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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

NASA Thermal Recovery Energy Efficient System (TREES) for Aircraft Exergy Optimization

Future air vehicles will increasingly incorporate electrical powertrains that require very tight integration of power, propulsion, thermal, and airframe technologies. These complex and highly integrated sub-systems present a new exergy utilization and thermo-economics challenge due to the significant and highly distributed low-grade waste heat being produced. One system-wide solution is proposed that utilizes acoustic thermal energy conversion technologies to simultaneously provide thermal management and waste energy recycling for the entire vehicle. This system level solution serves to optimize aircraft exergy utilization.

Dyson, Rodger↗
NASA NTRS1983

ECUT: Energy Conversion and Utilization Technologies program. Industry, university and research interest in the US Department of Energy ECUT biocatalysis research activity

The results of a Research Opportunity Notice (RON) disseminated by the Jet Propulsion Laboratory for the U.S. Department of Energy Conversion and Utilization Technologies (ECUT) Program's Biocatalysis Research Activity are presented. The RON was issued in late April of 1983 and solicited expressions of interest from petrochemical and chemical companies, bioengineering firms, biochemical engineering consultants, private research laboratories, and universities for participating in a federal research program to investigate potential applications of biotechnology in producing chemicals. The RON results indicate that broad interest exists within the nation's industry, universities, and research institutes for the Activity and its planned research and development program.

Wilcox, R. E.↗
DOE OSTI2023

Identifying impacts of process, precursors, and defects in metal halide perovskite solar cells

With efficiencies of halide perovskite solar cells stagnating over the last few years at values above 25% and approaching thermodynamic limits, focus must shift to ensuring stability of these devices over the long term. The overarching goal of this project was to understand the root causes of instability in halide perovskite solar cells. Our approach was rooted in fundamental scientific pursuits, determining at the molecular level those processes responsible for degradation of the metal halide perovskite system, either in the precursor ink, or in the solid state. We then used this understanding to show that degradation leads to midgap states in halide perovskite semiconductors, explaining loss in performance; also, this in-depth understanding allowed us to develop specifically targeted solutions to prevent these degradation mechanisms. These include guidance about amines in perovskite inks, solvents to use (and not to use), and impacts of Cs incorporation to perovskite inks and solids. Finally, we achieved our end-of-project goal and demonstrated an effective lifetime of a halide perovskite solar cell of 5000 h, including measurement of devices over 3000 h, amongst the longest in the field. Overall, this project has considerably pushed forward the science of perovskite degradation and sets examples and groundwork for future studies to enable halide perovskite solar cells to be a successful solar energy conversion technology.

14 SOLAR ENERGY↗
NASA NTRS2007

Advanced Stirling Technology Development at NASA Glenn Research Center

The NASA Glenn Research Center has been developing advanced energy-conversion technologies for use with both radioisotope power systems and fission surface power systems for many decades. Under NASA's Science Mission Directorate, Planetary Science Theme, Technology Program, Glenn is developing the next generation of advanced Stirling convertors (ASCs) for use in the Department of Energy/Lockheed Martin Advanced Stirling Radioisotope Generator (ASRG). The next-generation power-conversion technologies require high efficiency and high specific power (watts electric per kilogram) to meet future mission requirements to use less of the Department of Energy's plutonium-fueled general-purpose heat source modules and reduce system mass. Important goals include long-life (greater than 14-yr) reliability and scalability so that these systems can be considered for a variety of future applications and missions including outer-planet missions and continual operation on the surface of Mars. This paper provides an update of the history and status of the ASC being developed for Glenn by Sunpower Inc. of Athens, Ohio.

Shaltens, Richard K.↗
DOE OSTI2020

Photoinduced charge transfer in transition metal dichalcogenide heterojunctions – towards next generation energy technologies

