonstrated 15 new oxygen carriers with superior redox performance. These results support the effectiveness of the high-throughput approaches for accelerated materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surface Engineering Strategy to Synthesize Bicomponent Carbons for Rechargeable Zinc-Air Batteries

Atomic Fe-N x moieties and nanosized FeCo species anchored on carbons have each been demonstrated to be among the most effective active components for oxygen reduction and evolution reactions (ORR/OER), respectively in rechargeable zinc -air batteries (ZABs). However, incorporating both of these components in a single catalyst presents a great challenge due to the trade-off in formation between them during hightemperature preparation. Herein, we integrate them into a bicomponent carbon through a surface engineering strategy. In this process, K 3 [Fe(CN) 6 ] is engineered on the surface of a precursor mixture consisting of polyaniline-coated graphene oxide and ZIF-67. This is followed by pyrolysis to produce the bicomponent carbon catalyst of FeCo nanoparticles modified carbon polyhedron (for accelerating the OER), supported on atomically dispersed Fe -N -doped carbon nanosheet (for boosting the ORR). The catalyst exhibits a small potential gap of 0.69 V for OER/ORR. In situ Raman spectroscopy demonstrates that spinel FeCo oxides may be responsible for OER. The use of this catalyst in ZABs achieves high power densities of 225 mW cm -2 in aqueous electrolyte and 164 mW cm -2 in solid-state electrolyte. Additionally, a small and stable voltage gap of 0.712 V at 10 mA cm -2 is maintained after 1035 discharge -charge cycles demonstrating the great application potential in energy devices.

An, Jia-Xing↗
DOE OSTI2026

Optimization of Desalination Systems with Detailed Water Chemistry through Integration of Reaktoro in WaterTAP

Chemistry predictions are critical for an accurate estimation of performance and costs in desalination process models, which allows for the estimation of the value of new technologies and the viability of treating new water sources. Herein, we present how an implicit function formulation can be used to integrate the chemical modeling package, Reaktoro, into the techno-economic assessment and modeling platform, WaterTAP. This approach resolves the critical issues of integrating large-scale thermodynamic models and databases into equation-oriented process models while allowing more flexibility relative to previously presented surrogate-based methods. We describe how this integration into Pyomo and WaterTAP models is implemented and used through the open-source package Reaktoro-PSE . We first validate this integration approach by performing optimization on a previously presented desalination treatment train with softening and acid addition as the pretreatment steps. Then, to demonstrate the value of this approach, we extend the cost-optimization problem to include the simultaneous addition of lime and soda ash for softening, and HCl and H 2 SO 4 in the acidification steps. Finally, we were able to confirm the previously established results that were obtained by using surrogate models and demonstrate that the implicit function approach enables exploration of different feedwater compositions and a larger number of chemicals and their combinations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accelerated Deterministic Phonon Transport With Consistent Material Temperature and Intensities

Abstract We present a method for deterministically solving the frequency and temperature dependent phonon radiative transport (PRT) equation in the single-mode relaxation time (SMRT) approximation in the self-adjoint angular flux (SAAF) form. To handle the nonlinear coupling between the phonon intensities and the material temperature, we apply a linearization approach that is similar to one in thermal radiative transport. This procedure leads to the PRT equation with pseudo-scattering. The method presented includes acceleration of both the inner pseudo-scattering source iterations and outer temperature iteration with a gray diffusion synthetic acceleration (DSA) and Anderson acceleration, respectively. We use the finite-element method to discretize the PRT equation in space and the method of discrete ordinates (SN) for angular discretization. The proposed method is verified by a gray method of manufactured solutions problem and demonstrated on a problem using temperature and direction dependent multigroup data from lithium aluminate (LiAlO2). The iterative performance of the acceleration method in each test is then compared to the unaccelerated method.

