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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗
DOE OSTI2020

Expanding the Field of Climate Finance

Over the past twenty-one years, the Financial Innovations Roundtable (FIR), located at the Carsey School of Public Policy at the University of New Hampshire, has worked to address problems related to access to capital for low- and moderate-income consumers and communities. Since 2014, the event has been co-hosted by the Federal Reserve Board. The FIR works with a range of financial institutions, government agencies, foundations, and trade associations to access their expertise for problem-solving discussions. The 2020 FIR focused on the expanding field of climate finance and was co-hosted by the Federal Reserve Bank of San Francisco and The Climate Safe Lending Network. The event was originally slated to be in-person in San Francisco in May 2020 but was postponed due to the pandemic and shifted to an online event hosted November 16‒17, 2020. A significant amount has happened in 2020 on climate finance, racial justice, the economy, and COVID-19. The shocks and stresses of climate change are creating risks in low- and moderate-income communities as well as in the financial sector broadly. The 2020 FIR offered an opportunity to discuss the challenges and opportunities banks and Community Development Financial Institutions (CDFIs) face as they address these risks and how these institutions can help increase individual, institutional, and community-wide resilience. The program explored new and modified products that address climate risk in communities and how those products can be scaled. Conversations focused around: • The progress that has been made in the climate finance field and the challenges that lie ahead for financial institutions’ climate impact and climate-related risk. • Promising opportunities to decarbonize investments and finance low-carbon technology and infrastructure. • How lenders, insurers, housing organizations, and the public sector can work together to reduce housing instability due to climate-related factors and increase the climate-resilience of homes and neighborhoods. • Solutions to help communities address a wide range of related issues, including home weatherization and disaster preparation, home insurance loss, and climate gentrification and displacement. • Discussing lessons learned from other sectors such as renewable energy in order to design both people-based and place-based finance solutions that promote racial and economic inclusion. 1 • The need for all financial institutions to acknowledge that climate risks and racial inequity are systemic risks affecting their bottom line. • The role that bank regulators can play in promoting collaboration across the financial sector and in leading by example with regard to climate finance. • Mapping out concrete action-item initiatives including policy and industry pathways to climate safe lending as well as building a financing platform to provide clean energy to low-income communities. • More broadly, in order to systemically address climate risks, we will need to work together as a range of stakeholders across sectors and collaborate on shared goals and projects.

14 SOLAR ENERGY↗
DOE OSTI2026

Hydrogenolysis Versus Hydrocracking for Polyolefin Upcycling

Global plastic production has reached 413.8 million metric tons in 2024 and is forecasted to surpass 1.2 billion metric tons by 2050. Polyolefins, mainly polyethylene (PE) and polypropylene (PP), dominate single-use packaging and account for approximately 55% of global plastic waste. The chemical inertness that makes these materials desirable for commercial applications also renders them persistent in the environment. Current recycling technologies have proven to be insufficient to divert plastic waste from landfills or environmental loss due to technical limitations and poor economic incentives. Conventional mechanical recycling is a form of downcycling, in which the polymer remelting process results in products with inferior material properties and reduced market value. Pyrolysis, a thermochemical route used for the chemical recycling of plastic wastes into refinery feedstock, requires severe conditions, typically 400–600 °C in an oxygen-free environment. The high temperature drives up energy costs and produces a wide range of poorly defined products, including undesirable light gases and heavy tars that pose challenges for downstream processing. As an alternative, catalytic chemical recycling offers a promising route for converting waste polyolefins back into value-added hydrocarbons—such as fuels, lubricant base oils, and other chemical feedstocks—at temperatures typically below 300 °C. This opinion article focuses on two dominant pathways in heterogeneous catalysis that are used to cleave the C–C bonds of polyolefins: hydrogenolysis and hydrocracking. Both catalytic pathways have the potential to selectively convert polyolefin waste into valuable fuels and chemical feedstocks under mild conditions. Notably, while hydrocracking primarily yields branched hydrocarbon products, hydrogenolysis predominantly produces linear hydrocarbons. Here, we compare the mechanisms and catalyst designs for hydrocracking and hydrogenolysis, analyze critical technical challenges from catalyst stability to process engineering, and provide an outlook on how these complementary pathways can be used to repurpose plastic waste into valuable products.

