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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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Hydrogen generated by sunlight could play a major role in a low-carbon future, but high-efficiency demonstrations have been limited mostly to very small scales. New research now evaluates a complete system that generates 0.5 kg of hydrogen per day with 20% device (5.5% system) efficiency while showing the benefits of coupled light absorption and water electrolysis.
The paper examines technologies of hydrogen production. Its delivery, distribution, and end-use systems are reviewed, and a classification of solar energy and hydrogen production methods is suggested. The operation of photoelectric processes, biophotolysis, photocatalysis, photoelectrolysis, and of photovoltaic systems are reviewed, with comments on their possible hydrogen production potential. It is concluded that solar hydrogen derived from wind energy, photovoltaic technology, solar thermal electric technology, and hydropower could supply some of the hydrogen for air transport by the middle of the next century.
The solar wind hydrogen flux is mapped onto the topography of four lunar south pole craters; Shackleton, Haworth, Shoemaker and Faustini. Using altimetry data from the Lunar Reconnaissance Orbiter, we apply an analytic plasma model to map the hydrogen flux onto the surface, time-averaged over a lunar rotation cycle. We present a series of maps including the average flux, geomagnetic modulation, and ion flow energy. These results are intended to inform further studies of dynamic lunar surface processes, such as volatile implantation, sputtering,and weathering. As an example, we also present a map of a surface ice sheet lifetime based on ion sputtering.
This project achieved its overarching goal of accelerating the discovery and validation of solar thermochemical hydrogen (STCH) materials through a tightly integrated approach that combined high-throughput computational screening, advanced machine learning (ML), and experimental testing. Guided by the objectives outlined in the Statement of Project Objectives (SOPO), our work fulfilled all major milestones across four technical tasks and delivered scientific breakthroughs and practical tools that significantly exceeded the original scope of the project. We began by addressing the challenge of predicting material phase stability through machine learning. A novel Python module was developed to generate thousands of meaningful features from composition, structure, and electronic properties, enabling rapid and reproducible ML model development. Using these tools, we trained a model to predict temperature-dependent Gibbs energies (G(T)) for inorganic crystalline materials with near-chemical accuracy—roughly 40 meV/atom—marking the first such descriptor of its kind. We also introduced a new machine-learned tolerance factor, τ, that accurately predicted perovskite formability with over 90% success, outperforming traditional heuristic models, such as the Goldschmidt tolerance factor. These capabilities allowed for rapid and accurate predictions of phase stability across a vast oxide composition space, setting the stage for high-throughput thermodynamic screening. Building on this foundation, we conducted an extensive computational screening of candidate STCH oxide materials. Over 1.1 million perovskite compositions were evaluated using the τ descriptor, leading to the identification of more than 27,000 predicted stable structures. Using density functional theory (DFT), we refined over 68,000 multinary perovskite structures and computed oxygen vacancy formation energies for over 1,300 ternary and double perovskites. These calculations enabled us to isolate compounds with redox behavior consistent with STCH requirements and resulted in a public dataset now hosted on the Materials Project. Recognizing that thermodynamic screening alone is insufficient, we addressed kinetic limitations by developing a suite of tools to estimate transition state (TS) energies for key redox reactions. We implemented a novel bounding approach that provides lower and upper estimates of TS energies with dramatically reduced computational cost, requiring less than 10% of the CPU time of a full nudged elastic band (NEB) calculation while maintaining high accuracy. This enabled rapid evaluation of over 200 reaction pathways across 90 materials. To further accelerate screening, we developed a SISSO-based ML model to predict diffusion barriers with a 96.7% success rate in classifying fast vs. slow materials, supporting a robust, data-driven framework for assessing redox kinetics. Experimental validation was critical to confirming the predictive power of our models. We synthesized and tested a wide array of candidate materials, including Mn-doped hercynite and several Gd- and La-based perovskites. Notably, Sr 0.4 Gd 0.6 Mn 0.6 Al 0.4 O 3 (SGMA) and Gd 0.5 La 0.5 Co 0.5 Fe 0.5 O 3 (GLCF) emerged as leading STCH materials, exhibiting robust redox cycling and high hydrogen yields exceeding 150 µmol H 2 /g per cycle. These materials also retained over 50% of their hydrogen productivity under high-conversion conditions (H 2 O:H 2 = 1333:1), demonstrating strong thermodynamic favorability and promising performance under industrially relevant scenarios. Additional candidates, such as La 2 MnNiO 6 (L2MN), were found to produce even higher yields than ceria under standard STCH conditions. Our collaborators at Sandia National Laboratories confirmed these findings using high-temperature X-ray diffraction and thermogravimetric analysis, observing stable phase evolution and reversible redox activity. In several respects, the project went beyond the goals initially outlined in the SOPO. We published 17 peer-reviewed articles, including a large dataset of over 66,000 theoretical perovskites and a new structure prediction method (SPuDS-DFT) that accurately identifies ground-state structures at a fraction of the cost of traditional DFT. We demonstrated that our machine-learned G(T) model offers accuracy rivaling quasiharmonic calculations while being orders of magnitude faster. In partnership with the Materials Project, we made our datasets openly available, providing a powerful new resource for the broader materials science community. The combined computational and experimental advances of this project represent a significant advance in STCH materials discovery. By creating a robust, generalizable, and open workflow for thermodynamic and kinetic screening, and validating key findings through synthesis and reactor testing, we have provided a practical and scalable pathway for the rapid identification of new redox-active materials. The tools, data, and materials developed under this project are already supporting ongoing research and have laid the groundwork for the next generation of solar fuel technologies.
Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.
The innovative research conducted by Arizona State University and Princeton University in the project "Mixed Ionic-Electronic Conducting Quaternary Perovskites: Materials by Design for Solar Thermochemical Hydrogen" marks a significant stride forward in thermochemical water splitting. Through an intricate blend of computational design and experimental validation, the project delved into the promising potential of Mixed Ionic Electronic Conducting (MIEC) perovskites. These complex materials, characterized by their unique redox-active nature and adaptability in stoichiometry, present a promising frontier for efficient solar thermochemical hydrogen production. Firstly, the research enhanced the science by utilizing state-of-the-art computational methodologies to unravel the nuanced chemical potentials of MIEC perovskites. By simulating various off-stoichiometric scenarios and redox conditions, the team was able to predict material behaviors under diverse environmental conditions, a feat unachievable through conventional experimental methodologies alone. This approach not only fast-tracks the material screening process, significantly reducing the time from laboratory re-search to practical application, but also uncovers trends and correlations that are pivotal for future materials innovation. Regarding technical effectiveness, the project stands out in its economic feasibility. Traditional methods of materials discovery are often marred by high costs and extensive timeframes, owing to the iterative nature of experimental processes. However, by employing theoretical computations and validating these findings with targeted experiments, the project introduced a cost-effective paradigm for materials discovery and the first ever prediction, synthesis, and preliminary validation of a material solely from computational and theoretical considerations. This synergy between computation and experimentation expedites the discovery of optimal materials conducive to high-efficiency solar-to-hydrogen conversion processes. Furthermore, the public stands to benefit substantially from this research. The success of MIEC perovskites in solar thermochemical applications heralds a shift towards lower cost and lower electricity input for clean hydrogen production, hence potentially impacting climate and energy resilience. By improving the efficiency of solar-to-hydrogen conversions, the research paves the way for reduced dependency on fossil fuels, addressing the urgent global need for accessible and renewable energy sources. Moreover, the project's advancements contribute to scientific literacy in renewable energy technologies, empowering society through knowledge and spurring future innovations. In essence, this research project demonstrates significant progress in the realm of advanced water splitting through solar thermochemistry. Through its groundbreaking approaches in computational materials science and its implications for real-world applications, it holds the promise of a cleaner, more energy-resilient future.
Some basic technical approaches to producing hydrogen from solar energy are surveyed. Solar energy forms are divided into: (1) direct solar radiation and (2) indirect forms such as wind and ocean thermal gradient. Technical approaches are separated into: (1) direct hydrogen production from the action of sunlight on some substrate, (2) hydrogen production from sunlight via an intermediate form of energy such as heat and electricity, and (3) hydrogen production from indirect solar energy via an intermediate energy form. It is concluded that while hydrogen from solar energy will be expensive by present standards, the depletion of fossil fuels will cause solar hydrogen to emerge as one of the few alternatives to a nuclear-electric or nuclear-electric-hydrogen energy system.
Photoelectrochemical (PEC) water splitting, which utilizes sunlight and water to produce hydrogen fuel, is potentially one of the most sustainable routes to clean energy. One challenge to success is that, to date, similar materials and devices measured in different labs or by different operators lead to quantitatively different results, due to the lack of accepted standard operating procedures and established protocols for PEC efficiency testing. With the aim of disseminating good practices within the PEC community, we provide a vetted protocol that describes how to prepare integrated components and accurately measure their solar-to-hydrogen (STH) efficiency (η STH ). This protocol provides details on electrode fabrication, η STH test device assembly, light source calibration, hydrogen evolution measurement, and initial material qualification by photocurrent measurements under monochromatic and broadband illumination. Common pitfalls in translating experimental results from any lab to an accurate STH efficiency under an AM1.5G reference spectrum are discussed. A III–V tandem photocathode is used to exemplify the process, though with small modifications, the protocol can be applied to photoanodes as well. Dissemination of PEC best practices will help those approaching the field and provide guidance for comparing the results obtained at different lab sites by different groups.
