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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Bark morphological and chemical features are differentially correlated with disease resistance and yield in hybrid poplar taxa

In the southeastern United States, the establishment of short-rotation intensively cultured plantations of hybrid poplar has been hindered by its susceptibility to stem cankers. We evaluated the tradeoffs between biomass yield and disease tolerance in hybrid poplar genotypes belonging to P. deltoides × P. maximowiczii (DM), P. deltoides × P. nigra (DN), P. trichocarpa × P. maximowiczii (TM), and P. deltoides × P. deltoides (DD) taxa. We hypothesized that canker resistant genotypes will have thicker bark but bark thickness and biomass yield will be negatively correlated. After two growing seasons, the DD genotypes developed thicker bark compared to the genotypes of other taxa and bark thickness was not correlated with biomass yield in the DD genotypes (R 2 = 0.002). However, in the TM, DM, and DN genotypes, bark thickness was negatively correlated with biomass yield (R 2 = 0.33–0.77). Disease incidence studies revealed that the DM genotypes were most susceptible to canker whereas no disease was detected in DD genotypes. Furthermore, bark analysis conducted by Fourier transform infrared spectroscopy coupled with multivariate analysis showed that that DD genotypes to be chemically separate from the three hybrid genotypes and that bark chemistry was correlated with canker disease incidence. Taken together, these results reveal that it is possible to generate hybrid poplar genotypes with thicker bark, disease resistance, and higher biomass yields. This insight should guide further efforts to develop genetically improved hybrid poplar genotypes, both in terms of biomass yield and disease tolerance, for cultivation in the southeastern United States. Hybrid poplar cultivation in southeastern United States is hindered by its susceptibility to stem cankers. We evaluated tradeoffs between yield and canker disease resistance in various hybrid poplar genotypes. After two growing seasons, the DD genotypes showed disease resistance and developed thicker bark that was chemically distinct from the other genotypes. Bark thickness was not correlated with yield in the DD genotypes but was negatively correlated with yield in the other genotypes. These results will guide the development of hybrid poplar genotypes that are both disease resistant and high yielding for cultivation in the southeastern United States.

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

Effects of soybean 7S protein on the quality and digestibility of dry rice noodles under twin‐screw extrusion process

Summary Starch and protein are important components of food, the mixed system formed between them (complexes, gels, mixtures, etc.) can improve the physical and chemical properties of starch and protein, and its potential application in the food industry has also attracted widespread attention. In this study, indica rice flour and soybean 7S protein (β‐Conglycinin) were used as the experimental materials to explore the effect of soybean 7S protein addition on the quality and digestibility of rice noodles. Aims to develop rice noodles with high protein and low GI, so that people can take care of their health while satisfying their appetites. The results showed that with the increase of soybean 7S protein addition, the starch digestibility decreased, resulting in the estimated glycaemic index (eGI) and glycaemic load (GL) decreasing. However, the cooking loss rate and breakage rate of rice noodles gradually increased, the water absorption first increased and then decreased, and the taste of rice noodles is acceptable when the 7S protein addition amount is within 9%. The interaction between starch and soybean 7S protein was mediated by weak interactions such as hydrogen bonds and hydrophobic forces indicated by Fourier transform infrared spectroscopy (FTIR) and X‐ray diffraction (XRD).

Qiao, Fan↗
DOE OSTI2021

Structural, vibrational, thermal, and magnetic properties of mullite-type NdMnTiO 5 ceramic

