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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 19 records

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

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.

first-principles calculations↗

Hydrogen-Steam Separation Using Mechanical Vapor Recompression Cycle

Solar thermochemical hydrogen and fuel production is a promising pathways for producing sustainable fuels and chemicals. One of the main challenges in the development of these systems is their low steam conversion extent, dictated by its restrictive thermodynamics requiring extremely high temperatures and low oxygen partial pressure to obtain conversions over 10 \%. While condensing the unreacted steam is technically simple, the latent heat is thus lost, which can be larger than the producd hydrogen higher heating value. We propose to use a modified mechanical vapor recompression cycle, allowing to recover the latent heat by compressing the steam-hydrogen mixture prior to the condensation process, thus creating a temperature different between the hot exhaust and cold inlet streams. We show that this method can recover over 90 % of the latent heat, thus increasing the viability of solar thermochemical hydrogen production cycles even under limited conversion conditions.

hydrogen technology↗

Solar Thermochemical Redox Cycling Using Ga- and Al-Doped LSM Perovskites for Renewable Hydrogen Production

Solar thermochemical hydrogen production using redox-active metal oxides is a promising pathway for the production of green hydrogen and synthetic fuel precursors. Herein, the perovskite material (La 0.6 Sr 0.4 ) 0.95 Mn 0.8 Ga 0.2 O 3–δ (LSMG6482) is identified as a promising metal oxide for thermochemical water splitting. LSMG6482, along with more-established water splitters ceria and (La 0.6 Sr 0.4 ) 0.95 Mn x Al 1–x O 3–δ (LSMA) perovskites, is experimentally characterized via thermogravimetric (TGA) analysis and high-temperature water splitting in a reactor simulating solar concentrating conditions. TGA analysis demonstrated that LSMG6482 has high and stable oxygen exchange capacity under controlled pO 2 redox cycling, demonstrated by large changes in oxygen nonstoichiometry (δ) relative to ceria. Water splitting experiments using laser heating (T red = 1400 °C, T ox = 1200 °C) resulted in H 2 yields of 165.1 μmol g –1 for the candidate LSMG6482 composition, exceeding that of all benchmark materials tested. Under high conversion oxidation conditions, where H 2 is cointroduced with H 2 O (150 ≤ nH 2 O/nH 2 ≤ 500), H 2 yields were greatest for LSMG6482 and LSMA6482, up to four times that of ceria at the highest nH 2 O/nH 2 conditions. Crystallographic analysis showed that over the course of experimentation, there is some secondary phase growth for all perovskite compositions, except for LSMA6482, but there was no observable degradation in H 2 yields.

08 HYDROGEN↗

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

Benchmarking Advanced Water Splitting Technologies: Best Practices in Materials Characterization

The high-level project goal is to create a comprehensive Best Practices benchmarking framework at the materials, component, device and systems levels for advanced water splitting technologies. All advanced water splitting pathways covered under the HydroGEN Energy Materials Network (EMN) Consortium, which include advanced high and low temperature electrolysis of water, photoelectrochemical (PEC) water splitting and solar thermochemical hydrogen (STCH) need these best practices to advance materials discovery. These practices will also aid the H2@Scale DOE initiative to accomplish their goals of large-scale H2 production.

08 HYDROGEN↗

Technology for Electrically Enhanced Thermochemical Hydrogen (TEETH)

This is the Final Technical Report for the TEETH project. The TEETH concept couples high-temperature solar-thermochemical water splitting (TCWS) with electrochemical H 2 pumping through a proton conducting membrane (PCM) and capitalizes on the benefits of the individual technologies to synergistically providing new benefits. That is, TEETH is a coupled thermochemical/electrochemical process to produce H 2 from steam using solar energy. This approach is thermodynamically equivalent to other hybrid electrolytic processes but is unique in that the equilibrium of the reaction is driven forward by close coupling an electrically driven proton-conducting-membrane to the H 2 -producing reoxidation step. The process uniquely provides and benefits from the necessary H 2 /steam separation and, also unlike other hybrid processes, benefits thermodynamically from the use of readily generated high pressure steam. The concept also satisfies the objectives of previous concepts: 1) decreasing the reduction enthalpy (the reduction temperature), of the working metal-oxide (MO); 2) eliminating the need for a windowed receiver; and 3) widening the scope of material candidates, while also obviating the need for electrical connections to the working MO and avoiding the use of aqueous electrolytes and hydrated redox species (there is no liquid phase), without increasing mechanical complexity.

