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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 OSTI2026

Metamaterials as a Platform for the Development of Novel Materials for Energy Applications

To explore the fundamental properties of metamaterials (MMs) / metasurfaces and their potential for control of energy at the sub‐wavelength scale in support of the mission of the Department of Energy and the office of Basic Energy Sciences. Electromagnetic metamaterials provide a platform for the discovery and design of new materials with novel structures, functions, and properties. The PI proposes to advance the knowledge base of these materials through fundamental investigations of the experimental and theoretical properties of metamaterials for the discovery, prediction and design of new materials with novel structures, functions, and properties. The proposed research activities emphasize a complete basic research program including the conceptual / computational design, fabrication / synthesis of the materials, and the characterization and analysis of their electromagnetic properties. The proposed project explores the fundamental properties of metamaterials / metasurfaces and their potential for energy applications. There are three main topics which will be investigated: 1) Dispersion engineering with metamaterials and metasurfaces, 2) Epsilon near zero metamaterial absorbers and emitters, and 3) All dielectric metamaterials. The program implements a complete basic research program consisting of theory / design, modeling, characterization, and analysis, in order to fully characterize metamaterials and metasurfaces, while at the same time minimizing iterations necessary to achieve the proposal goals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Technoeconomic Design Optimization for Fast Reactors. Part I: Workflow Development and Case Study for Small LFR District Energy Application

The nuclear industry is developing small reactor designs that can target a variety of deployment locations and energy products. Smaller nuclear designs have traditionally struggled to handle the steep trade-offs between size and cost that have historically incentivized large reactors. This motivates computational optimization of small reactors to minimize costs and quantify the trade-off between size and cost. In this paper, the cost/size trade-off for a small fast reactor is derived using a multi-objective genetic algorithm optimization, with steady-state, transient, and cost analysis of the fast reactor being performed. Specifically, the method is demonstrated on a small 10- to 120-MW(thermal) U-Pu-Zr–fueled lead-cooled fast reactor with a 10-year core life for district energy applications, which can have a thermal load compatible with this range. The results reinforced that fast reactor cores at the lower end of this power range suffer cost penalties due to critical mass considerations. It was found that high power density cores with strong reactivity swings and many control rods were favored over designing to minimize reactivity swing. Furthermore, this contrasts with some traditional configurations designed using engineering judgment and demonstrates that optimizers can find nontraditional but realistic solutions, along with demonstrating the value of incorporating cost functions into whole-reactor design optimization.

Fast reactor↗
NASA NTRS1974

Assessment of the technology required to develop photovoltaic power system for large scale national energy applications

A technical assessment of a program to develop photovoltaic power system technology for large-scale national energy applications was made by analyzing and judging the alternative candidate photovoltaic systems and development tasks. A program plan was constructed based on achieving the 10 year objective of a program to establish the practicability of large-scale terrestrial power installations using photovoltaic conversion arrays costing less than $0.50/peak W. Guidelines for the tasks of a 5 year program were derived from a set of 5 year objectives deduced from the 10 year objective. This report indicates the need for an early emphasis on the development of the single-crystal Si photovoltaic system for commercial utilization; a production goal of 5 x 10 to the 8th power peak W/year of $0.50 cells was projected for the year 1985. The developments of other photovoltaic conversion systems were assigned to longer range development roles. The status of the technology developments and the applicability of solar arrays in particular power installations, ranging from houses to central power plants, was scheduled to be verified in a series of demonstration projects. The budget recommended for the first 5 year phase of the program is $268.5M.

Lutwack, R.↗
DOE OSTI2025

Data efficiency assessment of generative adversarial networks in energy applications

This study investigates the data requirements of generative artificial intelligence (AI), particularly generative adversarial networks (GANs), for reliable data augmentation in energy applications. Generative AI, though seen as a solution to data limitations, requires substantial data to learn meaningful distributions—a challenge often overlooked. This study addresses the challenge through synthetic data generation for critical heat flux (CHF) and power grid demand, focusing on renewable and nuclear energy. Two variants of GAN employed are conditional GAN (cGAN) and Wasserstein GAN (wGAN). Our findings include the strong dependency of GAN on data size, with performance declining on smaller datasets and varying performance when generalizing to unseen experiments. Mass flux and heated length significantly influence CHF predictions. wGAN is more robust to feature exclusion, making it suitable for constrained synthetic data generation. In energy demand forecasting, wGAN performed well for solar, wind, and load predictions. Longer lookback hours and larger datasets improved predictions, especially for load power. Seasonal variations posed challenges, with wGAN achieving a relatively high error of Root Mean Squared Error (RMSE) of 0.32 for load power prediction, compared to RMSE of 0.07 under same-season conditions. Feature exclusions impacted cGAN the most, while wGAN showed greater robustness. This study concludes that, while generative AI is effective for data augmentation, it requires substantial data and careful training to generate realistic synthetic data and generalize to new experiments in engineering applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Synthesis Methods for Nanoparticle Morphology Control in Energy Applications

