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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 361 records · Page 20

Influence of Mo- and Ga-Supported HZSM-5 Co-Catalyst Configuration in Microwave-Assisted Methane and Ethane Dehydroaromatization

Microwave (MW)-assisted dehydroaromatization (DHA) using an Mo-supported HZSM-5 catalyst (Mo/HZSM-5) enhances the value of natural gas resources by converting stranded or underutilized natural gas into value-added chemicals in modular microwave reactor systems. This approach offers the potential to generate economic value. However, natural gas mixtures often contain multiple components, including ethane (C2H6) and propane (C3H8), which complicate the reaction pathways. Ga-supported HZSM-5 (Ga/HZSM-5) catalysts are generally inactive toward CH4 but exhibit higher activity toward C2H6 and C3H8. Therefore, investigating the combination of Mo/HZSM-5 and Ga/HZSM-5 in various catalyst bed configurations is essential. This study explores different co-catalyst bed configurations and CH4/C2H6 feed compositions to determine the most effective way for enhanced natural gas conversion and benzene production.

cocatalyst bed configuration↗

First-Principles Thermodynamic Assessments of Sr-Containing Secondary Phase Formation in La1-xSrxMnO3±δ Perovskites for Solid Oxide Cell Applications

Sr-secondary phase formation is a potentially significant degradation mode threatening solid-oxide cell (SOC) commercial viability. A first-principles thermodynamic study was performed for rhombohedral perovskite (La1-xSrx) MnO3±δ (LSM) to assess its stability against Sr secondary phase formation in SOC applications. In this work, the Sr secondary phase formation reaction free energies were determined by combining ab initio lattice dynamics calculations for the solid phases and an ab initio thermodynamics approach for the gas phases. Furthermore, this approach goes beyond previous thermodynamic modeling studies by integrating first-principles based point-defect equilibria into the analyses. The modeling results indicate an increased tendency to form SrO oxide from LSM upon decreasing the oxygen partial pressure. Additionally, enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with contaminant gas species as a function of temperature and gas pressure.

Defect and phase stability↗

Upcycling Polyethylene Waste Into Hybrid Graphitic Porous Carbon Materials Used in High-Performance Zinc-Ion Hybrid Capacitors

Polyethylene (PE) waste is a challenge to upcycle into useful materials because this plastic tends to decompose into volatile compounds when heated at relatively low temperatures. In this work, we report a chemical process that addresses this challenge by converting mixtures of linear low-density polyethylene (LLDPE), low-density polyethylene (LDPE), and high-density polyethylene (HDPE) waste into a hybrid graphitic porous carbon (HGPC) that can be used as a zinc-ion hybrid capacitor cathode. The process uses a low temperature thermal oxidation pre-treatment step, with assistance of an inert solid additive (KCl) to increase the effective surface area of the PE melt, to functionalize, cross-link, and stabilize the PE waste followed by carbonization and catalytic graphitization steps at higher temperatures with a potassium carbonate (K2CO3) catalyst. The PE waste derived HPGC (PW-HPGC) has a hybrid structure composed of graphene-like carbon nanosheets grown on the surface of carbon particles, high porosity with the Brunauer–Emmett–Teller (BET) specific surface area up to 1,763 m2g-1, and good graphitic degree with average Raman I2D/IG ratios of 0.53. When used as a cathode material for zinc-ion hybrid capacitors, this PW-HGPC exhibits an excellent specific capacity up to 126.7 mAhg-1 at high mass loading of 10 mgcm-2. Moreover, PW-HGPC exhibits remarkable cycling stability with capacity retention of >94% after 10,000 cycles at a current density of 2.0 A g-1.

hybrid graphitic porous carbon↗

Scalable Fabrication of a Fibrous Amine-functionalized Matrix (FAM) Sorbent for Critical Mineral Recovery

We report a novel flat sheet Fibrous Amine-functionalized Matrix (FAM) sorbent platform designed for efficient and selective capture of CM from dilute solutions. The FAM sorbent features crosslinked amine microfilms coated onto/within a glass fiber matrix, providing fast mass transfer and excellent mechanical stability. Systematic batch and flow-through tests with FAM revealed rapid metal uptake kinetics and high capacity for representative species, achieving ~90 mg/g of Gallium, ~100 mg/g of Cobalt, and ~90 mg/g for Neodymium. Moreover, multiple eluents, including mineral acids and complexing agents, enabled highly effective desorption of adsorbed metals, demonstrating the feasibility of regenerating FAM sorbents. Importantly, tests with authentic coal ash leachate demonstrated strong selectivity toward U.S. Department of Energy (DOE)-listed CM and rare earth elements over abundant base cations, confirming the robustness of FAM in realistic complex solutions. The flat sheet geometry was amenable to scaling into durable spiral wound modules, highlighting the potential for future regeneration and reuse. This work establishes FAM sorbents as a promising platform for the recovery of CM from wastewaters, advancing both resource sustainability and environmental stewardship.