Engineering↗
DOE OSTI2021

Fatigue Performance of High-Strength Pipeline Steels and Their Welds in Hydrogen Gas Service

Objectives of the project include: Enable the use of high strength steel hydrogen pipelines, as significant cost savings can result by implementing high strength steels as compared to lower strength pipes. Demonstrate that girth welds in high-strength steel pipe exhibit fatigue performance similar to lower-strength steels in high-pressure hydrogen gas. Identify pathways for developing high-strength pipeline steels by establishing the relationship between microstructure constituents and hydrogen-accelerated fatigue crack growth (HA-FCG)

08 HYDROGEN↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Real-time pilot guidance system for improved flight-test maneuvers

The real-time pilot display uplink development at the Dryden Flight Research Facility is described, with a focus on recent F-104 studies. A nose boom gathers data on the Mach number, pressure altitude, and angle of attack. The system provides the pilot with guidance to improve maneuver accuracy and fly more complex trajectories. The uplink presents the pilot with computed differences between a reference flight path and actual flight state conditions, using a downlink to the ground where engineering computations are performed, feedback is transmitted, and corrections are applied. Details of the flight test trajectories and data from test results are provided for level turns, constant thrust turns, dynamic pressure trajectories, constant radar altitude accelerations and decelerations, and a Reynolds number trajectory. The system has proved capable of reducing pilot workload and saving fuel by decreasing the flight time necessary to obtain specific data.

Schneider, E. T.↗
NASA NTRS1984

Simulation evaluation of two VTOL control/display systems in IMC approach and shipboard landing

Two control/display systems, which differed in overall complexity but were both designed for VTOL flight operations to and from small ships in instrument meteorological conditions (IMC), were tested using the Ames Flight Simulator for Advanced Aircraft (FSAA). Both systems have attitude command in transition and horizontal-velocity command in hover; the more complex system also has longitudinal-acceleration and flightpath-angle command in transition, and vertical-velocity command in hover. The most important overall distinction between the two systems for the viewpoint of implementation is that in one - the more complex - engine power and nozzle position are operated indirectly through flight controllers, whereas in the other they are operated directly by the pilot. Simulated landings were made on a moving model of a DD 963 Spruance-class destroyer. Acceptable transitions can be performed in turbulence of 3 m/sec rms using either system. Acceptable landings up to sea state 6 can be performed using the more complex system, and up to sea state 5 using the other system.

Merrick, V. K.↗
NASA NTRS1991

Experiments on hypersonic ramjet propulsion cycles using a ram accelerator

Work on hypersonic propulsion research using a ram accelerator is presented. Several different ram accelerator propulsive cycles have been experimentally demonstrated over the Mach number range of 3 to 8.5. The subsonic, thermally choked combustion mode has accelerated projectiles to near the Chapman-Jouguet (C-J) detonation velocity within many different propellant mixtures. In the transdetonative velocity regime (85 to 115 percent of C-J speed), projectiles have established a propulsive cycle which allows them to transition smoothly from subdetonative to superdetonative velocities. Luminosity data indicate that the combustion process moves forward onto the projectile body as it approaches the C-J speed. In the superdetonative velocity range, the projectiles accelerate while always traveling faster than the C-J velocity. Ram accelerator projectiles operating continuously through these velocity regimes generate distinctive hypersonic phenomena which can be studied very effectively in the laboratory. These results would be very useful for validating sophisticated CFD computer codes and in collecting engineering data for potential airbreathing hypersonic propulsive systems.

Chew, G.↗
NASA NTRS2007

Sensitivity Testing of the NSTAR Ion Thruster

During the Extended Life Test of the DS1 flight spare ion thruster, the engine was subjected to sensitvity testing in order to characterize the macroscopic dependence of discharge chamber sensitivity to a +\-3% vatiation in main flow, cathode flow and beam current, and to +\5% variation in beam and accelerator voltage, was determined for the minimum- (THO), half- (TH8) and full power (TH15) throttle levels. For each power level investigared, 16 high/low operating conditions were chosen to vary the flows, beam current, and grid voltages in in a matrix that mapped out the entire parameter space. The matrix of data generated was used to determine the partial derivative or senitivity of the dependent parameters--discharge voltage, discharge current, discharge loss, double-to-single-ion current ratio, and neutralizer-keeper voltage--to the variation in the independent parameters--main flow, cathode flow, beam current, and beam voltage. The sensititivities of each dependent parameter with respect to each independent parameter were determined using a least-square fit routine. Variation in these sensitivities with thruster runtime was recorded over the duration of the ELT, to detemine if discharge performance changed with thruster wear. Several key findings have been ascertained from the sensitivity testing. Discharge operation is most sensitve to changes in cathode flow and to a lesser degree main flow. The data also confirms that for the NSTAR configuration plasma production is limited by primary electron input due to the fixed neutral population. Key sensitivities along with their change with thruster wear (operating time) will be presented. In addition double ion content measurements with an ExB probe will also be presented to illustrate beam ion production and content sensitivity to the discharge chamber operating parameteres.

