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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Characterization of Electrochemical Behavior for Aqueous Organic Redox Flow Batteries

Use of aqueous redox flow batteries with organic redox-active materials holds great promise for large-scale and sustainable energy storage. The development of low-cost, highly efficient aqueous redox flow batteries lies in a comprehensive understanding of the electrochemical behaviors of redox-active compounds. In this work, an alkaline redox battery with organic dihydroxyphenazine sulfonate (DHPS) anolyte and ferro-/ferricyanide (Fe(CN) 6 ) catholyte is investigated as a typical example of aqueous redox flow batteries using organic redox-active materials. The electrochemical kinetics of DHPS and Fe(CN) 6 are separately characterized using the symmetrical cell design. The resistance components are calculated directly from the experimental measurement. The key kinetic parameters are extracted and compared for DHPS and Fe(CN) 6 electrolytes. The extracted parameters are validated with symmetrical and full flow cell simulations at different operating conditions. Key parameters and internal loss are also compared with all-vanadium redox flow batteries, representing current state of the art. In addition, our extracted key parameters from a symmetrical flow cell are compared with the measured key parameters by cyclic voltammetry, a widely deployed electroanalytical technique. The cell performance prediction of DHPS anolyte on a 780 cm 2 interdigitated cell is made and found the power density is peaked at 475 mW cm -2 at our measurement condition.

25 ENERGY STORAGE↗
DOE OSTI2023

Rapid CFD Using Machine Learning Algorithms (CRADA Final Report)

This is a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (“LLNL”) and Guardian Glass, LLC ("Guardian Glass") to develop a fast-running emulator of the reactive Computational Fluid Dynamics (“CFD”) simulations needed to understand the complex reactions and flows in the glass melting, fining, and forming subprocesses. This CRADA project is sponsored under the High-Performance Computing for Manufacturing (“HPC4Mfg”) Program of the Department of Energy’s Advanced Manufacturing Office (“AMO”) within the Energy Efficiency and Renewable Energy (“EERE”) Office.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Metal Halide Perovskite Photovoltaics Research

Metal halide perovskite (MHP) photovoltaics (PV) are a potentially transformational next-generation energy technology. These materials have remarkable and tunable physical properties that enable a range of process approaches to produce high-efficiency devices. NREL efforts address both basic material and device-level considerations to advance the state of the art in MHP PV and accelerate its path to market.

14 SOLAR ENERGY↗
DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗
DOE OSTI2025

Earth-Abundant Manganese Nitride Catalysts for Mild-Condition Ammonia Synthesis

Developing advanced catalytic materials for mild-condition ammonia (NH 3 ) synthesis is essential for improving the energy efficiency of the industrial Haber-Bosch process. Here, in this study, we report a ζ-phase manganese nitride (MnN 0.43 ) catalyst for low-temperature NH 3 synthesis. The as-synthesized MnN 0.43 catalyst is protected by a carbon shell, allowing for the storage and processing of the air-sensitive metal nitride under ambient conditions. After activation in situ, the MnN 0.43 catalyst exhibits high activity for NH 3 synthesis at 250–350 °C, surpassing the conventional noble metal based Ru/MgO catalyst. A combination of kinetic, chemisorption, isotope labeling and computational studies indicate that a nitrogen vacancy-mediated associative mechanism accounts for the catalytic enhancements. Our work highlights the great potential of earth-abundant transition metal nitrides for catalyzing mild-condition NH 3 synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Radiative Cooling Paints: Application on Warehouses and Integration with Phase Change Materials

Despite extensive research on radiative cooling (RC), researchers are still working to understand its best implementation strategy and potential benefits. Understanding this could be an instrumental part of reducing building energy costs and combating climate change. In this work, we introduce two concepts to achieve this goal and broaden the application of RC paints. While building energy simulations for RC are common, most studies focus on single-layer paints in residential settings. Limited research exists on warehouses, and no literature has conducted multi-climate zone analyses or included RC technologies with >90% reflectance. As RC technology advances in efficiency, versatility, and affordability, large-scale simulations across diverse climates are crucial, particularly for warehouses as a passive indoor temperature control solution. Here, a TRNSYS-modeled single-story warehouse assesses the energy impact of BaSO4-based RC paints. Another under-explored RC application is its integration with phase change materials (PCMs), which provide thermal regulation via latent heat storage. Though RC and PCMs have been combined by placing PCMs atop, beneath, or within RC layers, studies focus on either experiments or modeling, with no validation between the two. Here, we develop a simple RC+PCM experimental and modeling setup, placing RC paint atop an aluminum cell filled with a Rubitherm PCM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Recent Progress on Cerium Oxide‐Based Nanostructures for Energy and Environmental Applications