Lightweight nano-composite materials, nano-coatings, nanocatalysts, nano-structured materials have demonstrated an ability to reduce emissions and maximize clean energy production. Nanoparticles play an important role in engineering and decarbonization for energy applications, and a wide range of nanoparticle synthesis methods have been developed to include those that enable control over particle morphology. The ability to control nanoparticle morphology allows the tailoring and improvement of material properties that will accelerate efforts towards lowering carbon emissions by developing advanced catalysts for carbon sequestration and will enhance energy efficient processes and technologies. Synthesis methods aimed towards shape control of nanoparticles have demonstrated an ability to form spheres, rods, flower-like shapes, cubes, plates, shells, and chiral geometries. Processing methods used to form these morphologies include microwave assisted synthesis, solvothermal, hydrothermal, and a wide range of capping agents. A discussion of a few of these methods is given along with results and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

3D printing of metal-based materials for renewable energy applications

Large-scale renewable energy must overcome conversion and storage challenges before it can replace fossil fuels due to its intermittent nature. However, current sustainable energy devices still suffer from high cost, low efficiency, and poor service life problems. Recently, porous metal-based materials have been widely used as desirable cross-functional platforms for electrochemical and photochemical energy systems for their unique electrical conductivity, catalytic activity, and chemical stability. To tailor the porosity length scale, ordering, and compositions, 3D printing has been applied as a disruptive manufacturing revolution to create complex architected components by directly joining sequential layers into designed structures. In conclusion, this article intends to summarize cutting-edge advances of metal-based materials for renewable energy devices (e.g., fuel cells, solar cells, supercapacitors, and batteries) over the past decade.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Laboratory Testing to Assess the Feasibility of Polyurethane Flat Belts for Marine Energy Applications

Polyurethane flat belts have received limited scientific attention as load-bearing elements in marine energy systems, particularly in applications involving dynamic tensile and bending loads. This study evaluates their potential as a replacement for traditional wire ropes in marine energy applications, with a focus on their ability to be integrated into winch-driven wave energy converters where bending and tensile stresses can make long-term operation difficult. Polyurethane belts are hypothesized to offer enhanced fatigue resistance due to their reduced thickness in the bending plane and therefore lower bending stresses. This research involves a series of tests utilizing the National Renewable Energy Laboratory’s (NREL) Large-Amplitude Motion Platform to replicate the dynamic conditions experienced by mooring lines of winch-based point-absorber-type marine energy converters. The conditions tested include unequal coiling and uncoiling tensions and load cases resulting from the device’s unconstrained movement relative to its anchor, such as twisting and off-axis loading. Results from this study show that polyurethane flat belts can achieve more than 198 percent of the fatigue life of a conventional wire rope under similar load profiles. The stress concentrations resulting from off-axis loading and cumulative twist beyond the system’s allowable limits have been identified as potential failure modes for flat belt mooring lines used in winch-driven wave energy converters deployed in ocean environments. To mitigate these risks, the use of anti-spin systems and fairleads designed to accommodate off-axis loading while limiting twist accumulation is recommended.

13 HYDRO ENERGY↗
DOE OSTI2020

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Atomic Structure, Dynamics, Changes in Chemical Bonding and Semiconductor-Metal Transition in Sb 2 Se 3 : A Remarkable Material for Quantum Networks and Energy Applications

