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At least 181 records · Page 10

Journey to Time-Variable Moment Tensors through Inversion of Acoustic and Seismoacoustic Data

We explore the capability of acoustic and seismoacoustic datasets to directly resolve a complex, time-variable source consisting of a buried mechanism, represented as a moment tensor, and a spall mechanism, represented as a vertical force at the surface. Traditionally, each component of a resolved moment tensor assumes one underlying source time function, which likely fails to capture the full evolution of a dynamic source, such as an explosion followed by slip on near-source joints or development of spallation. Specifically, we expand previous work to resolve a time-variable moment tensor using single-modality and joint-modality inversion frameworks through analysis of infrasound and seismoacoustic data recorded as part of the Source Physics Experiment Phase II: Dry Alluvium Geology (DAG). We investigate the impact of including signals from seismic-to-air coupling that are local to each infrasound sensor in comparison to mainly atmosphere-propagating acoustic signals, which occur from coupling of the wavefield from the subsurface to the atmosphere directly above the source. Additionally, we assess the ability of our inversion algorithm to fit observed infrasound data using a variety of time-variable source mechanisms. First, we consider the buried moment tensor source alone, which assumes that the determined Green’s functions incorporate effects from spallation or that the impact from spallation is minimal. Second, we examine the estimated buried moment tensor and vertical surface spallation as terms that must both be resolved in the inversion. Third, we assess the ability for an estimated vertical surface spallation source to fit the acoustic data on its own. Finally, we compare results from the joint inversion of both seismic geophone and infrasound acoustic data for the buried-only source compared to buried and spallation sources. Our results are a preliminary investigation into the applications of the inversion technique to recorded datasets and show the technique has limited capabilities using acoustic data alone. Instead, this method shows promise for seismic and seismoacoustic datasets to resolve the time-variable mechanisms of a buried source.

47 OTHER INSTRUMENTATION↗

Generalized Analysis of Dynamic Flow Fouling on Heat Transfer Surfaces

Several energy applications involve flow of untreated heat transfer fluids that contain trace amounts of mineral salts, such as calcium carbonate and calcium sulfate, which show reverse solubility with temperature. The gradual accretion of these salts onto the heat transfer surfaces causes fouling that degrades thermal performance over time. While fouling of bare surfaces has been extensively studied, fouling of nonwetting superhydrophobic or liquid-infused surfaces is less understood, especially under dynamic flow conditions. This study presents a systematic experimental analysis to elucidate dynamic flow fouling of calcium carbonate and calcium sulfate on smooth, superhydrophobic and liquid-infused surfaces in a generalized manner. Here, copper tubes with modified inner surface wettability are fabricated and subjected to forced convection at different flow rates and fouling salt concentrations. Fouling characteristics of the two salts on the different surfaces are examined through microstructural analysis, and quantified in terms of asymptotic fouling resistance that measures the total extent of fouling, and a threshold time, which correlates to the onset of significant fouling. Using Taguchi design of experiments, the study reports, for the first time, closed-form analytical relationships for the asymptotic fouling thermal resistance and threshold time on the Reynolds number, dimensionless concentration of fouling agent and dimensionless infused liquid viscosity that represents the different surface types in a unified manner. It is shown that the analytical model accurately predicts the fouling characteristics in up to about 97% of the data, based on which contour maps of optimum surface designs for minimizing fouling resistance are presented. The results provide information on designing surfaces for reduced fouling or for estimating the fouling characteristics for a given surface in applications.

36 MATERIALS SCIENCE↗

A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

Stochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. One form of reduced model, the linear inverse model (LIM), has been widely used for regional climate predictability studies—typically focusing more on tropical or midlatitude studies. However, most LIM fitting techniques rely on point estimation techniques deriving from fluctuation–dissipation theory. In this methodological study we explore the use of Bayesian inference techniques for LIM parameter estimation of sea surface temperature (SST), to quantify the skillful decadal predictability of Bayesian LIM models at high latitudes. We show that Bayesian methods, when compared to traditional point estimation methods for LIM-type models, provide better calibrated probabilistic skill, while simultaneously providing better point estimates due to the regularization effect of the prior distribution in high-dimensional problems. We compare the effect of several priors, as well as maximum likelihood estimates, on 1) estimating parameter values on a perfect model experiment and 2) producing calibrated 1-yr SST anomaly forecast distributions using a preindustrial control run of the Community Earth System Model (CESM). Finally, we employ a host of probabilistic skill metrics to determine the extent to which an LIM can forecast SST anomalies at high latitudes. We find that the choice of prior distribution has an appreciable impact on estimation outcomes, and priors that emphasize physically relevant properties enhance the model’s ability to capture variability of SST anomalies.

