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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Resolving dynamic mineral-organic interactions in the rhizosphere by combining in-situ microsensors with plant-soil reactive transport modeling

Associations between minerals and organic matter represent one of the most important carbon storage mechanisms in soils. Plant roots are major sources of soil carbon, and resolving the dynamics and dominance of microbial consumption versus mineral sorption of root-derived carbon is critical to understanding soil carbon storage. Here we integrate in-situ rhizosphere microsensor and plant physiological measurements with a 3-D plant-soil reactive transport model to explore the fate of dissolved organic carbon (DOC) in the rhizosphere, particularly its microbial consumption and interaction with Fe oxide minerals. Over several days, a microdialysis probe sampling pore water at the root-soil interface of growing Vicia faba roots in live soil, revealed clear diel patterns of DOC concentration. Daytime DOC spikes coincided with peaks in leaf-level photosynthesis rates and were accompanied by declining redox potential and dissolved oxygen as well as increasing pH in the rhizosphere. Incorporating microsensor data into our modeling framework showed that the measured rapid loss of DOC after each mid-day spike could not be explained by consumption via aerobic respiration, nor via anaerobic respiration dominated by Fe oxide reduction. Rather, in the model, a large fraction of rhizosphere DOC was rapidly immobilized each day by adsorption to Fe oxides. Further, modeled microbial Fe reduction (fueled by DOC) did not mobilize significant organic carbon from Fe oxides during the day. Instead, the model predicted equilibrium desorption of organic carbon from Fe oxides at night. This new mechanistic modeling framework, which couples aboveground plant physiological measurements with non-destructive high-resolution monitoring of rhizosphere processes, has great potential for exploring the dynamics and balance of the various microbial reactions and mineral interactions controlling carbon transformations and storage in soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Perspectives and progress on wurtzite ferroelectrics: Synthesis, characterization, theory, and device applications

Wurtzite ferroelectrics are an emerging material class that expands the functionality and application space of wide bandgap semiconductors. Promising physical properties of binary wurtzite semiconductors include a large, reorientable spontaneous polarization, direct band gaps that span from the infrared to ultraviolet, large thermal conductivities and acoustic wave velocities, high mobility electron and hole channels, and low optical losses. The ability to reverse the polarization in ternary wurtzite semiconductors at room temperature enables memory and analog type functionality and quasi-phase matching in optical devices and boosts the ecosystem of wurtzite semiconductors, provided the appropriate combination of properties can be achieved for any given application. In this article, advances in the design, synthesis, and characterization of wurtzite ferroelectric materials and devices are discussed. Highlights include: the direct and quantitative observation of polarization reversal of ~135 μC/cm 2 charge in Al 1-x B x N via electron microscopy, Al 1-x B x N ferroelectric domain patterns poled down to 400 nm in width via scanning probe microscopy, and full polarization retention after over 1000 h of 200 °C baking and a 2× enhancement relative to ZnO in the nonlinear optical response of Zn 1-x Mg x O. In conclusion, the main tradeoffs, challenges, and opportunities in thin film deposition, heterostructure design and characterization, and device fabrication are overviewed.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Unstable Invasion of Sedimenting Granular Suspensions

Here we investigate the development of mobility inversion and fingering when a granular suspension is injected radially between horizontal parallel plates of a cell filled with a miscible fluid. While the suspension spreads uniformly when the suspension and the displaced fluid densities are exactly matched, even a small density difference is found to result in a dense granular front which develops fingers with angular spacing that increase with granular volume fraction and decrease with injection rate. We show that the timescale over which the instability develops is given by the volume fraction dependent settling timescale of the grains in the cell. We then show that the mobility inversion and the nonequilibrium Korteweg surface tension due to granular volume fraction gradients determine the number of fingers at the onset of the instability in these miscible suspensions.