critical mineral recovery↗

Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions

Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.

artificial intelligence↗

Computational screening of fly ash zeolite sorbents for boric acid removal

In the United States, many impoundments at coal-fired power plants contain elevated contaminants like arsenic, boron, barium, and selenium. Zeolites synthesized from fly ash show promise as sorbents for these contaminants. However, optimizing sorption capacity is challenging due to numerous possible topologies, silicon to aluminum (Si/Al) ratios, and cation types. In this study, molecular simulations are used to design cationic zeolites for boric acid adsorption. Force field models based on quantum mechanical calculations (PBE + D2) for Na-, Ca-, Mn-, and Fe-exchanged chabazite and LTA are presented. The new D2FF force fields reproduce DFT energies with about half the error of UFF. Zeolite performance depends on Si/Al ratio and cation type, with low Si/Al ratio chabazite (CHA) and phillipsite (PHI) zeolite frameworks exchanged with Ca 2+ or Na + /Ca 2+ mixtures showing the highest adsorption. In conclusion, these findings suggest tailored fly ash-derived zeolites could provide effective boron removal from leachate ponds.

CCR impoundment↗

Rate expressions and kinetic parameters for metal ferrites in relation to applications of fossil fuel conversion to hydrogen: Part 1 of 2

Here, the goal of the present work was to provide the necessary reaction emulation information to enable detailed process simulation of a chemical looping H 2 production system from fossil fuels using CaFe 2 O 4 . This specifically pertained to the necessary kinetic data, reaction model development, and model rate parameters required for reaction emulation in both reducing and oxidizing environments. A logical methodology was defined, which included discretization of the reaction network, establishing a core model for reaction emulation that could be adapted based on the system phenomena, and development of a rate parameter regression tool designed around the core model. An extensive array of data sets was acquired by which parametric regressions were performed. The work presented and tabulated a comprehensive set of rate parameters for the reduction and oxidation reactions of CaFe 2 O 4 and descendent phases of Ca 2 Fe 2 O 5 , FeO, Fe 3 O 4 , Fe, and CaO to emulate reaction behavior in a looping-based process environment. This included direct reduction using CH 4 , H 2 , and CO, and direct oxidation reactions with steam, CO 2 and O 2 . Dynamic equilibrium was quantified for reactions that could utilize H 2 O and CO 2 as soft oxidants to re-saturate lattice oxygen in the depleted structure/phases. The kinetics associated with the oxidative mechanisms with the soft oxidants were quantified and compared to those of the reducing counterparts. The analysis provided critical insight to emulate reactions for a process that seeks to use natural gas (NG) or other fossil fuels as a direct reductant for the end goal of H 2 production.

calcium ferrite oxygen carriers↗

Record acceleration of the two-dimensional Ising model using a high-performance wafer-scale engine

The versatility and wide-ranging applicability of the Ising model, originally introduced to study phase transitions in magnetic materials, have made it a cornerstone in statistical physics and a valuable tool for evaluating the performance of emerging computer hardware. Here, we present a novel implementation of the two-dimensional Ising model on Cerebras Wafer-Scale Engine (WSE) – a revolutionary processor that is opening new frontiers in computing. In our deployment of the checkerboard algorithm, we optimized the Ising model to take advantage of the unique WSE architecture. Specifically, we employed a compressed bit representation storing 16 spins on each int16 word, and efficiently distributed the spins over the processing units enabling seamless weak scaling and limiting communications to only immediate neighboring units. Our implementation can handle up to 754 simulations in parallel, achieving an aggregate of over 61.8 trillion flip attempts per second for Ising models with up to 200 million spins. This represents a gain of up to 148 times over previously reported single-devices with a highly optimized implementation on NVIDIA V100 and up to 88 times in productivity compared to NVIDIA H100. Our findings highlight the significant potential of the WSE in scientific computing, particularly in the field of materials modeling.