Increasing interest in using two-dimensional transition metal dichalcogenides (2D TMDCs) in optical energy conversion technologies creates a demand for improving the yields and lifetimes of photogenerated charge carriers. Despite inherently fast photocarrier decay in neat 2D TMDCs, the unique photophysics in these quantum-confined systems motivates continued effort to control the evolution of photoexcited states and create functional devices. Here, an intriguing strategy to accomplish this goal is to employ TMDCs in heterojunctions with appropriate semiconductors, where energy level offsets drive photoinduced charge transfer (PCT) across material interfaces. PCT in TMDC-based systems can be optimized for many different applications, such as driving free carriers to photocatalytic sites for redox reactions like water splitting, extracting charge to perform work in photovoltaics or photodetectors, and manipulating the spin and momentum valley electronic degrees of freedom for quantum computing systems. Here, we review recent strides in optimizing PCT for such applications through greater fundamental understanding of the photophysics that occurs at TMDC/semiconductor interfaces. After giving an overview of isolated TMDC properties, synthetic methods, and the basics of PCT, we discuss TMDCs in heterojunctions with several classes of materials, including other TMDCs, small molecule semiconductors, polymers, single-walled carbon nanotubes, quantum dots, perovskites, and electrolytes. In addition to highlighting the unique benefits of each materials category, we also identify parallels across common themes, such as the roles of charge-transfer states, spin, electronic coupling, delocalization, interfacial atomic morphology, and the precise design of energy landscapes to direct charge and energy motion. We hope to capture a broad range of the valuable work in this fast-paced field to inspire new research directions for employing PCT in targeted TMDC-based systems.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1979

Nuclear power source for electric propulsion

A low specific weight (20 to 40 Kg/Kwe), long life (6 to 10 year), 100 to 400 KWe nuclear electric propulsion (NEP) system can deliver 2,000 to 10,000 Kg payloads for intensive study of our solar system. The nuclear power source is about 80% of the NEP system mass, thus the NASA program is focused on developing the power source technology. Because of the long life requirements, direct thermal to electric energy conversion technology (thermionic and thermoelectric) is being pursued. In order to meet the low specific weight it is necessary to develop a 10 to 15% conversion module with a 875 K minimum heat rejection temperature and a 1675 K maximum input temperature. The thermoionic converter is about 9% efficient at these temperatures. The thermoelectric converter is limited to a 1300 K input temperature. So, the thermionic program is focused on improving the efficiency while the thermoelectric program is focused on increasing the temperature.

Mondt, J. F.↗
DOE OSTI2025

Understanding and controlling the fundamental photochemistry of protonic solar energy conversion (Final Scientific/Technical Report)

The selectivity and activity of most fuel-forming reactions are tunable by the concentration of electrons, holes, protons, and/or hydroxides. That is one reason why traditional solar energy conversion processes are used to drive these reactions, where light directly increases the concentration of electrons and holes. We, instead, took a different approach, using light to increase the concentration of protons and/or hydroxides. For this, we leveraged photophysical and solid-state physics theories, techniques, and design strategies previously developed for the study of traditional solar energy conversion processes. We designed and fabricated several materials platforms based on molecular photoacid and photobase dyes coupled with ion-exchange polymer membranes and assessed their fundamental photoelectrochemistry. We demonstrated control over built-in electric potentials, photovoltages, proton-transfer kinetics, and efficiency limits to our approach. Understanding the basic science of these dye-sensitized protonic membranes and their photochemical mechanisms is of use to the DOE-relevant processes of solar photochemical fuel formation, solar photodialytic desalination, and solar cells. Moreover, functional materials that we developed from this project may be of use to several broad-reaching fields and may provide the foundation for a completely new, inexpensive, and robust solar energy conversion technology.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Solid-State Exergy Optimized Electric Aircraft Thermal and Fault Management

Future air vehicles will increasingly incorporate electrical powertrains that require very tight system level integration of power, propulsion, thermal, fault protection, and airframe technologies. This paper provides an overview of a new category of thermal energy conversion technology that can be used to enable a fully solid-state integrated thermal and fault management electric aircraft protection system, while synergistically managing and recycling both the low-grade waste heat from electrical components and the high-grade waste heat from engine components. This is achieved with exergy amplification of the powertrain waste-heat, a new class of fast flight-weight breakers, new class of long variable conductance heat pipe with multiple switchable condensers, new class of turbofan integrated heat exchangers and a gradient-based powertrain system optimizer.

safety↗
NASA NTRS2020

Electric Aircraft Cooling with Bio-Inspired Exergy Management

Future air vehicles will increasingly incorporate electrical powertrains that require very tight system-level integration of power, propulsion, thermal, fault protection, and airframe technologies. This chapter provides an overview of a new category of thermal energy conversion technology and describes the development of the resulting Thermal Recovery Exergy Efficient System, TREES. TREES can be used to enable a fully solid-state integrated thermal and fault management electric aircraft protection system, while synergistically managing and recycling both the low-grade waste heat from electrical components and the high-grade waste heat from engine components. This is achieved with exergy amplification of the powertrain waste heat, a new class of fast flight-weight breakers, a new class of long variable-conductance heat pipes with multiple switchable condensers, a new class of turbofan-integrated heat exchangers, and a gradient-based powertrain system optimizer. This approach is like the human body’s thermal management system in which the heart, arteries, and veins are analogous to the turbofan, acoustic tubes, and heat pipes proposed herein.