Zhang, Ruoxi [Iowa State Univ., Ames, IA (United S↗
DOE OSTI2023

Novel Calibration Approach for Monitoring Aerosol Hydrogen Isotopes Using Laser-Induced Breakdown Spectroscopy for Molten Salt Reactor Off-Gas Streams

Online monitoring is a key challenge for the continued development of molten salt reactor (MSR) technology. Laser-induced breakdown spectroscopy (LIBS) has previously been demonstrated to be a viable tool for monitoring aerosolized species and noble gases in real time, but the ability to discern varying isotopes in these streams has not yet been investigated for MSR applications. Tritium will form in MSRs from ternary fission and from (n,α)-reactions occurring in lithium-containing salts. This study compares three spectrometers of varying resolutions and types for measuring hydrogen isotope shifts in LIBS spectra of wetted filter paper. For each spectrometer, multivariate models were built (i.e., principal component regression, partial least squares regression, and multivariate curve resolution) to quantify the isotope ratio. The top models were then modified and corrected to apply the models to aerosol samples with varying isotope ratios. This novel calibration strategy offers an 82% reduction in volume of the calibration samples needed and is a more viable pathway for calibrating deployable LIBS systems. Lastly, this calibration model was compared with an all-aerosol trained model for monitoring hydrogen isotopes during a real-time test where the protium/deuterium ratio, along with representative salt species (i.e., lithium, sodium, and potassium) were adjusted dynamically. Results of this test validated the predictive capabilities of the transferred model and highlighted the capabilities of LIBS for real-time monitoring of MSR effluent streams.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Collective neural network behavior in a dynamically driven disordered system of superconducting loops

Collective properties of complex systems composed of many interacting components such as neurons in our brain can be modeled by artificial networks based on disordered systems. We show that a disordered neural network of superconducting loops with Josephson junctions can exhibit computational properties like categorization and associative memory in the time evolution of its state in response to information from external excitations. Superconducting loops can trap multiples of fluxons in many discrete memory configurations defined by the local free energy minima in the configuration space of all possible states. A memory state can be updated by exciting the Josephson junctions to fire or allow the movement of fluxons through the network as the current through them surpasses their critical current thresholds. Simulations performed with a lumped element circuit model of a 4-loop network show that information written through excitations is translated into stable states of trapped flux and their time evolution. Experimental implementation on a high-Tc superconductor YBCO-based 4-loop network shows dynamically stable flux flow in each pathway characterized by the correlations between junction firing statistics. Neural network behavior is observed as energy barriers separating state categories in simulations in response to multiple excitations, and experimentally as junction responses characterizing different flux flow patterns in the network. The state categories that produce these patterns have different temporal stabilities relative to each other and the excitations. This provides strong evidence for time-dependent (short-to-long-term) memories, that are dependent on the geometrical and junction parameters of the loops, as described with a network model.

Josephson junctions↗
DOE OSTI2020

Isolating p- and n-Doped Fingers With Intrinsic Poly-Si in Passivated Interdigitated Back Contact Silicon Solar Cells

Polycrystalline silicon on silicon oxide (poly-Si/SiO x ) passivating contacts enable ultra high efficiency interdigitated back contact silicon solar cells. To prevent shunt between n- and p-type doped fingers, an insulating region is required between them. We evaluate the use of intrinsic poly Si for this isolation region. Interdigitated fingers were formed by plasma deposition of doped hydrogenated amorphous silicon through mechanically aligned shadow masks, on top of a full-area intrinsic amorphous silicon layer. High temperature annealing then crystallized the a-Si:H to poly Si and drove in the dopants. Two mechanisms were identified which cause contamination of the intrinsic poly Si gap during processing. During deposition of doped fingers, we show using secondary ion mass spectrometry and conductivity measurements that the intrinsic gap becomes contaminated by doped a-Si:H tails several nanometers thick to concentrations of ~10 20 cm -3 . Another source of contamination occurs during high-temperature annealing, where dopants desorb from doped regions and readsorb onto intrinsic a Si:H. Both pathways reduce the resistivity of the intrinsic gap from ~10 5 Ω·cm to ~10 -1 Ω·cm. We show that plasma etching of the a-Si:H surface before crystallizing with a capping layer can eliminate the contamination of the intrinsic poly-Si, maintaining a resistivity of ~10 5 Ω·cm. Lastly, this demonstrates masked plasma deposition as a dopant patterning method for Si solar cells.

14 SOLAR ENERGY↗
NASA NTRS2014

Firing Room Remote Application Software Development

The Engineering and Technology Directorate (NE) at National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC) is designing a new command and control system for the checkout and launch of Space Launch System (SLS) and future rockets. The purposes of the semester long internship as a remote application software developer include the design, development, integration, and verification of the software and hardware in the firing rooms, in particular with the Mobile Launcher (ML) Launch Accessories subsystem. In addition, a Conversion Fusion project was created to show specific approved checkout and launch engineering data for public-friendly display purposes.