Mullite-type $R$Mn 2 O 5 ($R$ = Y, rare-earth element) ceramics are of ongoing research attention because of their interesting crystal-chemical and magnetic properties. We report nuclear and magnetic structures of NdMnTiO 5 together with its spectroscopic, thermogravimetric, and magnetic properties. The polycrystalline sample is prepared by solid-state synthesis and characterized from neutron and X-ray powder diffraction data Rietveld refinements. NdMnTiO 5 crystallizes in the orthorhombic space group $Pbam$ with metric parameter $a$ = 755.20(1) pm, $b$ = 869.91(1) pm, $c$ = 582.42(1) pm, and $V$ = 382.62(1) 10 6 pm 3 . The Mn 3+ and Ti 4+ cations are observed to be located in the octahedral and pyramidal sites, respectively. The vibrational features in these polyhedral sites are characterized by Raman and Fourier transform infrared spectroscopes. The higher decomposition temperature of NdMnTiO 5 , compared to other $R$Mn 2 O 5 phases, is explained in terms of the higher bond strength of Ti-O bonds than those of Mn-O bonds. Temperature-dependent DC magnetic susceptibility suggests a paramagnetic to antiferromagnetic phase transition at 43(1) K. Inverse susceptibility in the paramagnetic region above 120 K follows the Curie-Weiss law, resulting in a magnetic moment of 6.33(1) μ B per formula unit. Neutron diffraction data collected at 7.5 K reveal that the magnetic moments of Nd 3+ and Mn 3+ in NdMnTiO 5 are incommensurately ordered with a propagation vector $k$ = (0, 0.238, 0.117).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Validation of Numerical Models of the Offshore Wind Turbine From the Alpha Ventus Wind Farm Against Full-Scale Measurements Within OC5 Phase III

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project validates OWT models against the measurements recorded on a Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. The following operating conditions of the wind turbine were chosen for the validation: (1) idling below the cut-in wind speed, (2) rotor-nacelle assembly (RNA) rotation maneuver below the cut-in wind speed, (3) power production below and above the rated wind speed, and (4) shutdown. A number of validation load cases were defined based on these operating conditions. The following measurements were used for validation: (1) strains and accelerations recorded on the support structure and (2) pitch, yaw, and azimuth angles, generator speed, and electrical power recorded from the RNA. Strains were not directly available from the majority of the OWT simulation tools; therefore, strains were calculated based on out-of-plane bending moments, axial forces, and cross-sectional properties of the structural members. The simulation results and measurements were compared in terms of time series, discrete Fourier transforms, power spectral densities, and probability density functions of strains and accelerometers. A good match was achieved between the measurements and models setup by OC5 Phase III participants.

17 WIND ENERGY↗
DOE OSTI2025

Simultaneous Control of Unburned NH 3 and NO x Emissions From High Load Dual-Fuel Ammonia Operation on a High-Speed Diesel Engine Using a Cu-SCR System

Dual-fuel ammonia strategies are being investigated as a promising way to utilize NH 3 as an alternative fuel for internal combustion engines in the maritime sector. One of the remaining barriers to implementing dual-fuel NH 3 combustion strategies is understanding ways to minimize unburned NH 3 and nitrogen oxide (NO x ) emissions from these engines, both of which are elevated relative to a conventional diesel baseline. Selective catalytic reduction (SCR) systems are widely used for lean NO x emission controls for engines across transportation and stationary energy applications. SCR systems use a reducing agent, such as NH 3 , to react with NO x in the exhaust, converting it into nitrogen and water. Typically, NH 3 is injected into the exhaust as a urea solution. In dual-fuel NH 3 engines, where unburned NH 3 is present in the exhaust, an SCR system could be used to mitigate both NH 3 and NO x emissions. The presented work evaluates a commercial copper-zeolite SCR and ammonia slip catalyst system, designed for on-road diesel engine applications, for controlling unburned NH 3 and NO x emissions from a dual-fuel NH 3 combustion engine. The aftertreatment system was installed downstream of a single-cylinder four-stroke diesel engine that has been modified for dual-fuel ammonia use. Furthermore, the emissions were characterized by using a Fourier transform infrared spectrometer for both late- and early-injection diesel pilot strategies over three air–fuel equivalence ratios spanning from 1.6 to 1.0 at 1200 rpm and 12.6 bar IMEP g condition (with greater than 95% ammonia energy fraction). Initial findings indicate that the SCR achieves more than 99% NO x conversion with less than 50 ppm NH 3 slip at air–fuel equivalence ratios greater than 1.4 at the operating conditions investigated. However, these benefits are accompanied by additional N 2 O emissions that are formed over the Cu-SCR.

