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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2022

Emergent microrobotic oscillators via asymmetry-induced order

Abstract Spontaneous oscillations on the order of several hertz are the drivers of many crucial processes in nature. From bacterial swimming to mammal gaits, converting static energy inputs into slowly oscillating power is key to the autonomy of organisms across scales. However, the fabrication of slow micrometre-scale oscillators remains a major roadblock towards fully-autonomous microrobots. Here, we study a low-frequency oscillator that emerges from a collective of active microparticles at the air-liquid interface of a hydrogen peroxide drop. Their interactions transduce ambient chemical energy into periodic mechanical motion and on-board electrical currents. Surprisingly, these oscillations persist at larger ensemble sizes only when a particle with modified reactivity is added to intentionally break permutation symmetry. We explain such emergent order through the discovery of a thermodynamic mechanism for asymmetry-induced order. The on-board power harvested from the stabilised oscillations enables the use of electronic components, which we demonstrate by cyclically and synchronously driving a microrobotic arm. This work highlights a new strategy for achieving low-frequency oscillations at the microscale, paving the way for future microrobotic autonomy.

42 ENGINEERING↗
DOE OSTI2026

The anaerobic fungus Caecomyces churrovis produces H 2 via a non-bifurcating NADH-dependent enzyme complex

ABSTRACT Hydrogenosomes are mitochondria-derived organelles that produce ATP and H 2 to support energy metabolism in anaerobic eukaryotes. H 2 production allows reoxidation of reduced cofactors generated during fermentative metabolism; however, the metabolic mechanisms for H 2 production in anaerobic eukaryotes remains incompletely understood. In particular, it remains unclear whether anaerobic fungi (AF) hydrogenosomes use a ferredoxin-dependent pathway or a distinct mechanism to regenerate NAD(P) + and link electron transfer to H 2 formation. Here, by combining genomic search, proteomic analysis, and enzymology, we reveal the molecular mechanism for H 2 production in the AF strain Caecomyces churrovis . Our enzyme assays on the organelle fraction of C. churrovis revealed the activity of H 2 :NAD + oxidoreductase but not pyruvate:ferredoxin oxidoreductase, which is usually linked to H 2 formation. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis , and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified enzymes, we found Hyd and NuoEF proteins formed H 2 directly from NADH independently of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is commonly shared among the AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could potentially be exploited as a target for controlling AF H 2 production and altering fungal metabolism. IMPORTANCE H 2 production is a prominent feature of anaerobic energy metabolism, yet our understanding of eukaryotic mechanisms remains limited. Anaerobic fungi (AF) are key decomposers of lignocellulose and contribute to hydrogen flux in anaerobic environments. Although it has been more than 40 years since the H 2 production from AF was first reported, the molecular mechanism for hydrogenosomal H 2 production and redox balance remains unclear. We demonstrate that AF produce H 2 from NADH utilizing a non-bifurcating NADH-dependent enzyme complex rather than an electron-bifurcating, ferredoxin-dependent variant. We show that this enzyme complex is conserved across multiple AF lineages and thus demonstrate the occurrence of a non-bifurcating NADH-dependent enzyme in eukaryotes. This discovery expands our understanding of eukaryotic hydrogenosomal metabolism, reveals a previously unknown strategy for redox balancing, and highlights potential targets for manipulating H 2 production. These insights have broad implications for microbial energy metabolism, anaerobic ecosystems, and bioengineering of H 2 -producing systems.