02 PETROLEUM↗
DOE OSTI2020

Predicting antimicrobial susceptibility from the bacterial genome: A new paradigm for one health resistance monitoring

The laboratory identification of antibacterial resistance is a cornerstone of infectious disease medicine. In vitro antimicrobial susceptibility testing has long been based on the growth response of organisms in pure culture to a defined concentration of antimicrobial agents. By comparing individual isolates to wild type susceptibility patterns, strains with acquired resistance can be identified. Acquired resistance can also be detected genetically. After many decades of research, the inventory of genes underlying antimicrobial resistance (AMR) is well known for several pathogenic genera including zoonotic enteric organisms such as Salmonella and Campylobacter and continues to grow substantially for others. With the decline in costs for large scale DNA sequencing, it is now practicable to characterize bacteria using whole genome sequencing (WGS), including the carriage of resistance genes in individual microorganisms and those present in complex biological samples. With genomics we can generate comprehensive, detailed information on the bacterium, the mechanisms of antibiotic resistance, clues to its source, and the nature of mobile DNA elements by which resistance spreads. These developments point to a new paradigm for antimicrobial resistance detection and tracking for both clinical and public health purposes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Alkylperoxy radicals are responsible for the formation of oxygenated primary organic aerosol

Organic aerosol (OA) is an air pollutant ubiquitous in urban atmospheres. Urban OA is usually apportioned into primary OA (POA), mostly emitted by mobile sources, and secondary OA (SOA), which forms in the atmosphere due to oxidation of gas-phase precursors from anthropogenic and biogenic sources. By performing coordinated measurements in the particle phase and the gas phase, we show that the alkylperoxy radical chemistry that is responsible for low-temperature ignition also leads to the formation of oxygenated POA (OxyPOA). OxyPOA is distinct from POA emitted during high-temperature ignition and is chemically similar to SOA. We present evidence for the prevalence of OxyPOA in emissions of a spark-ignition engine and a next-generation advanced compression-ignition engine, highlighting the importance of understanding OxyPOA for predicting urban air pollution patterns in current and future atmospheres.

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

Exploring urban typologies using comprehensive analysis of transportation dynamics

Abstract As urban areas continue to expand and develop, categorizing cities into typologies offers a valuable framework for understanding metropolitan dynamics and fostering inter-city collaboration. However, existing typologies related to urban mobility have limitations, failing to consider cities within a single large urban region and often overlooking crucial dimensions such as trip demand and traffic flow. In this paper, we introduce a transportation-focused characterization for cities within a large urban region, specifically the San Francisco Bay Area, California. We incorporate over 40 metrics across five transportation dimensions: trip demand, road network, multi-modal network, traffic flow, and land use. Specifically, for the trip demand dimension, we include metrics capturing residents’ trip characteristics, such as mode share, intra-city trips, and inter-city trips. Additionally, we analyze the purpose of trips entering the city to gain a deeper understanding of incoming trip patterns. In the traffic flow dimension, we examine metrics like vehicle miles traveled, delay, and congestion to assess the traffic conditions on the street network. These, combined with other dimensions, provide a comprehensive view of a city’s transportation dynamics. Using unsupervised machine learning clustering methods, we identified eight distinct typologies for the Bay Area: Live Work Cities; Job and Activity Magnet Cities; Anchor Cities; Multi-modal Cities; Hyper-connected Cities; Low-density Residential Cities; Medium-density Residential Cities; and Mixed-use Residential Cities. Our findings show that many clusters are strongly influenced by trip demand and traffic flow metrics. Finally, we examine the practicality of this typology and its potential to guide collaborative transportation management strategies. The typologies provide a foundation for dialogue among Bay Area cities, focusing on evaluating shared characteristics and leveraging successes or challenges to develop unified strategies for transportation management.