Catalysts↗
DOE OSTI2021

Experimental Investigation on the Performance Loss of Cross-Linked Polymers During Photo-Oxidative Aging

Abstract Polymeric substances have seen an unprecedented integration in countless applications and fields of life, subjecting them to a broad range of environmental conditions, which can cause a form of damage to the structural and mechanical properties of these components known as aging. In this study we investigate the effects of the degradation of polymeric materials due to the extended exposure to sunlight, which can be simulated through controlled photo-oxidative aging using ultraviolet (UV) radiation as the main catalyst of this phenomenon. The effects on mechanical behavior and chemical properties of four polymeric materials with different mechanical characteristics was accordingly monitored throughout the study. The materials range in hardness with the polyurethane adhesive being the hardest and acting plastically, followed by an acrylic which exhibits greater hardening with time, a polyurethane sealant, which behaves in an elastomeric manner, and a silicon sealant, which is the softest of the set. Samples were prepared and subjected to UV radiation at three different temperatures namely 45, 60 and 80°C, for different aging periods ranging from 1 day for higher temperatures to 150 days for lower ones. The samples were then subjected to the Fourier transform Infrared spectroscopy (FTIR) test to monitor the change in the chemical composition of the materials along the aging durations and conditions. The materials were then subjected to mechanical testing along two modes of mechanical loading, which are a simple tension until failure and a double-cyclic test with progressively increasing strain limits after every two successful cycles until the sample reaches failure. The samples are loaded at constant strain rates throughout both tests. These tests revealed the change of behavior of our materials along the aging periods and conditions. The changes in mechanical behavior vary across each individual material depending on the aging temperature and period, with the changes ranging from hardening to softening, embrittlement or an increase in the maximum strain the material can endure before failure. A general trend would be that most materials become harder after photo-oxidation, however due to the range of temperatures in the aging conditions, thermo-oxidation, which causes softening in some of the polymers, has an increasingly notable effect at higher temperatures. A visible correlation can be noted between the change in mechanical behavior and a change in absorbance of Infrared Radiation (IR) in the FTIR spectrum, as the greater the crosslinking throughout the polymer matrix, the lower the absorbance of IR radiation due to the increased stiffness of the overall macro-molecular structure.

Korayem, Abd-Elrahman↗
DOE OSTI2024

Evaluation of Common Thermoplastic Polymers in High-Pressure Cycling Hydrogen Under Ambient and Cold Environments as Applicable to the Hydrogen Infrastructure

Thermoplastic polymers are required to perform unfailingly under stringent conditions of changing pressures (35 MPa to 70 MPa) and temperatures (-40°C to +85°C) in storage and fueling operations. Although diffusivity in glassy polymers appear to be an order of magnitude lower than elastomers, polymer microstructural attributes such as degree of crystallinity and presence of polar and non-polar groups on the main chain with and without branching can play a substantial role in influencing their behaviors in hydrogen environments. In the work described here, the effect of high-pressure hydrogen cycling on PEEK, PTFE, PA11, HDPE, POM (and different commercial grades of these polymers) under ambient and cold (-40°C) conditions is addressed. Ex-situ characterization for polymer changes included density measurements for impact of hydrogen retention, hardness changes using nanoindentation, storage modulus and glass transition changes using dynamic mechanical and thermal analysis (DMTA), degree of crystallization with Differential Scanning Calorimetry (DSC) and tensile testing following ASTM D412. In other evaluations, solid-state nuclear magnetic resonance (NMR), attenuated total reflectance Fourier transform infra-red spectroscopy (ATRFTIR), X-ray diffraction (XRD), and X-ray CT results are presented. The overall impact of these evaluations is to establish a technical basis for the behaviors of common thermoplastics in cycling hydrogen environments under ambient and cold temperatures while establishing the relationship between polymer structure-based properties and hydrogen transport effects.