Zhang, Bo [Department of Chemical Engineering, Uni↗
DOE OSTI2020

Towards single-species selectivity of membranes with subnanometre pores

Synthetic membranes with pores at the subnanometre scale are at the core of processes for separating solutes from water, such as water purification and desalination. While these membrane processes have achieved substantial industrial success, the capability of state-of-the-art membranes to selectively separate a single solute from a mixture of solutes is limited. Such high-precision separation would enable fit-for-purpose treatment, improving the sustainability of current water-treatment processes and opening doors for new applications of membrane technologies. In this paper, we introduce the challenges of state-of-the-art membranes with subnanometre pores to achieve high selectivity between solutes. Here, we then analyse experimental and theoretical literature to discuss the molecular-level mechanisms that contribute to energy barriers for solute transport through subnanometre pores. We conclude by providing principles and guidelines for designing next-generation single-species selective membranes that are inspired by ion-selective biological channels.

42 ENGINEERING↗
DOE OSTI2020

Etching sharp tips from thin metallic wires for tuning-fork-based scanning probe microscopy

Sharp tips are critical for obtaining high resolution images in scanning probe microscopy (SPM), particularly in samples with large variations in topography. For tuning-fork-based SPM, such tips are commonly obtained by electrochemical etching of metallic wires (e.g., tungsten). Electrochemical etching of metallic wires is the preferred means of preparing tips for scanning tunneling microscopy (STM), and techniques for obtaining sharp tips have been investigated extensively. However, the requirements for STM and tuning-fork-based SPM are different. In particular, the wires used in STM are typically 250-500 μ m in diameter, while the wires used for tuning-fork-based SPM are usually an order of magnitude narrower in order to minimize loading of the tuning fork: 25-50 μ m and sometimes down to a few micrometers in diameter. Consequently, many of the recipes developed for etching thicker metallic wires for STM tips do not give optimal results for smaller diameter wires. The authors describe here a modification of the etching circuit of Ibe et al . that significantly improves the reproducibility and reliability of the etching process for thin wires, and discuss the parameters that affect the aspect ratio of produced tips.

42 ENGINEERING↗
DOE OSTI2025

Selection of solvents for integrated CO 2 absorption and electrochemical reduction systems

Abstract Solvent‐based electrochemical CO 2 reduction (CO 2 R) enables the production of chemicals or fuels using CO 2 from a preceding absorption process. Employing previously tested CO 2 capture solvents does not ensure their suitability for either CO 2 R or integrated CO 2 absorption‐reduction. We propose solvent selection criteria that include the CO 2 solubility, kinetic constant, ionic conductivity, concentration of the bicarbonate, carbamate, and solvent cation in the CO 2 ‐loaded solution, and sustainability indicators. They are implemented for solvent selection (a) from novel, aqueous mixtures of N ‐methylcyclohexylamine (MCA) with piperazine (PZ), 2‐amino‐2‐methyl‐1‐propanol (AMP), potassium hydroxide (KOH), and potassium chloride (KCl) and (b) from aqueous monoethanolamine (MEA), AMP, KOH, MCA, and PZ solutions. Versions of a modified Kent‐Eisenberg model for strong bases, carbamate, and non‐carbamate‐forming amine solutions are developed and parameterized through experimental equilibrium measurements. CO 2 R experimental results are presented for solutions of KOH and MCA + KOH, as these indicate desired trade‐offs for CO 2 absorption and reduction.

Amines↗
DOE OSTI2020

A statistical model for the product energy distribution in reactions leading to prompt dissociation

Direct dynamics calculations have been performed for three reactions: C 3 H 8 + H → i-C 3 H 7 + H 2 , C 3 H 8 + H → n-C 3 H 7 + H 2 , and C 2 H 3 + O 2 → HCO + CH 2 O. The fraction of the population for the radical products that promptly dissociates is computed. Here the results for C 3 H 8 + H are qualitatively similar to previous results for C 3 H 8 + OH, but the new results exhibit a slightly higher branching fraction for prompt dissociation products, owing to the fact that a greater fraction of the internal energy in the transition state ends up in the radical. For C 2 H 3 + O 2 → HCO + CH 2 O, the fraction of HCO that promptly dissociates is in excess of 99%. Consequently, the main product for C 2 H 3 + O 2 at lower temperatures should be written as H + CO + CH 2 O and not HCO + CH 2 O. These results are then compared with four previous systems: CH 2 O + H → HCO + H 2 , CH 2 O + OH → HCO + H 2 O, C 3 H 8 + OH → i-C 3 H 7 + H 2 O, and C 3 H 8 + OH → n-C 3 H 7 + H 2 O. Based upon these seven system, several statistical models are presented. The goal of these statistical models is to predict the fraction of the transition state energy that ends up in the rovibrationally excited radical. On average, these statistical models provide an excellent prediction of product energy distribution. Consequently, these models can be used instead of costly trajectory simulations for predicting prompt radical dissociation for larger species.