Pathways↗
DOE OSTI2022

Formation of 6H-Ba 3 Ce 0.75 Mn 2.25 O 9 during Thermochemical Reduction of 12R-Ba 4 CeMn 3 O 12 : Identification of a Polytype in the Ba(Ce,Mn)O 3 Family

The resurgence of interest in a hydrogen economy and the development of hydrogen-related technologies has initiated numerous research and development efforts aimed at making the generation, storage, and transportation of hydrogen more efficient and affordable. Solar thermochemical hydrogen production (STCH) is a process that potentially exhibits numerous benefits such as high reaction efficiencies, tunable thermodynamics, and continued performance over extended cycling. Although CeO 2 has been the de facto standard STCH material for many years, more recently 12R-Ba 4 CeMn 3 O 12 (BCM) has demonstrated enhanced hydrogen production at intermediate H 2 /H 2 O conditions compared to CeO 2 , making it a contender for large-scale hydrogen production. However, the thermo-reduction stability of 12R-BCM dictates the oxygen partial pressure (pO 2 ) and temperature conditions optimal for cycling. In this study, we identify the formation of a 6H-BCM polytype at high temperature and reducing conditions, experimentally and computationally, as a mechanism and pathway for 12R-BCM decomposition. 12R-BCM was synthesized with high purity and then controllably reduced using thermogravimetric analysis (TGA). Synchrotron X-ray diffraction (XRD) data is used to identify the formation of a 6H-Ba 3 Ce 0.75 Mn 2.25 O 9 (6H-BCM) polytype that is formed at 1350 degrees C under strongly reducing pO 2 . Density functional theory (DFT) total energy and defect calculations show a window of thermodynamic stability for the 6H-polytype consistent with the XRD results. These data provide the first evidence of the 6H-BCM polytype and could provide a mechanistic explanation for the superior water-splitting behaviors of 12R-BCM.

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

Pressurized in situ X-ray diffraction insights into super/subcritical carbonation reaction pathways of steelmaking slags and constituent silicate minerals

This study explores mineral carbonation of industrial stainless steelmaking slags and relevant synthetic constituent minerals via in situ pressurized X-ray diffraction, to clarify carbonation reaction pathways and efficiency for carbon storage and waste valorization. The primary mineral phases of Argon Oxygen Decarburization (AOD) and Continuous Casting (CC) slags, namely, åkermanite, bredigite, cuspidine, merwinite, and β- and γ-C 2 S, were reacted in a custom-built beryllium-capped XRD reactor filled with either water-saturated (wet) subcritical CO 2 (g), or wet supercritical CO 2(SC) , in a series of carbonation experiments. Formation of calcite and aragonite was observed for most Ca-bearing minerals, transient precipitation of metastable vaterite was observed, while carbonation of AOD and CC slags in CO 2(SC) resulted in hydrated crystalline calcium carbonates and indirect evidence of amorphous carbonate. Overall, results obtained suggest that low-pressure subcritical carbonation routes are attractive for standalone slag carbonation processes, while high-pressure supercritical carbonation routes are amiable to symbiotic integration with CO 2(SC) -generating green technologies.

42 ENGINEERING↗
DOE OSTI2025

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Knocking out the carboxyltransferase interactor 1 (CTI1) in Chlamydomonas boosted oil content by fivefold without affecting cell growth

Summary The first step in chloroplast de novo fatty acid synthesis is catalysed by acetyl‐CoA carboxylase (ACCase). As the rate‐limiting step for this pathway, ACCase is subject to both positive and negative regulation. In this study, we identify a Chlamydomonas homologue of the plant carboxyltransferase interactor 1 (CrCTI1) and show that this protein interacts with the Chlamydomonas α‐carboxyltransferase (Crα‐CT) subunit of the ACCase by yeast two‐hybrid protein–protein interaction assay. Three independent CRISPR‐Cas9 mediated knockout mutants for CrCTI1 each produced an ‘enhanced oil’ phenotype, accumulating 25% more total fatty acids and storing up to fivefold more triacylglycerols (TAGs) in lipid droplets. The TAG phenotype of the crcti1 mutants was not influenced by light but was affected by trophic growth conditions. By growing cells under heterotrophic conditions, we observed a crucial function of CrCTI1 in balancing lipid accumulation and cell growth. Mutating a previously mapped in vivo phosphorylation site (CrCTI1 Ser108 to either Ala or to Asp), did not affect the interaction with Crα‐CT. However, mutating all six predicted phosphorylation sites within Crα‐CT to create a phosphomimetic mutant reduced this pairwise interaction significantly. Comparative proteomic analyses of the crcti1 mutants and WT suggested a role for CrCTI1 in regulating carbon flux by coordinating carbon metabolism, antioxidant and fatty acid β‐oxidation pathways, to enable cells to adapt to carbon availability. Taken together, this study identifies CrCTI1 as a negative regulator of fatty acid synthesis in algae and provides a new molecular brick for the genetic engineering of microalgae for biotechnology purposes.