54 ENVIRONMENTAL SCIENCES↗

Code for paper "Reconstructing an Implosion with Space-Time Smoothing of Velocimetry Traces"

New diagnostics to obtain high-temporal resolution observation of surface velocity provide a rich collection of data from high-explosive (HE) experiments. Using this data to estimate the temporal evolution of an imploding, HE-driven surface is of great interest for validating simulation of the physical system and for design of future experiments. This is the code for a paper in which we propose a method for using a Gaussian process to estimate the surface position over time and provide uncertainty estimates on that reconstruction accounting for measurement error, uncertainty to sparse spatial sampling velocity data, and robustness to outlying observations. In the paper, the code is applied on data from a hemispherical HE implosion experiment. This code is for release with the paper for peer-review, replicating the results and making the figures from the paper.

Grosskopf, Michael↗

Snow thermal conductivity and conductive flux in the Central Arctic: Estimates from observations and implications for models

During the Arctic winter, the conductive heat flux through the sea ice and snow balances the radiative and turbulent heat fluxes at the surface. Snow on sea ice is a thermal insulator that reduces the magnitude of the conductive flux. The thermal conductivity of snow, that is, how readily energy is conducted, is known to vary significantly in time and space from observations, but most forecast and climate models use a constant value. This work begins with a demonstration of the importance of snow thermal conductivity in a regional coupled forecast model. Varying snow thermal conductivity impacts the magnitudes of all surface fluxes, not just conduction, and their responses to atmospheric forcing. Given the importance of snow thermal conductivity in models, we use observations from sea ice mass balance buoys installed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition to derive the profiles of thermal conductivity, density, and conductive flux. From 13 sites, median snow thermal conductivity ranges from 0.33 W m −1 K −1 to 0.47 W m −1 K −1 with a median from all data of 0.39 W m −1 K −1 from October to February. In terms of surface energy budget closure, estimated conductive fluxes are generally smaller than the net atmospheric flux by as much as 20 W m −2 , but the average residual during winter is −6 W m −2 , which is within the uncertainties. The spatial variability of conductive heat flux is highest during clear and cold time periods. Higher surface temperature, which often occurs during cloudy conditions, and thicker snowpacks reduce temporal and spatial variability. These relationships are compared between observations and the coupled forecast model, emphasizing both the importance and challenge of describing thermodynamic parameters of snow cover for modeling the Arctic as a coupled system.

54 ENVIRONMENTAL SCIENCES↗

The impact of multi-sensor land data assimilation on river discharge estimation

River discharge is one of the most critical renewable water resources. Accurately estimating river discharge with land surface models (LSMs) remains challenging due to the difficulty in estimating land water storages such as snow, soil moisture, and groundwater. While data assimilation (DA) ingesting optical, microwave, and gravity measurements from space can help constrain theses storage states, its impacts on runoff and eventually river discharge are not fully understood. In this study, by taking advantage of recently published land DA results that jointly assimilate eight different combinations of observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), Gravity Recovery and Climate Experiment (GRACE), and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), we quantify to what degree multi-sensor land DA improves the river discharge simulation skills over 40 global river basins, and investigate the complementary strengths of different satellite measurements on river discharge. To be more specific, river discharge is updated by feeding gridded runoff from the eight multi-sensor DA simulations into a vector-based river routing model named the Routing Application for Parallel computatIon of Discharge (RAPID). Our modeling results, including 7-year simulations at 177,458 river reaches globally, are used to study the seasonal to interannual variability of river discharge. It is found that assimilating GRACE has the greatest impact on global runoff patterns, leading to the most pronounced improvements in spatial river discharge in the middle and high latitudes with the R 2 increased by 0.16. The seasonal variation of spatial discharge is most skillful during the boreal summer. However, our evaluation also shows model and DA still struggle to generate reasonable variability and averaged discharge over permafrost regions. Finally, by assessing how different satellites add value to discharge forecasts, this study paves the way for more advanced multi-sensor satellite data assimilation to predict the terrestrial hydrological cycle.