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

Thermodynamic modeling of countercurrent chemical looping reverse water gas shift process for redox material screening

The reverse water gas shift (RWGS) reaction is a key pathway for CO 2 utilization, particularly within Power-to-X process chains aimed at sustainable fuel and chemical production. Countercurrent chemical looping (CL-RWGS) using non-stoichiometric oxides can overcome equilibrium limitations of conventional RWGS reactors, enabling significantly higher CO 2 conversions. However, modeling the limiting performance of such systems is challenging due to their multiphase nature and coupled spatial and temporal variation in chemical composition. In this work, we present a discretized batch equilibrium model that simulates CL-RWGS reactors as a series of localized equilibrium exchanges between gas and solid elements. The model is numerically stable, computationally efficient, and free of kinetic source terms, making it well-suited for parametric studies and system-level integration. It is validated against established convection–diffusion models and shown to predict reasonable upper bounds on experimental results. Application of the model to a range of oxygen carrier materials identifies cerium–zirconium solid solutions, particularly Ce 0.80 Zr 0.20 O 2 , as a promising class offering superior oxygen storage characteristics compared to state-of-the-art La 0.6 Sr 0.4 FeO 3 . This framework provides a robust platform for materials screening, reactor sizing, and performance optimization in chemical looping systems. The model implementation is available as open-source software to support further research and development.

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

High-throughput chemical imaging for optimizing biofuel synthesis using synthetic biology (Final Technical Report)

Fatty acids can be produced biosynthetically in microbes and these compounds can serve as precursors to biodiesels and other high value oleochemicals. However, progress on engineering fatty acid biosynthesis, and biofuel synthesis more generally, has been hindered by current quantification methods that are either indirect or not amenable to high-throughput or single-cell resolution screening. In this project, we assembled an interdisciplinary team with complimentary expertise in synthetic biology and microscopy, metabolic engineering, and chemical imaging to address these challenges. We used chemical imaging to directly measure lipid biosynthesis in Escherichia coli engineered to produce fatty acids, obtaining detailed single-cell resolution measurements. We deployed stimulated Raman scattering (SRS) microscopy in concert with multiplexed genome engineering and gene circuit design strategies from synthetic biology to optimize production of fatty acids. These results provided novel insight into cell-to-cell heterogeneity present in biofuel production strains. In addition, we introduced new chemical imaging methods which are label-free and do not require fluorescent reporters. These efforts were complemented by other studied developing foundational tools for regulation and control, which offer excellent potential for advancing researchers’ ability to rapidly design, build, and test strains for enhanced biofuel synthesis.

09 BIOMASS FUELS↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2022

Acid anion electrolyte effects on platinum for oxygen and hydrogen electrocatalysis