electric propulsion↗
NASA NTRS2009

High-Throughput Top-Down and Bottom-Up Processes for Forming Single-Nanotube Based Architectures for 3D Electronics

We have developed manufacturable approaches to form single, vertically aligned carbon nanotubes, where the tubes are centered precisely, and placed within a few hundred nm of 1-1.5 micron deep trenches. These wafer-scale approaches were enabled by chemically amplified resists and inductively coupled Cryo-etchers for forming the 3D nanoscale architectures. The tube growth was performed using dc plasma-enhanced chemical vapor deposition (PECVD), and the materials used for the pre-fabricated 3D architectures were chemically and structurally compatible with the high temperature (700 C) PECVD synthesis of our tubes, in an ammonia and acetylene ambient. Tube characteristics were also engineered to some extent, by adjusting growth parameters, such as Ni catalyst thickness, pressure and plasma power during growth. Such scalable, high throughput top-down fabrication techniques, combined with bottom-up tube synthesis, should accelerate the development of PECVD tubes for applications such as interconnects, nano-electromechanical (NEMS), sensors or 3D electronics in general.

plasma-enhanced chemical vapor deposition (PECVD),↗
DOE OSTI2024

Presentation: Reactor Containment Passive Safety Analysis: Steam Condensation in Presence of Non-condensable Gas Scaled Experiment and Modeling

This study presents steam condensation scaled experiments and semi-empirical models in presence of nitrogen--a noncondensable gas (NCG), simulating air in the reactor containment--to support water-cooled small modular reactors (SMRs) passive containment cooling system (PCCS) design and analysis. Previous experimental studies on PCCS are focused on fixed and smaller tube (mostly 2-in.) geometries and specific test condition variations, bringing challenges with geometric scaling and mismatching with SMR prototypic design. To address these challenges, this study presents steam condensation test dataset obtained from three scaled test sections of 1-, 2-, and 4-in.-diameter steam condensers with an annular/jacket cooling of 2-, 3-, and 6 in.-diameter tubes, respectively. Test data were collected for steam ranges from 58 to 63 kg/hr., and NCG flow of 4.4 to 13.3 kg/hr. Annular cooling water flow was varied to obtain required testing conditions of saturated steam inlet and fully condensed outlet. Axial temperature test data of bulk cooling water, steam and condensate were collected by thermocouples for three test sections and various steam-NCG mixing/testing conditions. A standard data reduction method was adopted--utilizing iterative and nodalized mass and heat transfer calculation to estimate axial local heat fluxes, heat transfer coefficients (HTCs), condensation rates, film thickness, and Nusselt number. Based on the obtained dataset semi-empirical model results--a ratio of experimental and Nusselt's theoretical HTC are presented. Such results and findings are supportive of developing scaled-up testing facility, to enable model validations and accelerate next generation of reactors development and deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Effects of Electron Irradiation on Candidate Materials for Target Window in Accelerator-Driven Mo-99 Production

Room-temperature (RT) axial tensile tests were conducted in 2018 and 2021 with flat, sub-sized, dog-boned samples of non-irradiated and irradiated Inconel 718 and irradiated beryllium (Be). The sample gauge length was 7.62 mm. Tensile properties of interest are the engineering yield stress (YS), ultimate tensile stress (UTS), uniform elongation (UE) and total elongation (TE). The electron dose of the 2021 samples was ≈2 times the dose of samples tested in 2018. Relative dose rates of 0, 1 (2018), and 2 (2021) are assigned to these samples. The 2021 electron-irradiated Be samples were brittle with a low failure stress of 338±64 MPa based on two samples. The failures occurred in the gauge section. The 2018 results for electron-irradiated Be indicated a slight decrease in ductility and strength for the one electron-irradiated sample that failed in the gauge section.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