Kuncheria, Anu↗
DOE OSTI2022

Ion Transport in 2D Nanostructured $\pi$-Conjugated Thieno[3,2- b ]thiophene-Based Liquid Crystal

Leveraging the self-assembling behavior of liquid crystals designed for controlling ion transport is of both fundamental and technological significance. Here, we have designed and prepared a liquid crystal that contains (2,5-bis(5-(2,5,8,11-tetraoxatridecan-13-yl)thiophen-2yl)thieno[3,2-b]thiophene (BTTT) as mesogenic core and conjugated segment and symmetric tetra(ethylene oxide) (EO4) as polar side chains for ionic conducting regions. Driven by the crystallization of the BTTT cores, BTTT/dEO4 exhibits well-ordered smectic phases below 71.5 °C as confirmed by differential scanning calorimetry, polarized optical microscope, temperature dependent wide-angle X-ray scattering and grazing incidence wide-angle X-ray scattering (GIWAXS). We adopted a combination of experimental GIWAXS and molecular dynamics (MD) simulations to better understand the molecular packing of BTTT/dEO4 films, particularly when loaded with the ion conducting salt, lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). Ionic conduction of BTTT/dEO4 is realized by the addition of LiTFSI, with the material able to maintain smectic phases up to r = [Li + ]/[EO] = 0.1. In this work, The highest ionic conductivity of 8 × 10 -3 S/cm was attained at an intermedium salt concentration of r = 0.05. It was also found that ion conduction in BTTT/dEO4 is enhanced by forming a smectic layered structure with irregular interfaces between the BTTT and EO4 layers and by the lateral film expansion upon salt addition. This can be explained by the enhancement of the misalignment and configurational entropy of the side chains, which increase their local mobility and that of the solvated ions. Our molecular design thus illustrates how, beyond the favorable energetic interactions that drive the assembly and ion solvating domains, modulation of entropic effects can also be favorably harnessed to improve ion conduction.

thin film electrochemical impedance spectroscopy↗
DOE OSTI2022

Temporal and spatial tuning of optical constants in praseodymium doped ceria by electrochemical means

Abstract Temporal and spatial tuning of the refractive index of optical thin films is desired for flat optics applications. The redistribution of mobile ions in mixed ionic-electronic conductors (MIEC) has been demonstrated to serve as a viable means for achieving optical tuning down to the nanoscale. Here we studied the dynamic range of the optical tuning achievable in the refractive index, in the MIEC oxide – Pr x Ce 1− x O 2− δ (PCO), for x = 0.1, 0.2 and 0.4, at 500 °C, by in-situ spectrophotometry. Significant increases in the modulation of both the imaginary and real optical constants in the visible and the adjacent spectra were obtained for increased doping levels. Device employing an electrochemical titration method was implemented to modulate the oxygen concentration, and thereby the optical transmission of PCO. Incorporation of a patterned top electrode allowed for the demonstration of spatial control of PCO thin film properties by in-situ video imaging of the optical switching process. The electrochemically induced optical state is shown to remain non-volatile upon quenching the device to room temperature under applied bias.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Direct Laser Writing Crystal Polymorphs of Organic Semiconductors for Phase Change Electronics

The many diverse polymorphic behaviors observed in organic electronic materials offer opportunities to modulate electronic properties through reversibly switching crystal structures. Here, we access the prolific polymorphism observed in two-dimensional quinoidal terthiophene via laser writing to locally heat and direct the phase transitions. We access a metastable polymorph IV through rapid cooling and observe distinct symmetry as well as packing through grazing incidence X-ray diffraction (GIXD). Using our open-source PolyChemPrint patterning platform, we direct laser heating to initiate the IV-I transition, switching the conductance by >2 orders of magnitude. Here, this is confirmed via a combination of GIXD and Raman spectroscopy. Finally, we demonstrate switching of transistor devices as well as discrete tuning of conductance via laser writing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Conotoxin Prediction: New Features to Increase Prediction Accuracy