Platinum is an important material with applications in oxygen and hydrogen electrocatalysis. To better understand how its activity can be modulated through electrolyte effects in the double layer microenvironment, herein we investigate the effects of different acid anions on platinum for the oxygen reduction/evolution reaction (ORR/OER) and hydrogen evolution/oxidation reaction (HER/HOR) in pH 1 electrolytes. Experimentally, we see the ORR activity trend of HClO 4 > HNO 3 > H 2 SO 4 , and the OER activity trend of HClO 4 > HNO 3 ~ H 2 SO 4 . HER/HOR performance is similar across all three electrolytes. Notably, we demonstrate that ORR performance can be improved 4-fold in nitric acid compared to in sulfuric acid. Assessing the potential-dependent role of relative anion competitive adsorption with density functional theory, we calculate unfavorable adsorption on Pt(111) for all the anions at HER/HOR conditions while under ORR/OER conditions ClO$^{-}_{4}$ binds the weakest followed by NO$^{-}_{3}$ and SO$^{2-}_{4}$. Our combined experimental-theoretical work highlights the importance of understanding the role of anions across a large potential range and reveals nitrate-like electrolyte microenvironments as interesting possible sulfonate alternatives to mitigate the catalyst poisoning effects of polymer membranes/ionomers in electrochemical systems. These findings help inform rational design approaches to further enhance catalyst activity via microenvironment engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Genetic algorithm optimization of a chemical kinetic mechanism for propane at engine relevant conditions

Propane has demonstrated significant potential for reductions in greenhouse gas and pollutant emissions in medium- and heavy-duty engine applications, but further improvements require accurate, compact, and scalable chemical kinetic mechanisms to design the next generation of propane fueled engines, particularly at the boosted operating conditions necessary to meet the power density demand of medium- and heavy-duty applications. In this work, six key chemical reactions were identified in a reduced mechanism with 70 species and 352 reactions through a sensitivity analysis performed at conditions typical of thermodynamic trajectories observed in a high compression ratio, long stroke engine operated on propane from throttled to boosted operating conditions. While the original mechanism was validated against rapid compression machine (RCM) data, it was found to overpredict experimental autoignition tendencies in 2-zone, 0-D SI engine simulations performed in Chemkin Pro. Subsequently, a genetic algorithm approach was used to optimize the six reaction rate parameters within established uncertainty bounds by performing RCM simulations and comparing to two independent sets of literature ignition delay times for propane, thus generating two new kinetic mechanisms. The first optimization achieved a mean absolute percent error (MPE) reduction in 2nd stage ignition delay of 61.4% in seven generations, while the second optimization utilized a newer experimental RCM dataset, and achieved MPE reduction of 56.7% in seven generations, and further marginal improvement to 57.8% reduction in 34 generations. Finally, the two mechanisms were then evaluated again in the 2-zone 0-D SI engine model in Chemkin Pro comparing typical mean and knocking cycle trajectories, and it was found that the second optimized mechanism provided better prediction of knock onset at the representative conditions evaluated in this work, particularly for higher load operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electronic Spin Qubit Candidates Arrayed within Layered Two-Dimensional Polymers

Molecular electronic spin qubits are promising candidates for quantum information science applications because they can be reliably produced and engineered via chemical design. Embedding electronic spin qubits within two-dimensional polymers (2DPs) offers the possibility to systematically engineer inter-qubit interactions while maintaining long coherence times, both of which are prerequisites to their technological utility. Here, we introduce electronic spin qubits into a diamagnetic 2DP by n-doping naphthalene diimide subunits with varying amounts of CoCp 2 and analyze their spin densities by quantitative electronic paramagnetic resonance spectroscopy. Low spin densities (e.g., 6.0 × 10 12 spins mm –3 ) enable lengthy spin–lattice (T 1 ) and spin–spin relaxation (T 2 ) times across a range of temperatures, ranging from T 1 values of 164 ms at 10 K to 30.2 μs at 296 K and T 2 values of 2.36 μs at 10 K to 0.49 μs at 296 K for the lowest spin density sample examined. Higher spin densities and temperatures were both found to diminish T 1 times, which we attribute to detrimental cross-relaxation from spin–spin dipolar interactions and spin–phonon coupling, respectively. Higher spin densities decreased T 2 times and modulated the T 2 temperature dependence. Here, we attribute these differences to the competition between hyperfine and dipolar interactions for electron spin decoherence, with the dominant interaction transitioning from the former to the latter as spin density and temperature increase. Overall, this investigation demonstrates that dispersing electronic spin qubits within layered 2DPs enables chemical control of their inter-qubit interactions and spin decoherence times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Equilibrium and non-equilibrium effects in high pressure phase transformations of carbon