Cerium oxide (CeO 2 ) photo/electrocatalysts for energy storage and environmental applications have attracted considerable interest because of stable crystal structure, low toxicity/cost, superior chemical stability, stable redox (Ce 3+ /Ce 4+ ) pairs, abundant oxygen defects, and capablility for intense interaction with other materials. However, the wide bandgap and poor conductivity lower the CeO 2 photo/electrocatalytic and energy storage performances. To overcome these limitations, various modification strategies (tuning morphology, doping or loading of metal nanoparticles, and heterostructures) have been applied for the improvement of photocatalytic (removal of organic contaminants from water/wastewater and H 2 production and CO 2 reduction reactions) efficiency, electrocatalytic (hydrogen/oxygen evolution reactions and CO 2 reduction reactions), and energy storage performances (supercapacitor) of CeO 2 ‐based materials. Herein, the recent progress of CeO 2 ‐based materials for electro(photo)catalysis and energy storage applications has been discussed. The challenges and possible direction of CeO 2 ‐based materials for electro(photo)catalysis and energy storage applications have been emphasized. Furthermore, this comprehensive review is expected to advance the design of CeO 2 ‐based materials and their applications in electro(photo)catalysis and energy.

Ray, Schindra Kumar [Department of Chemistry North↗
DOE OSTI2021

Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials

Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects-their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches. Here, we present a reinforcement learning (RL) [Monte Carlo Tree Search (MCTS)] based on delayed rewards that allow for efficient search of the defect configurational space and allows us to identify optimal defect arrangements in low-dimensional materials. Using a representative case of two-dimensional MoS 2 , we demonstrate that the use of delayed rewards allows us to efficiently sample the defect configurational space and overcome the energy barrier for a wide range of defect concentrations (from 1.5 to 8% S vacancies)-the system evolves from an initial randomly distributed S vacancies to one with extended S line defects consistent with previous experimental studies. Detailed analysis in the feature space allows us to identify the optimal pathways for this defect transformation and arrangement. Comparison with other global optimization schemes like genetic algorithms suggests that the MCTS with delayed rewards takes fewer evaluations and arrives at a better quality of the solution. The implications of the various sampled defect configurations on the 2H to 1T phase transitions in MoS 2 are discussed. In this study, we introduce a RL strategy employing delayed rewards that can accelerate the inverse design of defects in materials for achieving targeted functionality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Wind power production from very large offshore wind farms

In this work, we provide the first quantitative assessment of power production and wake generation from offshore wind energy lease areas along the U.S. east coast. Deploying 15-MW wind turbines, with spacing equal to the European average, yields electricity production of 116 TWh/year or 3% of current national supply. However, power production is reduced by one-third due to wakes caused by upwind wind turbines and wind farms. Under some flow conditions whole wind-farm wakes can extend up to 90 km downwind of the largest lease areas, and the frequency-weighted average area with a 5% velocity deficit is 2.6 times the footprint of the lease areas. Simulations including maritime corridors demonstrate reduction in the wake effects leading to power-efficiency gains and may offer contingent benefits. First-order scaling rules are developed that describe how “wake shadows” from large offshore wind farms scale with prevailing meteorology and wind turbine installed densities.

15 MW↗
DOE OSTI2022

Scalable Gas Diffusion Electrode Fabrication for Electrochemical CO 2 Reduction Using Physical Vapor Deposition Methods