Conotoxins are toxic, disulfide-bond-rich peptides from cone snail venom that target a wide range of receptors and ion channels with multiple pathophysiological effects. Conotoxins have extraordinary potential for medical therapeutics that include cancer, microbial infections, epilepsy, autoimmune diseases, neurological conditions, and cardiovascular disorders. Despite the potential for these compounds in novel therapeutic treatment development, the process of identifying and characterizing the toxicities of conotoxins is difficult, costly, and time-consuming. This challenge requires a series of diverse, complex, and labor-intensive biological, toxicological, and analytical techniques for effective characterization. While recent attempts, using machine learning based solely on primary amino acid sequences to predict biological toxins (e.g., conotoxins and animal venoms), have improved toxin identification, these methods are limited due to peptide conformational flexibility and the high frequency of cysteines present in toxin sequences. This results in an enumerable set of disulfide-bridged foldamers with different conformations of the same primary amino acid sequence that affect function and toxicity levels. Consequently, a given peptide may be toxic when its cysteine residues form a particular disulfide-bond pattern, while alternative bonding patterns (isoforms) or its reduced form (free cysteines with no disulfide bridges) may have little or no toxicological effects. Similarly, the same disulfide-bond pattern may be possible for other peptide sequences and result in different conformations that all exhibit varying toxicities to the same receptor or to different receptors. We present here new features, when combined with primary sequence features to train machine learning algorithms to predict conotoxins, that significantly increase prediction accuracy.

collisional cross section↗
DOE OSTI2026

Structural, magnetic and electrical transport properties of YMnAl

The intermetallic compound YMnAl, crystallizing in the cubic C-15 (MgCu 2 -type) structure, was prepared using arc-melting and annealing. Rietveld refinement of the XRD pattern yields a lattice parameter of a = 7.816(1) Å⁠. The system exhibits antiferromagnetic order with a transition temperature of approximately 38 K, along with indications of a spin-glass–like phase. The effective magnetic moment, estimated from Curie–Weiss fitting of the susceptibility versus temperature curve, is 6.06 μ B /f.u. and the Curie–Weiss temperature of −79 K confirming the antiferromagnetic nature. Isothermal magnetization measurements below and above the Néel temperature show no saturation, with a maximum magnetization of 0.09 μ B /f.u observed at an applied field of 9 T. The temperature dependence of resistivity exhibits a negative temperature coefficient, characteristic of dirty metals. Hall effect measurements indicate the absence of an anomalous Hall contribution. The Hall coefficient RH, carrier concentration n, and mobility μ estimated from R XY (H) are -1.05×10 -8 m 3 /C, 5.92×10 26 m -3 and 1.05×10 -3 m 2 /V.s, respectively. Our first-principles calculations indicate that YMnAl in the orthorhombic (Imma) structure has the lowest energy; however, the substitutional disorder occurring during experimental synthesis may favor the formation of the cubic Laves phase.

Crystallography↗
DOE OSTI2024

Detection of Isotopes in Urban Source Search Gamma Spectra Using Hopfield Neural Network

Source search campaigns involve the measurement of consecutive background gamma-ray spectra obtained with a mobile detector-spectrometer, such as tellurium-doped sodium iodide NaI(Tl) scintillator detector-spectrometer. Counts are measured with NaI(Tl) detector in short acquisition intervals, such as one second. Detection of isotopes in search data is challenging because of the low signal-to-noise ratio (S/N) of the spectral lines and highly varying background due to naturally occurring radioactive material (NORM). In this work, we investigate the performance of the detection of orphan Cs-137, Am-241, and I-131 isotopes in a gamma ray data set obtained in a search survey. Isotopic detection is performed with a Hopfield Neural Network (HNN), which implements an auto-associative memory by matching incoming measurements to the closest one of its memory-stored signature patterns. HNN is trained on examples of spectra of calibrated isotopic sources with well-resolved spectral lines. During testing, HNN processes spectra with partially complete or distorted isotopic lines. The performance of the HNN detection algorithm is benchmarked with Precision, Recall, and F1 scores. Test results demonstrate the potential of HNN to detect the isotope of interest with high accuracy (F1 > 90%) for all isotopes in this study.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Local p‐ and n‐Type Doping of an Oxide Semiconductor via Electric‐Field‐Driven Defect Migration