08 HYDROGEN↗

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗

Scalable Solar Fuels Production in A Reactor Train System by Thermochemical Redox Cycling of Novel Nonstoichiometric Perovskites

Hydrogen production via two-step thermochemical water splitting redox cycles using nonstoichiometric redox-active metal oxides has the potential to dramatically increase fuel production rates. At moderate-to-low water splitting temperatures, surface reaction kinetics co-limit the process. In such cases, stable and high surface area microstructures that allow exploitation of the full thermodynamic potential of the materials are essential as is tight thermal integration of the reactor module. This project’s goals were the development of novel nonstoichiometric perovskite oxides with high stability and favorable thermodynamic and kinetic properties, to optimize their microstructure for maximizing the fuel productivity, and to build a prototype reactor train system (RTS) comprising at least one reactor to meet specific performance targets: (1) capable of an in-house solar thermochemical hydrogen (STCH) productivity ≥ 12 mL g -1 for stable continuous operation ≥ 20 cycles; and (2) demonstration of scalable solar fuels production at practical solar reactor level in an industrial-scale concentrated solar tower (CST) using developed perovskites to achieve a hydrogen production rate ≥ 1 g h -1 .

08 HYDROGEN↗

Hydrogen production from solar energy

Three alternatives for hydrogen production from solar energy have been analyzed on both efficiency and economic grounds. The analysis shows that the alternative using solar energy followed by thermochemical decomposition of water to produce hydrogen is the optimum one. The other schemes considered were the direct conversion of solar energy to electricity by silicon cells and water electrolysis, and the use of solar energy to power a vapor cycle followed by electrical generation and electrolysis. The capital cost of hydrogen via the thermochemical alternative was estimated at $575/kW of hydrogen output or $3.15/million Btu. Although this cost appears high when compared with hydrogen from other primary energy sources or from fossil fuel, environmental and social costs which favor solar energy may prove this scheme feasible in the future.

Eisenstadt, M. M.↗

Solar thermochemical process interface study

The design and analyses of a subsystem of a hydrogen production process are described. The process is based on solar driven thermochemical reactions. The subject subsystem receives sulfuric acid of 60% concentration at 100 C, 1 atm pressure. The acid is further concentrated, vaporized, and decomposed (at a rate of 122 g moles/sec H2SO4) into SO2, O2, and water. The produce stream is cooled to 100 C. Three subsystem options, each being driven by direct solar energy, were designed and analyzed. The results are compared with a prior study case in which solar energy was provided indirectly through a helium loop.

Source record↗

Solar Metal Sulfate-Ammonia Based Thermochemical Water Splitting Cycle for Hydrogen Production

Two classes of hybrid/thermochemical water splitting processes for the production of hydrogen and oxygen have been proposed based on (1) metal sulfate-ammonia cycles (2) metal pyrosulfate-ammonia cycles. Methods and systems for a metal sulfate MSO.sub.4--NH3 cycle for producing H2 and O2 from a closed system including feeding an aqueous (NH3)(4)SO3 solution into a photoctalytic reactor to oxidize the aqueous (NH3)(4)SO3 into aqueous (NH3)(2)SO4 and reduce water to hydrogen, mixing the resulting aqueous (NH3)(2)SO4 with metal oxide (e.g. ZnO) to form a slurry, heating the slurry of aqueous (NH4)(2)SO4 and ZnO(s) in the low temperature reactor to produce a gaseous mixture of NH3 and H2O and solid ZnSO4(s), heating solid ZnSO4 at a high temperature reactor to produce a gaseous mixture of SO2 and O2 and solid product ZnO, mixing the gaseous mixture of SO2 and O2 with an NH3 and H2O stream in an absorber to form aqueous (NH4)(2)SO3 solution and separate O2 for aqueous solution, recycling the resultant solution back to the photoreactor and sending ZnO to mix with aqueous (NH4)(2)SO4 solution to close the water splitting cycle wherein gaseous H2 and O2 are the only products output from the closed ZnSO4--NH3 cycle.

Huang, Cunping↗