Electrochemical CO 2 reduction (ECR) promises the replacement of fossil fuels as the source of feedstock chemicals and seasonal storage of renewable energy. While much progress has been made in catalyst development and electrochemical reactor design, few studies have addressed the effect of catalyst integration on device performance. Using a microfluidic gas diffusion electrolyzer, we systematically studied the effect of thickness and the morphology of electron beam (EB) and magnetron-sputtered (MS) Cu catalyst coatings on ECR performance. We observed that EB-Cu outperforms MS-Cu in current density, selectivity, and energy efficiency, with 400 nm thick catalyst coatings performing the best. Additionally, the superior performance of EB-Cu catalysts is assigned to their faceted surface morphology and sharper Cu/gas diffusion layer interface, which increases their hydrophobicity. Tests in a large-scale zero-gap electrolyzer yielded similar product selectivity distributions with an ethylene Faradaic efficiency of 39% at 200 mA/cm 2 , demonstrating the scalability for industrial ECR applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solvent-free production of carbon materials with developed pore structure from biomass for high-performance supercapacitors

The study aimed at preparing porous carbon materials, with superhydrophilic characteristics and developed micro/mesoporous structure (CSB-800), from corn stover by a solvent-free method including pre-carbonization, ball milling, and activation. The effect of pre-carbonization, ball milling on the detailed structural composition and properties especially the hydrophilicity and porous structures were studied, and the potential application of CSB-800 as electrode in supercapacitors was also investigated. The results revealed that pre-carbonization increased the accessibility of raw materials as well as the efficiency of the ball milling with KOH, leading to small carbon particles with good dispersion behavior. Ball milling promoted the porosity, surface energy, hydrophilicity, crystallinity, and graphitization of the carbon materials. CSB-800 exhibited a high specific surface area of 2440.6 m 2 /g with developed micro and porous structures. The heteroatom nitrogen formed nitrogen-containing groups of N Q and N X, which provided faradaic pseudocapacitance when CSB-800 was used as an electrode material, and this material presented a specific capacitance of 398 F/g at 0.5 A/g in 1 M H 2 SO 4 electrolyte in a three-electrode system, while the value was 243 F/g in a two-electrode system, and the energy density reached 5.01 Wh/kg at a power density of 100 W/kg.

09 BIOMASS FUELS↗
DOE OSTI2022

Numerical modeling and parametric study of a dual purpose underground thermal battery

We report integrating thermal energy storage with building energy systems can enable flexible building electric demands at buildings to help mitigate the mismatch between electricity supply and demand. A novel building heating and cooling system that integrates a dual-source heat pump with hybrid thermal storage named dual-purpose underground thermal battery (DPUTB) has been developed for reshaping building electric demands. The proposed DPUTB integrated geothermal heat pump system is an original innovation that enables Grid-interactive Energy Efficient buildings. This paper focuses on the study of the novel DPUTB. The DPUTB works as both a thermal storage tank (an inner tank) and a ground heat exchanger (an outer tank separated from the inner tank by the insulation material). High fidelity and computationally effective models are needed to predict the performance of the novel DPUTB. This study has developed a simplified dynamic model for the DPUTB according to heat transfer and energy conservation principles and validated it by using experimental data obtained from testing a small-scale DPUTB apparatus. A parametric study was conducted to identify a design that can achieve the target thermal storage performance of load shift and energy efficiency. The parametric study results show that the inner tank shell thermal conductivity and the phase change material's melting point are the two most influencing factors on the performance of the DPUTB. One single full-size DPUTB with the identified design could provide 1-ton cooling (3.51 kW) with the supply temperature lower than 11 °C for 4 hours in summer after being fully charged in 8 hours. The inner tank filled with phase change material is for cooling thermal storage as a latent tank in the design. However, its capacity can be as high as 60 MJ as a sensible water tank for heating storage in winter. In the future study, the DPUTB model will be incorporated into the dual-source heat pump system for evaluating the overall system performance of demand side management in the long term.

25 ENERGY STORAGE↗
DOE OSTI2025

Pyrolyzer Assisted Vapor Transport Deposition of Antimony-Doped Cadmium Telluride

In this study, we developed a new method for in situ Sb doping of CdTe thin films combining vapor transport deposition with a Group V pyrolyzer to address Sb doping concentration and doping efficiency. The Sb doped CdSeTe (CdSeTe:Sb) films were deposited in solar cell structures under variations of Sb dopant source heater, vapor pyrolyzer temperature, and Cd vapor excess. Results indicate that although these parameters do not affect the CdTe morphology or crystal structure, they critically influence doping efficiency and trap concentration. Capacitance-voltage measurements show that a higher dopant heater (TD) or pyrolyzer (TP) temperature leads to higher net carrier concentration, achieving a net carrier concentration of 1016 cm-3 and 20% doping efficiency with a TD/TP combination of 600 degrees C/1100 degrees C. By tuning the Cd/Sb flux ratio during CdSeTe:Sb deposition, the lowest defect concentration is achieved at Cd/Sb of 1.4:1, which produced the best VOC CdSeTe:Sb cell. This demonstrates a path to produce high net carrier concentration polycrystalline CdTe thin film with a low concentration of dopant-induced defects.