Layered oxides exhibit high ionic mobility and chemical flexibility, attracting interest as cathode materials for lithium-ion batteries and the pairing of hydrogen production and carbon capture. Recently, layered oxides emerged as highly tunable semiconductors. For example, by introducing anti-Frenkel defects, the electronic hopping conductance in hexagonal manganites is increased locally by orders of magnitude. Here, local acceptor and donor doping in Er(Mn,Ti)O3 is demonstrated, facilitated by the controlled splitting of anti-Frenkel defects under applied d.c. voltage. By combining density functional theory calculations, scanning probe microscopy, atom probe tomography, and scanning transmission electron microscopy, it is shown that the oxygen defects can readily be moved through the layered crystal structure, leading to nano-sized interstitial-rich (p-type) and vacancy-rich (n-type) regions. The resulting pattern is comparable to dipolar npn-junctions and stable on the timescale of days. These findings reveal the possibility of temporarily functionalizing oxide semiconductors at the nanoscale, giving additional opportunities for the field of oxide electronics and the development of transient electronics in general.

He, Jiali↗
DOE OSTI2022

Geographic patterns and determinants of antibiotic resistomes in coastal sediments across complex ecological gradients

Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH 4 + -N, NO 3 − -N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

Xiong, Shangling↗
DOE OSTI2020

GPU-Based Static Data-Flow Analysis for Fast and Scalable Android App Vetting

Many popular vetting tools for Android applications use static code analysis techniques. In particular, Interprocedural Data-Flow Graph (IDFG) construction is the computation at the core of Android static data-flow analysis and consumes most of the analysis time. Many analysis tools use a worklist algorithm, an iterative fixed-point approach, to construct the IDFG. In this paper, we observe that a straightforward GPU parallelization of the worklist algorithm leads to significant underutilization of the GPU resources. We identify four performance bottlenecks, namely, frequent dynamic memory allocations, high branch divergence, workload imbalance, and irregular memory access patterns. Accordingly, we propose GDroid, a GPU-based worklist algorithm implementation with multiple fine-grained optimizations tailored to common characteristics of Android applications. The optimizations considered are: matrix-based data structure, memory access-based node grouping, and worklist merging. Our experimental evaluation, performed on 1000 Android applications, shows that the proposed optimizations are beneficial to performance, and GDroid can achieve up to 128X speedups against a plain GPU implementation.

Android security↗
DOE OSTI2023

p -Azaquinodimethane: A Versatile Quinoidal Moiety for Functional Materials Discovery

The past 50 years of discovery in organic electronics have been driven in large part by the donor–acceptor design principle, wherein electron-rich and electron-poor units are assembled in conjugation with each other to produce small band gap materials. While the utility of this design strategy is undoubtable, it has been largely exhausted as a frontier of new avenues to produce and tune novel functional materials to meet the needs of the ever-increasing world of organic electronics applications. Its sister strategy of joining quinoidal and aromatic groups in conjugation has, by comparison, received much less attention, to a great extent due to the categorically poor stability of quinoidal conjugated motifs. In 2017 though, the p-azaquinodimethane (AQM) motif was first unveiled, which showed a remarkable level of stability despite being a close structural analogue to p-quinodimethane, a notably reactive compound. In contrast, dialkoxy AQM small molecules and polymers are stable even under harsh conditions and could thus be incorporated into conjugated polymers. When polymerized with aromatic subunits, these AQM-based polymers show notably reduced band gaps that follow reversed structure–property trends to some of their donor–acceptor polymer counterparts and yield organic field-effect transistor (OFET) hole mobilities above 5 cm 2 V –1 s –1 . Additionally, in an ongoing study, these AQM-based compounds are also showing promise as singlet fission (SF) active materials due to their mild diradicaloid character. An expanded world of AQMs was accessed through their ditriflate derivatives, which were first used to produce ionic AQMs (iAQMs) sporting two directly attached cationic groups that significantly affect the AQM motif’s electronics, producing strongly electron-withdrawing quinoidal building blocks. Conjugated polyelectrolytes (CPEs) created with these iAQM building blocks exhibit optical band gaps stretching into the near-infrared I (NIR-I) region and showed exemplary behavior as photothermal therapy agents. In contrast to these stable AQM examples, the synthetic exploration of AQMs also produced examples of more typical diradicaloid reactivity but in forms that were controllable and produced intriguing and high-value products. With certain substitution patterns, AQMs were found to dimerize to form highly substituted [2.2]paracyclophanes in distinctly more appreciable yields than typical cyclophane formation reactions. Certain AQM ditriflates, when crystallized, undergo light-induced topochemical polymerization to form ultrahigh molecular weight (>10 6 Da) polymers that showed excellent performances as dielectric energy storage materials. These same AQM ditriflates could be used to produce the strongly electron-donating redox-active pentacyclic structure: pyrazino[2,3-b:5,6-b']diindolizine (PDIz). Importantly, the PDIz motif allowed for the synthesis of exceedingly small band gap (0.7 eV) polymers with absorbances reaching all the way into the NIR-II region that were also found to produce strong photothermal effects. Both as stable quinoidal building blocks and through their controllable diradicaloid reactivity, AQMs have already proven to be versatile and effective as functional organic electronics materials.