54 ENVIRONMENTAL SCIENCES↗

Dissolution of Fluoride Salts in Hanford Tank Waste

The Direct Feed High-Level Waste (DFHLW) strategy seeks to bypass the Hanford Waste Treatment and Immobilization Plant Pretreatment Facility while retaining some processing functions to maximize waste feed loading and minimize high-level waste (HLW) waste volume. The DFHLW flowsheet needs leaching, washing, and solids concentration operations either in new or existing tanks. The effectiveness and efficiency of sludge washing has a substantial impact on DST space, mission duration, and the evaporation and low-activity waste (LAW) treatment operations required by these large wash-water additions. One target species requiring washing is fluoride. The HLW glass composition limits for fluorine drive operations to dissolve fluoride-bearing salts into the LAW fraction and thereby maximize waste loading in HLW glass. The fluoride in many high-level wastes at Hanford is predominantly in the form of fluoride-salt precipitates: villiaumite (NaF), kogarkoite (Na 3 FSO 4 ), and natrophosphate (Na 7 F(PO 4 ) 2 ·19H 2 O). Fluoride produces melter off-gas that creates corrosion risk in the off-gas system piping, while the sulfate and phosphate in the fluoride double salts kogarkoite and natrophosphate can be detrimental to glass waste loading. Fluoride salts are sparingly soluble, with solubilities ranging from approximately 40 to 130 kg per kL of pure water, and the dissolution kinetics of the three fluoride salts are not well known. Unexpected delays in a tank dissolution process could be encountered as a result of the lack of information about dissolution rates. In addition, if the double salts show transient non-stoichiometric dissolution of fluoride versus phosphate or sulfate, unexpectedly high concentrations of one of these other constituents could be produced. Washington River Protection Solutions authorized Pacific Northwest National Laboratory to collect the available data for fluoride salt dissolution rate, provide a scoping estimate of dissolution time if possible, and identify gaps in the understanding and predictive capability for estimating dissolution time. Open literature and Hanford reports were reviewed to document, understand, and (where possible) evaluate limitations on fluoride salt equilibria and dissolution kinetics, including both mass transport and surface reaction rate. Scoping estimates of dissolution time were made for mass-transfer-controlled dissolution of spherical particles of fluoride salts suspended in liquid. This is not the only potential governing mechanism; dissolution could be substantially slower if the surface reaction rate (the rate of release of ions from the surface) is the controlling mechanism. When the minimum amount of water for complete dissolution is used and the slip velocity between the liquid and suspended particles is less than or equal to the terminal settling velocity, the estimated mass-transfer rates allow 0.1 mm particles of fluoride salt to dissolve in minutes at 25 °C in water containing no other dissolved salts. Much larger solids, such as the 6-mm chunks that have been seen in heels, could take a few hours to more than a week to dissolve. The actual dissolution times will depend strongly on the actual slip velocity, the extent of particle suspension, constraint by surface reaction rates, the ratio of solvent to solid, and the presence of common ions that shift the solubility equilibria to restrict dissolution of fluoride salts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Comparison of planetary boundary layer height from ceilometer with ARM radiosonde data

Abstract. Ceilometer measurements of aerosol backscatter profiles have been widely used to provide continuous planetary boundary layer height (PBLHT) estimations. To investigate the robustness of ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using multiple years of U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) ceilometer and balloon-borne sounding data at ARM fixed-location atmospheric observatories and from ARM mobile facilities deployed around the world for various field campaigns. These observatories cover from the tropics to the polar regions and over both ocean and land surfaces. Statistical comparisons of ceilometer-estimated PBLHTs from the Vaisala CL31 ceilometer data with radiosonde-estimated PBLHTs from the ARM PBLHT-SONDE Value-added Product (VAP) are performed under different atmospheric conditions including stable and unstable atmospheric boundary layer, low-level cloud-free conditions, and cloudy conditions at these ARM observatories. Under unstable conditions, good comparisons are found between ceilometer- and radiosonde-estimated PBLHTs at ARM low- and mid-latitude land observatories. However, it is still challenging to obtain reliable PBLHT estimations over ocean surfaces even using radiosonde data. Under stable conditions, ceilometer- and radiosonde-estimated PBLHTs have weak correlations. We compare different PBLHT estimations utilizing the Heffter, the Liu–Liang, and the bulk Richardson number methods applied to radiosonde data with ceilometer-estimated PBLHT. We find that ceilometer-estimated PBLHT compares better with the Liu–Liang method under unstable conditions and compares better with the bulk Richardson number method under stable conditions.