Rodger W Dyson↗
DOE OSTI2020

Evaluating the Potential for Tidal Phase Diversity to Produce Smoother Power Profiles

Although tidal energy conversion technologies are not yet commercially available or cost-competitive with other renewable energy technologies like wind turbines and solar panels, tides are a highly predictable resource. Tidal energy’s predictability indicates that the resource could introduce less volatility into balancing the electric grid when compared to other renewables, a fundamentally desirable attribute for the electric system. More specifically, tidal energy resources are unique in that they have the potential to produce relatively smoother power profiles over time through aggregation. In order to generate smooth power profiles from tidal resources, sufficient complexity within the timing of tides is necessary within electrical proximity. This study evaluates the concept of aggregating diverse tides for the purpose of reducing periods of no and low energy production and creating smoother power profiles in regions around Alaska and Washington by calculating cross-correlations of tidal current velocity time series. Ultimately, study results show limited potential to exploit the resources for this purpose and describe the institutional mechanisms necessary to realize the benefits in practice.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Mesoporous Carbon-Based PGM-Free Catalyst Cathodes

Polymer electrolyte membrane fuel cell (PEMFC) is the most promising energy conversion technology which can be used as the power sources for the electric vehicles with the ultimate cleanness, (no carbon emission from the use of hydrogen), much-improved energy conversion efficiency, longer range, and rapid refueling. However, due to the large amount of platinum group metal (PGM) catalyst used in PEMFC electrodes, the high cost is the bottleneck for the broad commercialization of PEMFCs for transportation. Hence, there is a critical need to develop low-cost, high-performance PGM-free cathode catalysts that can dramatically reduce the cost of the catalyst in the PEMFC by one to two orders of magnitude. However, before PGM-free cathodes become viable, several technical challenges associated with PGM-free cathodes must be addressed, including the insufficient activity and stability of the catalysts as well as the large transport losses from the much thicker catalyst layer in the electrodes.

08 HYDROGEN↗
DOE OSTI2024

Reinforcement Learning Control for Enhancing Marine Hydrokinetic Turbine Energy Generation

This paper proposes a reinforcement learning-based method to maximize power generation for a direct-drive marine hydrokinetic turbine. A high levelized cost of energy (LCOE) is preventative in the widespread adoption of many marine energy conversion technologies. A straightforward way to reduce LCOE is to increase conversion efficiency and ensure maximum energy generation. The proposed method utilizes a damping control methodology, varying applied generator torque via a linear relationship between the applied damping coefficient and rotor speed. A state-action-reward-state-action (SARSA) algorithm has been used to learn the optimal control action for a given flow velocity. The proposed SARSA methodology uses Gaussian radial basis functions to create a three-dimensional surface to estimate the relationship between damping coefficient, incoming flow velocity, and coefficient of power (C p ). Here, the SARSA algorithm was compared against a baseline optimal tip speed ratio controller over a year-long flow velocity case profile while considering the effects of biofouling on the turbine system, where the proposed RL method generated 0.92% more energy than the baseline.

Damp↗
NASA NTRS1980

Solar cell array design handbook - The principles and technology of photovoltaic energy conversion

Photovoltaic solar cell array design and technology for ground-based and space applications are discussed from the user's point of view. Solar array systems are described, with attention given to array concepts, historical development, applications and performance, and the analysis of array characteristics, circuits, components, performance and reliability is examined. Aspects of solar cell array design considered include the design process, photovoltaic system and detailed array design, and the design of array thermal, radiation shielding and electromagnetic components. Attention is then given to the characteristics and design of the separate components of solar arrays, including the solar cells, optical elements and mechanical elements, and the fabrication, testing, environmental conditions and effects and material properties of arrays and their components are discussed.

Rauschenbach, H. S.↗
DOE OSTI2023

Using Co-Optimized Machine Learned Manifolds for Modeling Chemically Reacting Flows