Menon, Nalini C.↗
DOE OSTI2019

Infrared absorption cross section of SiN x thin films

At the molecular level, resonant coupling of infrared radiation with oscillations of the electric dipole moment determines the absorption cross section, $σ$. The parameter σ relates the bond density to the total integrated absorption. In this work, $σ$ was measured for the Si–N asymmetric stretch mode in SiN x thin films of varying composition and thickness. Thin films were deposited by low pressure chemical vapor deposition at 850 °C from mixtures of dichlorosilane and ammonia. σ for each film was determined from Fourier transform infrared spectroscopy and ellipsometric measurements. Increasing the silicon content from 0% to 25% volume fraction amorphous silicon led to increased optical absorption and a corresponding systematic increase in σ from 4.77 × 10 –20 to 6.95 × 10 –20 cm 2 , which is consistent with literature values. The authors believe that this trend is related to charge transfer induced structural changes in the basal SiN x tetrahedron as the volume fraction of amorphous silicon increases. Furthermore, experimental $σ$ values were used to calculate the effective dipole oscillating charge, q, for four films of varying composition. The authors find that q increases with increasing amorphous silicon content, indicating that compositional factors contribute to modulation of the Si–N dipole moment. Additionally, in the composition range investigated, the authors found that $σ$ agrees favorably with trends observed in films deposited by plasma enhanced chemical vapor deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantum JPEG

The joint photographic expert group algorithm compresses a digital image by filtering its high spatial-frequency components. Similarly, we introduce a quantum algorithm that uses the quantum Fourier transform to discard the high spatial-frequency qubits of an image, downsampling it to a lower resolution. This allows one to capture, compress, and send images even with limited quantum resources for storage and communication. We show under which conditions this protocol is advantageous with respect to its classical counterpart.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Atomic layer deposition of HfO 2 films using carbon-free tetrakis(tetrahydroborato)hafnium and water

Thin hafnium oxide films were prepared by atomic layer deposition using a carbon-free precursor, tetrakis(tetrahydroborato)hafnium [Hf(BH 4 )( 4 )], and H 2 O. Film growth was studied using an in situ quartz crystal microbalance and Fourier transform infrared spectroscopy measurements. Self-limiting growth was observed between 100 and 175 degrees C, but the thermal decomposition of the Hf precursor occurred at higher temperatures. The film properties were investigated using x-ray photoelectron spectroscopy, x-ray reflectivity, x-ray diffraction, ellipsometry, time-of-flight secondary ion mass spectrometry, and x-ray absorption spectroscopy. The as-deposited films were found to consist of an amorphous mixture of HfO 2 and B 2 O 3 , and had a lower density and lower refractive index compared to pure HfO 2 thin films. Finally, annealing the films to >750 degrees C yielded crystalline monoclinic HfO 2 with a density of 9g/cm 3 and a refractive index of 2.10.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modulating the optoelectronic properties of hybrid Mo-thiolate thin films

In this study, hybrid MoS 2 -based molybdenum thiolate thin films with selected organic motifs are grown using molecular layer deposition (MLD), allowing for tunable optoelectronic film properties. The thin films are deposited at 170°C using the metal precursor molybdenum hexacarbonyl and one of the three organic precursors: 1,2-ethanedithiol, 1,4-butanedithiol, and 1,4-benzenedithiol. The resulting Mo-ethanethiolate, Mo-butanethiolate, and Mo-benzenethiolate films show saturating growth with a growth per cycle of 1.2, 1.0, and 1.5 Å/cycle, respectively. Fourier transform infrared spectroscopy, x-ray photoelectron spectroscopy, Raman spectroscopy, x-ray absorption spectroscopy, and x-ray diffraction are used to characterize the as-deposited films. Results show that by changing the organic precursor, the film composition as well as the optical and electronic properties can be tuned. The Mo-thiolate films grown with benzenedithiol exhibit the lowest resistivity, which at 12 mΩ cm is ~400 times more conductive than Mo-thiolates grown with aliphatic organic linkers. All three backbone chemistries of the Mo-thiolates show an optical bandgap between 2.3 and 2.4 eV and mild photoconductivity response. The MLD of these Mo-thiolate films demonstrates the synthesis of transition metal-organosulfur thin films with tunable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