DevOps Pragmatic Practices and Potential Perils in Scientific Software Development

The DevOps movement, which aims to accelerate the continuous delivery of high-quality software, has taken a leading role in reshaping the software industry. Likewise, there is growing interest in applying DevOps tools and practices in the domains of computational science and engineering (CSE) to meet the ever-growing demand for scalable simulation and analysis. Translating insights from industry to research computing, however, remains an ongoing challenge; DevOps for science and engineering demands adaptation and innovation in those tools and practices. There is a need to better understand the challenges faced by DevOps practitioners in CSE contexts in bridging this divide. To that end, we conducted a participatory action research study to collect and analyze the experiences of DevOps practitioners at a major US national laboratory through the use of storytelling techniques. We share lessons learned and present opportunities for future investigation into DevOps practice in the CSE domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A high throughput assay to detect enzymatic polyethylene oxidation

Biological plastics deconstruction and upcycling have emerged as sustainable alternatives to traditional recycling technologies for plastics waste. The discovery and engineering of efficient thermostable poly(ethylene terephthalate) (PET) hydrolases have made biological PET recycling possible at scale; however, enzymes for non-PET plastics, which account for approximately 70% of all plastics produced, remain largely undiscovered. To accelerate the discovery of such enzymes, we develop a high-throughput screen to detect initial polymer oxidation, specifically that of the C-H bond to an aldehyde. We test 4-hydrazino-7-nitro-2,1,3-benxoxadiozole hydrazine (NBD-H), which reacts with generated aldehydes to form a fluorescent hydrazone on plasma oxidized low-density polyethylene (LDPE) films. Hydrazone generation correlated well with the area of aldehyde peaks as measured by Fourier Transform Infrared Spectroscopy (FTIR) (R2 = 0.92). Moreover, we demonstrate that the probe reliably identifies LDPE-active dye decolorizing peroxidases (DyPs) that generate aldehydes on LDPE films (1.7 – 3.0 fold change relative to background), serving as an effective screen as demonstrated by receiver operating characteristic area under the curve of 0.95. Furthermore, this assay offers an LDPE oxidation screening platform that can be readily parallelized and automated for accelerated discovery of enzymes involved in polyolefin deconstruction.

biocatalysis↗
DOE OSTI2023

Writing the Programs of Programmable Catalysis

It has long been known that non-steady state and periodic catalytic reactor operation in terms of temperature, pressure, and composition can lead to higher overall productivity and/or product selectivity than the best steady operation. Recently, the emergence of catalysts whose intrinsic properties can be made to oscillate with time, introduces advanced forcing capabilities that can be “programmed” into the catalysts to broaden the scope and applicability of periodic operation to surface chemistry. In this work, an algorithmic approach is implemented to significantly accelerate the discovery and optimization of periodic steady states of catalytic reactors. Decomposition of complex dynamics into fundamental mechanistic fast–slow steps is seen to improve conceptual understanding of the relationship between binding energy oscillation protocols and overall catalytic rates. Finding structured forcing protocols, optimally tailored to the multiple time scales of a given individual mechanism, requires an efficient search of high-dimensional parameter spaces. Here, this is enabled here through active learning (Bayesian optimization, enhanced by our proposed Bayesian continuation). Implementation of these methods is shown to accelerate the evaluation of catalyst programs by up to several orders of magnitude. Faster screening of programmable catalysts to discover periodic steady states enables the optimization of catalytic operating protocols and thus opens the possibility for catalyst engineering based on optimal forcing programs to control rate and product selectivity, even for complex multistep catalytic mechanisms.

catalysis↗
DOE OSTI2023

Data-driven electrolyte design for lithium metal anodes

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

25 ENERGY STORAGE↗