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

Investigating Thaw and Plant Productivity Constraints on Old Soil Carbon Respiration From Permafrost

Isotopic radiocarbon (Δ 14 C) signatures of ecosystem respiration (Reco) can identify old soil carbon (C) loss and serve as an early indicator of permafrost destabilization in a warming climate. Warming also stimulates plant productivity causing plant respiration to dominate Reco Δ 14 C signatures and potentially obscuring old soil C loss. Here, we investigate how a wide spatio-temporal gradient of permafrost thaw and plant productivity affects Reco Δ 14 C patterns and isotopic partitioning. Spatial gradients came from a warming experiment with doubling thaw depth and variable biomass, and a vegetation removal manipulation to eliminate plant contributions. We sampled in August and September to capture transitions from high to low plant productivity, decreased surface soil temperature, and relatively small seasonal thaw extensions. We found that surface processes dominate spatial variation in old soil C loss and a process-based partitioning approach was crucial for constraining old soil C loss. Resampling the same plots in different times of the year revealed that old soil C losses tripled with cooling surface temperature, and the largest old soil C losses were detected when the organic-to-mineral soil horizons thawed (~50–60 cm). We suggest that the measured increase in old soil respiration over the season and when the organic-to-mineral horizon thawed, may be explained by mobilization of nitrogen that stimulates microbial decomposition at depth. Our results suggest that soil C in the organic to mineral horizon may be an important source of soil C loss as the entire Arctic region warms and could lead to nonlinearities in projected permafrost climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sr 2 Fe 2–X Mo X O 6 double perovskites as electrocatalysts for oxidative dehydrogenation of ethane: Effect of B-site stoichiometry

The oxidative dehydrogenation of ethane (ODHE) was investigated using a solid oxide electrocatalytic cell with Sr 2 Fe 2–X Mo X O 6–δ (SFM) double perovskite as the anode electrocatalyst. As shown in the XRD patterns, SFM perovskites maintained their cubic structure upon modifying the B-site ratios of Mo and Fe. Increasing the Mo content of the perovskite structure resulted in a lower water signal intensity at low temperatures in TPR profiles, indicative of moderate oxygen transport through the perovskite structure. Because Mo–O bonds are stronger than Fe–O bonds, the electrical conductivity of SFM perovskites decreased with increasing Mo content. When operated at 100 mA cm –2 , ODHE activity improved four times compared to open circuit voltage, resulting in 16.1% conversion of C 2 H 6 and 83.1% selectivity to C 2 H 4 . It has been demonstrated that oxygen ions provided by perovskite lattices were the key species involved in activating C 2 H 6 based on the in-situ DRIFTS experiments. In conclusion, the SFM perovskite with higher Mo content showed the highest conversion and selectivity due moderate oxygen ion mobility and fast desorption of C 2 H 4 .

25 ENERGY STORAGE↗