Li, Zhongze [Aix‐Marseille Université, CEA, CNRS, ↗
NASA NTRS2015

Firing Room Remote Application Software Development

The Engineering and Technology Directorate (NE) at National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC) is designing a new command and control system for the checkout and launch of Space Launch System (SLS) and future rockets. The purposes of the semester long internship as a remote application software developer include the design, development, integration, and verification of the software and hardware in the firing rooms, in particular with the Mobile Launcher (ML) Launch Accessories (LACC) subsystem. In addition, a software test verification procedure document was created to verify and checkout LACC software for Launch Equipment Test Facility (LETF) testing.

Pathways↗
DOE OSTI2026

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗
DOE OSTI2021

H 2 O-assisted O 2 reduction by H 2 on Pt and PtAu bimetallic nanoparticles: Influences of composition and reactant coverages on kinetic regimes, rates, and selectivities

Hydrogen peroxide (H 2 O 2 ) can replace hazardous oxidants in industrial processes but is currently too expensive for many such applications. While direct synthesis of H 2 O 2 (H 2 + O 2 → H 2 O 2 ) may reduce costs in comparison to incumbent technology, current catalysts lack the requisite stability and selectivity. Here, we examine the direct synthesis of H 2 O 2 on bimetallic Pt 1 Au x (0 ≤ x ≤ 230) and Pt catalysts at steady-state in pure water and relate kinetic parameters for H 2 O 2 and H 2 O formation to possible active site structures informed by complementary characterization methods. X-ray photoelectron spectra show significant Pt surface enrichment compared to the bulk composition. Analysis of infrared spectra of mixed monolayers of 12 CO* and 13 CO* indicate that Pt and Au form substitutional surface alloys. The Pt 1 Au x nanoparticles with the greatest mole fractions of Au predominantly expose Pt monomers (i.e., isolated Pt atoms), yet Pt atoms exposed upon all these nanoparticles possess electronic structures distinct from bulk Pt. Despite these differences, rate measurements are consistent with product formation through proton-electron transfer pathways for all Pt 1 Au x catalysts. In situ XAS indicate that Pt remains metallic during H 2 O 2 synthesis. Under the most oxidizing conditions, selectivities toward H 2 O 2 increase strongly with the Au to Pt ratio from 2% for monometallic Pt to 85% for Pt 1 Au 170 . However, selectivities are similar among all catalysts within reducing conditions. Comparisons of apparent activation enthalpies for the formation of H 2 O 2 and H 2 O across these catalysts and the range of conditions suggest that Pt monomers within Au provide the greatest selectivities for H 2 O 2 formation, because these active sites present high barriers for O-O bond rupture. Further, selectivities decrease with increasing ratios of H 2 to O 2 pressures, because Pt atoms aggregate and form oligomers that readily dissociate dioxygen intermediates. The combined use of spectroscopy, kinetics, and concepts employed in reaching these conclusions take inspiration from the legacy of Prof. Michel Boudart, and specifically his elegant methods for interrogating bimetallic catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Densification, microstructure, and mechanical properties of Mo–30W alloys fabricated from conditioned powders