The behavior of carbon in the range 1–100 GPa and 1–10 kK is central to problems in planetary interiors, inertial confinement fusion targets, and high-pressure synthesis of carbon-based materials, but experiments in this regime are difficult and often provide only indirect constraints on phase behavior. As a result, phase boundary loci, structure, and limits of metastability at high pressure remain uncertain. In this work, machine-learning enhanced atomistic simulations are used to address this knowledge gap. We determine the melt line up to 100 GPa, the graphite-diamond phase boundary up to the melt line, and analyze structure of the coexisting phases. We show that the coexisting liquid evolves smoothly with pressure without evidence for a first-order liquid–liquid transition. Orientation-resolved graphite melting simulations indicate that basal-plane interfaces develop a dewetting layer and undergo layer-by-layer melting, producing kinetic hysteresis and an apparent orientation dependence of the melt line. Non-equilibrium quenches from the melt are used to construct a kinetically limiting graphite–diamond phase boundary for rapid quenches from above the melt line, and show that graphite is metastable at pressures of up to ≈ 25 GPa. These results provide bounds on equilibrium and metastable behavior in carbon relevant for interpreting high-pressure experiments and for designing synthesis pathways to specific carbon microstructures.

Lyu, Yanjun [Department of Materials Science and E↗
DOE OSTI2023

Characterizing and Engineering Trehalose Biosynthesis Pathways to Improve Acetate Tolerance in Pseudomonas putida KT2440

Alkaline pretreatment can depolymerize lignin into a diverse mixture of monomers and smaller compounds, enabling bioconversion of these compounds to value-added chemicals in engineered bacterial hosts such as Pseudomonas putida KT2440. Acetate and salts comprise approximately 8% and 32% of the lignin stream, respectively. High concentrations of these components can cause cell death in P. putida, so lignin-derived streams must be fed in lower amounts to decrease stress. Investigation of the mechanisms of bacterial tolerance to chemicals in lignin-rich substrates is therefore required to overcome this obstacle in lignin bioconversion. Previous work has shown that trehalose, an endogenously produced disaccharide, is involved in tolerance to heat, cold, and osmotic stress, as well as implicated in acid stress in other bacteria. As such, trehalose biosynthesis presents a useful target to increase acetate and osmotic tolerance in P. putida. This work investigates the native TreSA, TreSB, and TreY/TreZ trehalose biosynthesis pathways in this bacterial strain as well as the OtsAB pathway of Sphingobium sp. SYK-6. Overexpression of the OtsAB pathway in P. putida increased tolerance to acetate relative to wild-type. Additionally, functional knockouts of treSA, treSB, treY, and treZ in P. putida showed that interruption of any trehalose biosynthesis pathway, and, in the case of TreY/TreZ, interruption of the pathway at any point, significantly hindered growth in acetate as well as on glucose and LB broth. Each trehalose biosynthesis pathway was then engineered for overexpression in P. putida to determine whether overexpression of these genes conferred additional tolerance to acetate. The TreSA, TreSB, OtsA, and OtsB enzymes were also expressed and purified to determine the reaction rates and kinetics of these pathways. The hypothetical glycoside hydrolase family 15 protein, encoded in the gene located in between otsB and otsA in the Sphingobium operon, was purified as well to investigate its potential involvement in the OtsAB pathway. The findings of this work illuminated the mechanisms of trehalose biosynthesis in P. putida and identified genetic targets to improve strain tolerance to common components of alkaline-pretreated lignin streams. These findings could ultimately improve yields of desired products from lignin in engineered strains of P. putida.

alkaline pretreatment↗