Since solids are only sometimes seen en masse in a pure bulk form, and for liquids other than water almost never, a capability to model reflectance spectra from analytes deposited on various substrates would be highly advantageous. If available, the real, n ( ν ) , and imaginary, k ( ν ) , components of the complex refractive index, n n + i k , can be used to simulate infrared spectra, accounting for reflection, refraction, and absorption phenomena as a function of wavelength. We focus on using the Pacific Northwest National Laboratory (PNNL) derived n / k vectors for solid and liquid analytes deposited as thin layers on different types of substrates including conductors, such as aluminum, and inorganic dielectrics, such as glass. The model is an adaptation of the Monte Carlo ray trace modeling program, TracePro, extended through the use of its macrolanguage. The model is tested using thin films of organic liquids including silicone oil and no. 2 diesel fuel, as well as organic solids such as caffeine and acetaminophen on aluminum and glass. The predicted spectra for the solid films were compared to experimental hemispherical reflectance data measured using a Fourier transform spectrometer with an integrating sphere. The thickness of the calculated layer is a parameter for predicting the (transflectance) spectra and is obtained using the areal density measured from gravimetric methods to generate the thin-layer samples. Comparison of the calculated spectra with experimental hemispherical reflectance data shows excellent agreement, indicating promise for the use of measured n / k data to synthesize reference spectral data. In particular, accounting for the inhomogeneity of the deposits greatly improved the match with experimental data. Finally, the theoretical modeling shows that for thicker layers (ca. 20 to 100 μm) of typical organics possessing moderately strong k values, the longwave infrared features are often saturated and better spectral contrast is obtained from the overtone/combination bands in the shortwave infrared.

42 ENGINEERING↗
DOE OSTI2020

Quantitative far-infrared band strengths of iodine monochloride (ICl), a molten salt off-gas product

The gaseous (by)products generated from molten salt reactors need to be monitored to prevent the release of potentially toxic gases to the environment. In particular, 129I has a long half-life and its toxicity and persistence in the environment make iodine and iodine-containing compounds (such as ICl from chloride containing molten salt systems) of great concern. Optical spectroscopy tools, including Raman and Fourier-transform infrared (FTIR) spectroscopies, are ideal for monitoring and quantifying such off-gas products. Iodine (I2) has a strong and distinct Raman signature and the change in signal with a change in concentration can be used for quantification of these byproducts. Iodine monochloride (ICl) has distinct signatures in both the Raman and the infrared, and its spectrum can also potentially be used for quantitative measurement of this species. In this paper we discuss our recent results on the quantification of iodine monochloride using infrared spectroscopy, in particular first reports of the absolute infrared band strength of ICl.

infrared (IR) spectroscopy, Molten Salt Reactors, ↗
DOE OSTI2021

Application of machine learning to estimate fireball characteristics and their uncertainty from infrared spectral data

Experiments or events involving high explosives (HE) can be monitored remotely by infrared (IR) sensors to gather information about the configuration or materials involved in the device. Researchers at the Air Force Institute of Technology (AFIT) developed a phenomenological model for HE fireball spectra in the IR range that allows for parameters to be extracted from Fourier transform infrared (FTIR) data. This model includes parameters tied to physical characteristics of the fireball: temperature, size, soot, and gas concentrations. Previous works have sought to recover these parameters by the fitting of either whole spectra or select wavenumber bands to this phenomenological model. Difficulties arise due to the complex relationships between the parameters to be fit. Uncertainty quantification of the estimated fireball parameters is also problematic since HE experiments do not have any ground truth information on the parameters. It is suggested that artificial neural network (ANN) based approaches may be well suited to this problem, because of their ability to capture complex and highly nonlinear relationships. As such, this work seeks to explore the efficacy of deep artificial neural networks (DNNs) for this problem of parameter recovery from spectra and to also investigate the uncertainty of recovering the fireball parameters from FTIR data. Networks are designed using the hyperparameter optimization tool Hyperopt and trained/tested on artificial data generated using the phenomenological model developed by AFIT. The results of applying the network to the artificial data set are compared to a physics-based band approach that uses a selected number of bands based on their physical properties. Information on the uncertainty of estimating parameters from remotely sensed experimental data is obtained by treating the accuracy of the DNN model on artificial data as an upper bound and by examining the impact of emissivity due to soot on parameter estimation error; the results for artificial data are likely to be optimistic as compared to recovering parameters from experimental data.