Refractory alloys, such as molybdenum-based systems, are attracting growing interest for applications in extreme environments, such as in the nuclear and aerospace industries. Recent advances in sintering technologies, coupled with mechanical alloying, have enabled the tailored design of these alloys by leveraging powder characteristics to control final microstructures and mechanical properties. In this study, Mo-30W alloys were fabricated using electric field-assisted sintering (EFAS) from ball-milled powders with and without hydrogen treatment to investigate the influence of surface oxides on material properties and sintering behavior. The results revealed that samples processed from as-ball-milled powder contained a high density of oxides within the microstructure, whereas oxide presence was significantly reduced in samples fabricated from hydrogen-treated powders. Interestingly, the two powder types led to opposite trends in grain size distribution: samples from untreated powders exhibited grain refinement from sample periphery to the center, while samples from hydrogen-treated powders showed grain coarsening toward the center. This behavior is attributed to temperature gradients present during sintering due to electrical percolation pathway differences during Joule heating. The powder surface oxides may have influenced the temperature distribution and grain evolution. Microhardness profiles measured along both axial and thickness directions were consistent with the grain size distribution. Furthermore, oxide films on powder surfaces have delayed densification by hindering particle necking and atomic diffusion during sintering.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Uncertainty quantification and optimization of precipitating hydrometeor parameters for winter precipitation in a cloud microphysics scheme

The precipitating hydrometeor parameters used in cloud microphysics schemes carry inherent uncertainties. The quantification of these uncertainties, together with parameter optimization, can significantly improve precipitation forecasts. This study investigates the effects of 13 parameters in the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme, which define the hydrometeor characteristics such as fall velocity–diameter and mass–diameter relationships, as well as the shape parameter of the drop size distribution for precipitating particles such as rain, snow, and graupel on simulated winter precipitation. A comparison between the model's pre-defined parameters and observations from the International Collaborative Experiments for the PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018) field campaign reveals that the fall velocity–diameter relationship for rain, the mass–diameter relationships for snow and graupel, and the shape parameters for all precipitating particles in the WDM6 scheme deviate from the median values observed by the two-dimensional video disdrometer (2DVD). To quantify parameter sensitivities, a perturbed parameter ensemble (PPE) of 256 simulations was conducted within parameter ranges constrained by 2DVD observations for three winter precipitation cases. Bayesian optimization was then applied to identify parameter sets that minimized the root mean square error (RMSE) for each case, achieving reductions of up to 30.2 %. These results demonstrate that ensemble-based uncertainty quantification and parameter optimization can help identify key parameters and provide a pathway to improving precipitation simulation performance. In addition, measurement sites can be strategically selected based on regions that show high sensitivity to variations in hydrometeor characteristic parameters.

Bayesian optimization↗
DOE OSTI2025

Metabolic interactions underpinning high methane fluxes across terrestrial freshwater wetlands

Current estimates of wetland contributions to the global methane budget carry high uncertainty, particularly in accurately predicting emissions from high methane-emitting wetlands. Microorganisms drive methane cycling, but little is known about their conservation across wetlands. To address this, we integrate 16S rRNA amplicon datasets, metagenomes, metatranscriptomes, and annual methane flux data across 9 wetlands, creating the Multi-Omics for Understanding Climate Change (MUCC) v2.0.0 database. This resource is used to link microbiome composition to function and methane emissions, focusing on methane-cycling microbes and the networks driving carbon decomposition. We identify eight methane-cycling genera shared across wetlands and show wetland-specific metabolic interactions in marshes, revealing low connections between methanogens and methanotrophs in high-emitting wetlands. Methanoregula emerged as a hub methanogen across networks and is a strong predictor of methane flux. In these wetlands it also displays the functional potential for methylotrophic methanogenesis, highlighting the importance of this pathway in these ecosystems. Collectively, our findings illuminate trends between microbial decomposition networks and methane flux while providing an extensive publicly available database to advance future wetland research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Suppressing CO x in oxidative dehydrogenation of propane with dual-atom catalysts

Oxidative dehydrogenation of propane (ODHP) is a promising route for propylene production, but achieving high selectivity towards propylene while minimizing CO x byproducts remains a significant challenge for conventional metal oxide catalysts. Here we propose a solution to this challenge by employing atomically dispersed dual-atom catalysts (M 1 M' 1 -TiO 2 DACs). Ni 1 Fe 1 -TiO 2 DACs exhibit an ultralow CO x selectivity of 5.2% at a high propane conversion of 46.1% and 520 °C, with stable performance for over 1000 hours. Mechanistic investigations reveal that these catalysts operate via a cooperative Langmuir-Hinshelwood mechanism, distinct from the Mars-van Krevelen mechanism typical of metal oxides. This cooperative pathway facilitates efficient conversion of propane and oxygen into propylene at the dual-atom interface. The superior selectivity arises from facile olefin desorption from the dual-atom sites and suppressed formation of electrophilic oxygen species, which are preferentially adsorbed on Fe 1 sites rather than oxygen vacancies. This work highlights the potential of dual-atom catalysts for highly selective ODHP and provides insights into their unique catalytic mechanism.

02 PETROLEUM↗