14 SOLAR ENERGY↗
DOE OSTI2024

A butterfly-shaped acceptor with rigid skeleton and unique assembly enables both efficient organic photovoltaics and high-speed organic photodetectors

ABSTRACT It remains challenging to design efficient bifunctional semiconductor materials in organic photovoltaic and photodetector devices. Here, we report a butterfly-shaped molecule, named WD-6, which exhibits low energy disorder and small reorganization energy due to its enhanced molecular rigidity and unique assembly with strong intermolecular interaction. The binary photovoltaic device based on PM6:WD-6 achieved an efficiency of 18.41%. Notably, an efficiency of 19.42% was achieved for the ternary device based on PM6:BTP-eC9:WD-6. Moreover, the photodetection device based on WD-6 demonstrated an ultrafast response speed (205 ns response time at λ of 820 nm) and a high cutoff frequency of −3 dB (2.45 MHz), surpassing the values of most commercial Si photodiodes. Based on these findings, we showcased an application of the WD-6-based photodetection device in high-speed optical communication. These results offer valuable insights into the design of organic semiconductor materials capable of simultaneously exhibiting high photovoltaic and photodetective performance.

Science & Technology - Other Topics↗
DOE OSTI2024

Developing a Database of Bio-based Materials for Building Envelope Applications

Oak Ridge National Laboratory (ORNL) has been funded by the Department of Energy (DOE) to help accelerate the introduction of building envelope materials that would reduce the carbon footprint of the buildings sector. The DOE’s Building Technologies Office has historically sought to resolve the knowledge gaps regarding the energy efficiency and moisture durability of building envelope systems and to develop the data, guidance, and tools needed to facilitate rapid industry adoption of high-performance, moisture-managed envelope systems. This project will help accelerate the widespread acceptance of a new generation of building materials developed specifically with the intent of reducing the carbon footprint of buildings. We have produced a database of hygrothermal transport properties on low embodied carbon building materials that can be added to energy and durability simulation tools. Properties that were measured include density, heat capacity, thermal conductivity as a function of temperature and relative humidity, moisture dependent permeance, and sorption isotherms as a function of relative humidity. These data sets were measured following consensus national standards using state-of-the-art facilities. The data has been compiled and is being made available to building designers who require these data to assess these new materials in their designs. We will publish the data and seek its addition to reference databases such as the ASHRAE Handbook of Fundamentals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Application of Heat Transfer Enhancement (HTE) System for Improved Efficiency of Power Plant Condensers

The mission of the National Energy Technology Laboratory (NETL), a U.S. laboratory under the Department of Energy, is to drive innovation and deliver solutions for an environmentally sustainable and prosperous energy future. Through the U.S. Department of Energy (DOE)/Fossil Energy’s (FE) Crosscutting Research Program, NETL funded Interphase Materials to develop and demonstrate a technology to improve power plant condenser efficiency. From 2018 through 2021, Interphase Materials developed THERMOPHASE, an advanced material applied to the condenser during plant operation to increase efficiency and lower fuel consumption, CO 2 emissions, and water withdrawal. THERMOPHASE was evaluated in controlled environments where improvements to heat transfer and a reduction in fouling were observed. THERMOPHASE was also applied to the main condenser of the Longview Power plant and changes to the plant performance were monitored. After two years following application of THERMOPHASE, a reduction in condenser back pressure of 0.26 ± 0.13 inHg was observed resulting in an estimated $3.35M in fuel savings, 136 million lbs. of decreased CO 2 emissions, and 1,287 million gallons reduced water withdrawal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Materials FY 2021 Annual Progress Report

The Materials Technology subprogram supports the VTO’s mission to accelerate the deployment of clean energy technology toward achieving net-zero emissions in the transportation sector. Lighter vehicles with more efficient powertrains reduce energy use, decrease greenhouse gas (GHG) emissions, and save consumers money.

33 ADVANCED PROPULSION SYSTEMS↗