Ising model↗

Geologic hydrogen: From natural occurrences to anthropogenic generation – A review of fundamentals, potential, challenges and prospects

Growing demand for hydrogen is exposing the environmental and economic limits of reforming-based and carbon-managed supply chains, while the scale-up of electrolytic capacity remains capital-constrained. Geologic hydrogen, defined as molecular H₂ generated and stored within the Earth's crust offers a complementary, potentially lower-cost resource, yet exploration is still ad hoc. This review (1) revisits a global inventory of confirmed hydrogen seeps and subsurface occurrences; (2) analyzes the controlling reactions, migration pathways, and trapping conditions governing these occurrences; (3) proposes a process-based geologic hydrogen system concept analogous to, yet distinct from, the petroleum system; and (4) evaluates potential geologic hydrogen systems within the United States as a representative case study. Here, we contrast natural systems powered by serpentinization, mantle degassing or radiolysis with anthropogenic systems that stimulate the same reactions or convert in-situ hydrocarbons. Stable hydrogen accumulations require generation rates that outpace combined physical, chemical and microbial losses; the Bourakébougou field (Mali) exemplifies a self-recharging, free-gas reservoir sustained by meteoric-water serpentinization beneath an efficient caprock. Prospective geologic hydrogen resources are likely to occur in regions where iron-rich lithologies, deep-seated faults, and low-permeability sealing formations coexist. Applying this principle, we highlight three promising hydrogen play types in U.S. geological terrains: ophiolite belts (Appalachian and Californian regions), the Midcontinent Rift and the Lake Superior banded‑iron formations. Multiphysics numerical models and positive-unlabeled machine-learning workflows help to accelerate play screening and de-risk future production; yet, reaction kinetics, stimulation strategies, and full techno-economic and life-cycle assessments remain pivotal knowledge gaps.

Anthropogenic hydrogen generation↗

Multi-scale dynamic modeling and validation of radial flow fixed bed contactors for post-combustion CO 2 capture using bench scale and pilot plant data

Here, in this work, a multi-scale model of a radial flow fixed bed contactor packed with a carbon sorbent is developed and validated with laboratory-scale and pilot plant scale dynamic data. For the lab scale system, the model results were compared with low, medium and high gas and sweep flowrates, yielding root mean square error (RMSE) of 0.80, 0.63, 0.96 CO 2 mol%, respectively, for the outlet CO 2 concentration profile considering the entire A-D cycle. For the bed outer temperature profile, maximum RMSE was found to be 5.5 °C considering all flowrates and entire A-D cycles. An experimental campaign was developed and applied to a pilot plant at Technology Center Mongstad (TCM), Norway. Approaches were developed for pre-processing of data including consideration of the effect of gas mixing, measurement delay, and determination of cyclic steady-state conditions. Considering profiles during A-D cycles for all test runs, it was found that the maximum RMSE for pressure drop, temperature for the outer section of the bed, temperature for the middle section of the bed, and outlet CO 2 concentration profile remained less than 1.5 mbar, 3.5 °C, 2.8 °C, and 1.3 CO 2 mol%, respectively. The validated model was used to perform sensitivity studies on several key design operating variables for the adsorption-desorption cycle. It was found that the flow rate and concentration of flue gas have dominant nonlinear effects on the breakthrough time while the desorption time was strongly affected by the sweep gas flowrate for the specific sorbent being evaluated in this study.

20 FOSSIL-FUELED POWER PLANTS↗

A comparative assessment of the economic viability of nuclear-integrated direct air capture systems

Direct air capture (DAC) systems require heat and electricity to operate, which can be supplied by nuclear power plants (NPPs). In this study, the performance and cost of various conceptual nuclear-DAC systems are assessed, and their performance is compared with several non-nuclear options. Three nuclear-DAC systems are considered: (1) a liquid solvent direct air capture (L-DAC) system with heat supplied from natural gas (NG) and electricity supplied by an NPP, (2) an electrified L-DAC system, fully powered by electricity from an NPP, and (3) a solid sorbent direct air capture (S-DAC) system utilizing both heat and electricity generated by an NPP. Two nuclear technologies are considered: a pressurized water reactor and a high-temperature gas-cooled reactor. Under the medium conservatism scenario, the levelized cost of direct air capture (LCOD) for these systems range from $\$$310/tCO 2 to $\$$525/tCO 2 with the L-DAC system having an NG heat supply at the lower end of the range, and the electrified L-DAC system and the S-DAC system at the higher end of the range. Coupling with nuclear energy led to a 21 % reduction in LCOD for the L-DAC system with NG heat supply and a 29 % reduction for the S-DAC system when compared to fully NG-powered options. When powering the DAC system with grid electricity, the LCOD is highly dependent on the assumed electricity price and carbon intensity. The nuclear option is the cheaper choice when the price of low-carbon grid electricity exceeds $\$$95/MWh and $\$$45/MWh for the L-DAC and S-DAC systems, respectively.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Perovskite design principles for efficient microwave dry reforming with noble metal free catalysts