42 ENGINEERING↗
DOE OSTI2020

Multichannel spectral estimation in acoustics: A state-space approach

Spectral estimation is a necessary methodology to analyze the frequency content of noisy data sets especially in acoustic applications. Many spectral techniques have evolved starting with the classical Fourier transform methods based on the well-known Wiener-Khintchine relationship relating the covariance-to-spectral density as a transform pair culminating with more elegant model-based parametric techniques that apply prior knowledge of the data to produce a high-resolution spectral estimate. Multichannel spectral representations are a class of both nonparametric, as well as parametric, estimators that provide improved spectral estimates. In any case, classical nonparametric multichannel techniques can provide reasonable estimates when coupled with peak-peaking methods as long as the signal levels are reasonably high. Furthermore, parametric multichannel methods can perform quite well in low signal level environments even when applying simple peak-picking techniques. In this paper, the performance of both nonparametric (periodogram) and parametric (state-space) multichannel spectral estimation methods are investigated when applied to both synthesized noisy structural vibration data as well as data obtained from a sounding rocket flight. It is demonstrated that for the multichannel problem, state-space techniques provide improved performance, offering a parametric alternative compared to classical methods.

42 ENGINEERING↗
DOE OSTI2024

Two-dimensional silk

Despite the promise of silk-based devices, the inherent disorder of native silk limits performance. Here, we report highly ordered two-dimensional silk fibroin (SF) films grown epitaxially on van der Waals (vdW) substrates. Using atomic force microscopy, nano–Fourier transform infrared spectroscopy, and molecular dynamics, we show that the films consist of lamellae of SF molecules that exhibit the same secondary structure as the nanocrystallites of native silk. Increasing the SF concentration results in multilayers that grow either by direct assembly of SF molecules into the lamellae or, at high concentrations, along a two-step pathway beginning with a disordered monolayer that then crystallizes. Scanning Kelvin probe measurements show that these films substantially alter the surface potential; thus, they provide a platform for silk-based electronics on vdW solids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Spectroscopy signatures of electron correlations in a trilayer graphene/hBN moiré superlattice

ABC-stacked trilayer graphene/hexagonal boron nitride moiré superlattice (TLG/hBN) has emerged as a playground for correlated electron physics. Here, we report spectroscopy measurements of dual-gated TLG/hBN using Fourier transform infrared photocurrent spectroscopy. We observed a strong optical transition between moiré minibands that narrows continuously as a bandgap is opened by gating, indicating a reduction of the single-particle bandwidth. At half-filling of the valence flat band, a broad absorption peak emerges at ~18 milli–electron volts, indicating direct optical excitation across an emerging Mott gap. Similar photocurrent spectra are observed in two other correlated insulating states at quarter- and half-filling of the first conduction band. Our findings provide key parameters of the Hubbard model for the understanding of electron correlation in TLG/hBN.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reactive high-spin iron(IV)-oxo sites through dioxygen activation in a metal–organic framework

In nature, nonheme iron enzymes use dioxygen to generate high-spin iron(IV)=O species for a variety of oxygenation reactions. Although synthetic chemists have long sought to mimic this reactivity, the enzyme-like activation of O 2 to form high-spin iron(IV) = O species remains an unrealized goal. Here, we report a metal–organic framework featuring iron(II) sites with a local structure similar to that in α-ketoglutarate-dependent dioxygenases. The framework reacts with O 2 at low temperatures to form high-spin iron(IV) = O species that are characterized using in situ diffuse reflectance infrared Fourier transform, in situ and variable-field Mössbauer, Fe Kβ x-ray emission, and nuclear resonance vibrational spectroscopies. In the presence of O 2 , the framework is competent for catalytic oxygenation of cyclohexane and the stoichiometric conversion of ethane to ethanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