Antimony sesquiselenide has become an outstanding functional material for photovoltaics, energy storage and transformation, memory and photonic applications. Sb 2 Se 3 is one of the most successful emerging solar light absorbers and has also been identified as a highly promising ultralow-loss phase-change material (PCM) for next-generation coherent nanophotonic processors, photonic tensor cores, quantum and neuromorphic networks. Unlike benchmark telluride PCMs, Sb 2 Se 3 features a quasi-one-dimensional (1D) crystalline structure consisting of (Sb 4 Se 6 ) ∞ ribbons, lacks the typical PCM chemical bonding, and undergoes an extended semiconductor-metal transition above the melting point. Consequently, the origin of high optical contrast between crystalline (SET) and amorphous (RESET) logic states remains elusive and presents a significant challenge. Using high-energy X-ray diffraction and Raman spectroscopy over a wide temperature range, supported by first-principles simulations and complemented by thermal, optical and electrical measurements, as well as by 121 Sb-Mossbauer spectroscopy, the quasi-1D network of orthorhombic antimony sesquiselenide was found to undergo significant evolution in amorphous and supercooled Sb 2 Se 3 , leading to lower coordination, shorter interatomic distances and a higher p-electron density on antimony, indicating changes in chemical bonding. The observed novel Sb 2 Se 3 nanocrystalline polymorph, characterized by trigonal antimony coordination and more isolated Sb-Se ribbons, could help reduce multiple trapping defect states in the bandgap, which are typical of orthorhombic Sb 2 Se 3 , thereby enhancing the power-conversion efficiency of photovoltaic devices. Semimetallic and metallic liquid Sb 2 Se 3 exhibit a gradual transformation into a denser 2D and/or 3D network with higher antimony coordination. Localized electron states in the pseudogap are becoming extended, leading to an increase in electronic conductivity σ following the relationship σ ∝ N(E F ) 2 . Liquid Sb 2 Se 3 also appears to be strongly fragile, with a nonmonotonic change in viscosity and higher atomic mobility in the metallic liquid. Furthermore, these results explain extraordinary functionalities of Sb 2 Se 3 for photonic and energy applications.

antimony↗
DOE OSTI2023

Defect graph neural networks for materials discovery in high-temperature clean-energy applications

We present a graph neural network approach that fully automates the prediction of defect formation enthalpies for any crystallographic site from the ideal crystal structure, without the need to create defected atomic structure models as input. Here we used density functional theory reference data for vacancy defects in oxides, to train a defect graph neural network (dGNN) model that replaces the density functional theory supercell relaxations otherwise required for each symmetrically unique crystal site. Interfaced with thermodynamic calculations of reduction entropies and associated free energies, the dGNN model is applied to the screening of oxides in the Materials Project database, connecting the zero-kelvin defect enthalpies to high-temperature process conditions relevant for solar thermochemical hydrogen production and other energy applications. The dGNN approach is applicable to arbitrary structures with an accuracy limited principally by the amount and diversity of the training data, and it is generalizable to other defect types and advanced graph convolution architectures. In conclusion, it will help to tackle future materials discovery problems in clean energy and beyond.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Reflectance of metallic indium for solar energy applications

An investigation has been conducted in order to compile quantitative data on the reflective properties of metallic indium. The fabricated samples were of sufficiently high quality that differences from similar second-surface silvered mirrors were not apparent to the human eye. Three second-surface mirror samples were prepared by means of vacuum deposition techniques, yielding indium thicknesses of approximately 1000 A. Both hemispherical and specular measurements were made. It is concluded that metallic indium possesses a sufficiently high specular reflectance to be potentially useful in many solar energy applications.

Bouquet, F. L.↗
DOE OSTI2021

Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.

Li, H↗
DOE OSTI2020

Self-Repairing Polymer-Modified Cements for High Temperature Geothermal and Fossil Energy Applications

In this work five novel polymer-cement composite formulations were prepared and evaluated as potential cementitious material alternatives to conventional wellbore cement. These cement composites were cured at 200 °C and their mechanical properties, including compressive strength, Young modulus, shear bond strength to steel casing, and self-healing and re-adhering (to steel) capability. Thermal stability was also evaluated by curing these cement materials at 200 °C for up to one month followed by determining their mineralogy and chemical composition by X-ray diffraction spectroscopy, 13C NMR, and total organic carbon. Permeability analysis was performed before and after healing a longitudinal fracture on unmodified cements and polymer-cement composites with the later showing lower (2nd/1st) permeability ratios with respect to base cements. Furthermore, a reduction in permeability of up to 80X on average with respect to their unmodified (base) cement, was observed in two polymer-cement formulations suggesting that the introduction of these polymers bring about self-healing capability. Two of the best performing polymer-cement composites were exposed to 30-day curing period at 200 °C showing that their self-healing capability is maintained. The composite stability is associated to the fact that the polymer material is stable as demonstrated by total organic carbon and NMR spectroscopy. These advanced polymer-cement composites with higher ductility and self-healing capability could be used as alternative wellbore cement materials for geothermal and fossil energy applications.

Rod, Kenton A.↗