Microwave absorbing catalysts have the potential to electrify high-temperature thermal reactions such as the dry reforming of methane process (DRM: CO 2 + CH 4 → 2CO + 2 H 2 ). However, microwave catalysts present unique challenges due to their dual requirements of maintaining microwave absorption in both oxidative and reductive environments and stability across a range of temperatures in inherently non-isothermal reactors. Here, catalyst candidates from the La 0.8 Sr 0.2 CoO 3 -La 0.8 Sr 0.2 NiO 3 -La 0.8 Sr 0.2 MnO 3 perovskite systems were screened (28 total) to identify promising microwave catalysts free of noble metals for dry reforming methane. The best performing candidates met two main criteria. First, they occurred at crystal phase boundaries, giving rise to a pseudocubic perovskite structure. The combined use of Goldschmidt tolerance factor and octahedral tolerance factors appeared to be suitable for predicting pseudocubic perovskites. Second, they provided a balance of reducible metal sites with an irreducible metal oxide support. The best performing catalyst was found to exsolve Ni-Co alloy particles as active sites for the DRM reaction which offered superior resistance to coking for excellent reforming efficiency and stability.

42 ENGINEERING↗

Recent Advances and Future Perspectives of Low-Concentration CO 2 Enrichment and Emerging Applications

Low-concentration carbon dioxide (LCCO 2 ) streams, ranging from ambient air to industrial flue gas, represent a significant yet underutilized carbon resource. This review examines recent advances in technologies for enriching LCCO 2 and enabling its integration into a wide range of applications. It covers emerging materials and processes for CO 2 capture, including immobilized amines, metal oxides, polymers, porous carbons, and zeolites, with a focus on performance metrics, regeneration strategies, and process intensification. Beyond capture, the review explores the direct utilization of LCCO 2 through reactive capture pathways enabled by novel catalysts and processes, as well as nonreactive applications, such as greenhouse cultivation, enhanced weathering, and sustainable agriculture. Additionally, this review highlights the role of LCCO 2 in enhancing critical metal recovery. Finally, the review outlines crucial future research directions necessary to fully realize LCCO 2 enrichment’s potential within circular carbon economies and critical material supply chains, paving the way toward a more energy-innovative and resource-resilient industrial sector. The findings are significant for researchers in academia, industry, and government, as well as the public interested in extending the value of LCCO 2 .

atmospheric chemistry↗

Toward a Better Understanding of Ni Coarsening in Solid Oxide Cells: NiH on Ni (111) Examined Using a Combined Theoretical Approach

The coarsening of the Ni particles in the hydrogen electrode of solid oxide cells (SOCs) is an important degradation mechanism. Here, in this paper, density-functional theory and kinetic Monte Carlo methods are used to explore our recent hypothesis that the surface diffusion of NiH may cause faster Ni coarsening in electrolysis cell mode under an overpotential. Using both methods, the diffusion constant or diffusivity of NiH on Ni (111) is determined as the product of the surface coverage and single-molecule diffusivity for the first time considering all possible diffusion paths. It is then determined versus overpotential at the triple-phase boundary of the hydrogen electrode assuming a typical operating temperature of the SOC. Under a significant overpotential, the diffusivity of NiH is found to be sufficiently large to support the above hypothesis that NiH may promote Ni coarsening. However, based on the adsorption configurations identified, the dissociation and reformation of NiH on Ni (111) could occur. Thus, more work is needed to develop a model of Ni coarsening considering both molecular and dissociated forms of NiH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning-Accelerated First-Principles Molecular Dynamics Explains Anomalous Lattice Thermal Expansion in BaZr 0.78 Y 0.22 O 3-δ

Fuel cells are a vital clean energy technology that converts chemical energy directly into electricity with high efficiency, making them a cornerstone of a sustainable energy future. Herein we investigate the thermal and chemical lattice expansion behavior of hydrated BaZr 0.78 Y 0.22 O 3-δ using machine learning-accelerated ab initio molecular dynamics simulations. Here, our results reproduce the experimentally observed non-monotonic and anomalous temperature dependence of lattice expansion, which we attribute to the competing effects of thermal expansion and dehydration—two mechanisms that influence the lattice expansion in opposite directions. The importance of this work lies in its detailed demonstration of how advanced computational techniques can accurately capture complex environmental effects, providing a valuable framework for modeling similar phenomena in a variety of material systems and applications.

Proton conducting fuel cell↗