Non-stoichiometric perovskite oxides have been studied as a new family of redox oxides for solar thermochemical hydrogen (STCH) production owing to their favourable thermodynamic properties. However, conventional perovskite oxides suffer from limited phase stability and kinetic properties, and poor cyclability. Here, we report a strategy of introducing A-site multi-principal-component mixing to develop a high-entropy perovskite oxide, (La 1/6 Pr 1/6 Nd 1/6 Gd 1/6 Sr 1/6 Ba 1/6 )MnO 3 (LPNGSB_Mn), which shows desirable thermodynamic and kinetics properties as well as excellent phase stability and cycling durability. LPNGSB_Mn exhibits enhanced hydrogen production (~77.5 mmol mol oxide -1 ) compared to (La 2/3 Sr 1/3 )MnO 3 (~53.5 mmol mol oxide -1 ) in a short 1 hour redox duration and high STCH and phase stability for 50 cycles. LPNGSB_Mn possesses a moderate enthalpy of reduction (252.51–296.32 kJ (mol O) -1 ), a high entropy of reduction (126.95–168.85 J (mol O) -1 K -1 ), and fast surface oxygen exchange kinetics. All A-site cations do not show observable valence changes during the reduction and oxidation processes. In conclusion, this research preliminarily explores the use of one A-site high-entropy perovskite oxide for STCH.
Sustainble hydrogen production for use as a renewable combustible fuel and clean chemical feedstock is an important objective as the world moves towards a renewable energy future. High temperature steam electrolysis is a promising hydrogen production technology due to its reduced electric input that is offset by heat input into steam generation and steam superheating. An option to provide this heat is to use concentrating solar thermal technology that can sustainably provide heat input while renewable electricity is used for the electrolysis reaction. In this work, a solar-to-hydrogen high temperature steam electrolysis plant is designed and dynamically modeled, showing continuous hydrogen production by utilizing supplemental heating and efficient recuperative heating from the electrolysis product streams. Through this design, over 90% of the required heat input for the process can by met by a combination of solar and recuperative heat. Additionally, the plant can flexibility operate by ramping down hydrogen production and through flexible heat integration, which intelligently integrates solar heat based on solar conditions. Smooth operation with flexible hydrogen production is demonstrated which decreases electrical input during on-peak grid times and also decreases the total supplemental heat load over the course of a day from 26.1% to 24.5%. In addition, by using flexible heat integration, the plant can increase its solar heat usage by 4.1% relative to a base case. Both options for flexibility show efficient use of solar thermal energy to sustainably and continuously produce hydrogen.
Flux and energy spectrum of solar hydrogen, helium and heavy nuclei is measured during three rocket firings, using nuclear emulsions techniques
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Solar-powered photochemical water splitting using suspensions of photocatalyst nanoparticles is an attractive route for economical production of green hydrogen. SrTiO 3 -based photocatalysts have been intensely investigated due to their stability and recently demonstrated near-100% external quantum yield (EQY) for water splitting using wavelengths below 360 nm. To extend the optical absorption into the visible, SrTiO 3 nanoparticles have been doped with various transition metals. Here, in this work, we demonstrate that doping SrTiO 3 nanoparticles with 1% Rh introduces midgap acceptor states which reduce the free electron concentration by 5 orders of magnitude, dramatically reducing built-in potentials which could otherwise separate electron–hole (e–h) pairs. Rhodium states also function as recombination centers, reducing the photocarrier lifetime by nearly 2 orders of magnitude and the maximum achievable EQY to 10%. Furthermore, the absence of built-in electric fields within Rh-doped SrTiO 3 nanoparticles suggests that modest e–h separation can be achieved by exploiting a difference in mobility between electrons and holes.
Interstellar hydrogen ionized primarily by the solar wind has been detected by the Solar Wind Ion Composition Spectrometer instrument on the Ulysses spacecraft at a distance of 4.8 AUs from the sun. This 'pick-up' hydrogen is identified by its distinct velocity distribution function, which drops abruptly at twice the local solar wind speed. From the measured fluxes of pick-up protons and singly charged helium, the number densities of neutral hydrogen and helium in the distant regions of the solar system are estimated to be 0.077 +/- 0.015 and 0.013 +/- 0.003 per cu cm, respectively.
Micrometeoroid impacts, solar wind plasma interactions, and regolith gardening drive the complicated and nuanced mechanism of space weathering (or optical maturation); a process by which a material’s optical properties are changed as a result of chemical and physical alterations at the surface of grains on airless bodies. Reddened slopes, attenuated absorption bands, and an overall reduction in albedo in the visible and near-IR wavelength ranges are primarily the result of native iron nanoparticle (npFe0) production within glassy rims that form from sputtering and vaporization. The sizes and abundance of these particles provide information about the relative surface exposure age of a particular grain. In addition, many studies have indicated that composition greatly affects the rate at which optical maturation occurs. Despite our understanding of how npFe0 affects optical signatures, the relative roles of micrometeoroid bombardment and solar wind interactions remains undetermined. To simulate the early effects of weathering by the solar wind and to determine thresholds for optical change with respect to a given mineral phase, we irradiated a fine-grained lunar basalt with 1 keV H+ to a fluence of 6.4 x 1016 H+ per sq.cm. Surface alterations within four phases have been evaluated using transmission electron microscopy (TEM). We found that for a given fluence of H+, the extent of damage acquired by each grain was dependent on its composition. No npFe(0) was produced in any of the phases evaluated in this study. These results are consistent with many previous studies conducted using ions of similar energy, but they also provide valuable information about the onset of space weathering and the role of the solar wind during the early stages of optical maturation.
Primordial hydrogen and helium concentration in Pesyanoe meteorite measured by gas chromatography, indicating solar wind injection source