Chemically reacting flows play a key role in a wide range of engineered systems, from chemical and polymer processing to combustion-based energy conversion technologies. Simulations of these flows involve solving a coupled set of partial differential equations for mass, momentum, energy, and all relevant chemical species in the system. Chemical reaction pathways may be extremely complex and involve hundreds or more intermediate species, with reactions that occur over timescales varying by several orders of magnitude - presenting a significant numerical stiffness challenge. The combination of these factors makes simulation of chemically reacting flows vastly more expensive than nonreactive simulations, and often makes direct solution of the governing equations intractable. It is necessary to apply lower-fidelity models in place of the detailed governing equations in order to reduce computational cost to enable reacting flow simulation tools to be used in the engineering design process. Many of the models employed for this purpose are based on reducing the dimension of the thermochemical state, motivated by the observation that the observed thermochemical states in a system lie on a low-dimensional manifold in thermochemical state space. This behavior occurs due to the fast equilibration of certain reactive and transport processes, and physics-based manifold models rely on idealized assumptions about the balance of timescales and the way in which chemistry and transport are coupled. In this work, we apply a novel method for data-driven manifold-based modeling that can leverage data from high-fidelity reacting flow simulations to improve model accuracy in cases where the physics-based modeling assumptions break down. The approach is designed to be broadly applicable across chemically reacting flow systems but is applied here to turbulent combustion modeling.

machine learning↗
DOE OSTI2020

Quantum Mechanical Evaluation of CZTS Properties for Photovoltaic Applications

As a quaternary semiconductor, CZTS (Cu 2 ZnSnS 4 ) shows promise as a thin-film solar cell material. The constituent elements in CZTS are abundant and non-toxic, and CZTS has an ideal band gap (~1.5 eV) for solar cell applications, which produces a large absorption coefficient. Unfortunately, the low efficiencies and difficulties in synthesizing the desired crystallographic phase (kesterite) and the associated formation of antisite defects limit its deployment. Using theoretical and computational tools, we investigated these current limitations, explored strategies to resolve these issues, and developed design guidelines to improve the efficiency of CZTS-based sunlight absorbers. We first sought to understand the challenges associated with synthesizing the kesterite phase and proposed ways to favor kesterite growth, thus adding to the understanding of CZTS photovoltaics. We also analyzed the major limitations at the atomic scale lowering the efficiency of CZTS: the low open-circuit voltage (V oc ) and the short carrier lifetime, thus addressing the technical effectiveness of CZTS photovoltaics. We believe the latter is due to Shockley-Read-Hall (SRH) recombination centers associated with point defects. We also studied the electronic structure of interfaces and defects introducing such recombination centers, and explored doping strategies to reduce SRH recombination. Ultimately, these efforts will benefit the public by contributing to the development of cheap and efficient solar energy conversion technologies made from abundant, non-toxic materials.

14 SOLAR ENERGY↗
DOE OSTI2020

Coal direct chemical looping process: 250 kW pilot-scale testing for power generation and carbon capture

Chemical looping combustion (CLC) is an energy conversion technology that can produce concentrated CO 2 stream without the need for a gas separation step, and thus, has the potential to drastically reduce the energy consumption and cost associated with CO 2 capture in power generation. The coal-direct chemical looping (CDCL) process is a CLC technology that uses a moving bed reducer configuration that can directly consume coal as a feedstock without requiring an upstream gasification step. An integrated 250 kW th CDCL pilot unit using iron-based oxygen carriers was constructed and demonstrated for over 1000 h of testing. The principles for the CDCL pilot unit design and operation are summarized in this article. During the 288-hour continuous operation testing, the CDCL pilot unit achieved >96% coal conversion with a CO 2 purity of >97%. Low carbon carryover into the combustor, i.e. <2%, was also confirmed during the test, which shows the capability of the moving bed reactor to retain and convert coal using the oxygen available on the iron-based oxygen carrier. The results from the pilot unit testing confirms the CDCL concept as a promising coal combustion technology for heat and power generation with CO 2 capture.

10 SYNTHETIC FUELS↗
NASA NTRS1988

ECUT (Energy Conversion and Utilization Technologies) program: Biocatalysis Project

Fiscal year 1987 research activities and accomplishments for the Biocatalysis Project of the U.S. Department of Energy, Energy Conversion and Utilization Technologies (ECUT) Division are presented. The project's technical activities were organized into three work elements. The Molecular Modeling and Applied Genetics work element includes modeling and simulation studies to verify a dynamic model of the enzyme carboxypeptidase; plasmid stabilization by chromosomal integration; growth and stability characteristics of plasmid-containing cells; and determination of optional production parameters for hyper-production of polyphenol oxidase. The Bioprocess Engineering work element supports efforts in novel bioreactor concepts that are likely to lead to substantially higher levels of reactor productivity, product yields, and lower separation energetics. The Bioprocess Design and Assessment work element attempts to develop procedures (via user-friendly computer software) for assessing the economics and energetics of a given biocatalyst process.

Source record↗
DOE OSTI2021

Forecasting Solar-Thermal Systems Performance under Transient Operation Using a Data-Driven Machine Learning Approach Based on the Deep Operator Network Architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

DeepONet↗