54 ENVIRONMENTAL SCIENCES↗

Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps

Abstract An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations (e.g., lidar) have emerged as a promising method to accurately quantify SWE at high resolutions (scales of ∼100 m and finer). However, the frequency of these observations is very low, typically once or twice per season in the Rocky Mountains of Colorado. Here, we present a machine learning framework that is based on random forests to model temporally sparse lidar-derived SWE, enabling estimation of SWE at unmapped time points. We approximated the physical processes governing snow accumulation and melt as well as snow characteristics by obtaining 15 different variables from gridded estimates of precipitation, temperature, surface reflectance, elevation, and canopy. Results showed that, in the Rocky Mountains of Colorado, our framework is capable of modeling SWE with a higher accuracy when compared with estimates generated by the Snow Data Assimilation System (SNODAS). The mean value of the coefficient of determination R 2 using our approach was 0.57, and the root-mean-square error (RMSE) was 13 cm, which was a significant improvement over SNODAS (mean R 2 = 0.13; RMSE = 20 cm). We explored the relative importance of the input variables and observed that, at the spatial resolution of 800 m, meteorological variables are more important drivers of predictive accuracy than surface variables that characterize the properties of snow on the ground. This research provides a framework to expand the applicability of lidar-derived SWE to unmapped time points. Significance Statement Snowpack is the main source of freshwater for close to 2 billion people globally and needs to be estimated accurately. Mountainous snowpack is highly variable and is challenging to quantify. Recently, lidar technology has been employed to observe snow in great detail, but it is costly and can only be used sparingly. To counter that, we use machine learning to estimate snowpack when lidar data are not available. We approximate the processes that govern snowpack by incorporating meteorological and satellite data. We found that variables associated with precipitation and temperature have more predictive power than variables that characterize snowpack properties. Our work helps to improve snowpack estimation, which is critical for sustainable management of water resources.

54 ENVIRONMENTAL SCIENCES↗

A Gradient Based Subgrid-Scale Parameterization for Ocean Mesoscale Eddies

Mesoscale eddies play an important role in transport of heat and biogeochemical tracers in the global ocean circulation. Resolving these energetic eddies, however, is challenging in ocean general circulation models (OGCM) because it requires a horizontal grid spacing of ≲1/8° that is computationally expensive. As a result, we are required to parameterize mesoscale eddy effects on large-scale ocean flows. In this work, we introduce a new subgrid-scale (SGS) model that is developed based on a Taylor series expansion of resolved variables to parameterize subgrid mesoscale eddy transports and momentum fluxes in OGCM. We have performed an a priori study to evaluate the performance of our new gradient model using high-resolution ocean simulations. Our results show that the gradient model well predicts the actual SGS thickness fluxes in the zonal and meridional directions in coarse-resolution simulations with the grid spacing ≳1/4°. The unresolved kinetic energy at the ocean surface is also skillfully estimated. More importantly, unlike current mesoscale eddy parameterizations, which are mainly developed based on an assumption of flat bottom ocean, our new SGS model can capture the structure of unresolved standing meanders at the ocean surface. We have also developed a dynamic procedure for setting in non-dimensional parameters in our new parameterization through a non-ad hoc and tuning-free method. Overall, this work suggests that implementing the gradient model in OGCM can improve the model accuracy with an affordable computational cost in eddy-permitting and non-eddying simulations.

54 ENVIRONMENTAL SCIENCES↗

Urbanization exacerbates continental- to regional-scale warming

Urbanization is usually ignored when estimating past changes in large-scale climate and for future climate projections since cities historically covered a small fraction of the Earth’s surface. Here, by combining global land surface temperature observations with historical estimates of urban area, we demonstrate that the urban contribution to continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions and countries in Asia. Consequently, expected urban expansion over the next century suggests further increased urban influence on large-scale surface climate in the future (approximately 0.16 K for North America and Europe for high-emission scenario in 2100). Based on these results, also seen for air temperature, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in climate change assessments. This requires incorporation of dynamic urban extent and biophysics in current-generation Earth system models to quantify potential urban feedback on the climate system across scales.

Chakraborty, TC↗

In-situ coating of silicon-rich films on tokamak plasma-facing components with real-time Si material injection

Abstract Experiments have been conducted in the DIII-D tokamak to explore the in-situ growth of silicon-rich layers as a potential technique for real-time replenishment of surface coatings on plasma-facing components (PFCs) during steady-state long-pulse reactor operation. Silicon (Si) pellets of 1 mm diameter were injected into low- and high-confinement (L-mode and H-mode) plasma discharges with densities ranging from 3.9– 7.5 × 10 19 m −3 and input powers ranging from 5.5 to 9 MW. The small Si pellets were delivered with the impurity granule injector at frequencies ranging from 4 to 16 Hz corresponding to mass flow rates of 5–19 mg s −1 (1– 4.2 × 10 20 Si s −1 ) at cumulative amounts of up to 34 mg of Si per five-second discharge. Graphite samples were exposed to the scrape-off layer and private flux region plasmas through the divertor material evaluation system to evaluate the Si deposition on the divertor targets. The Si II emission at the sample correlates with silicon injection and suggests net surface Si-deposition in measurable amounts. Post-mortem analysis showed Si-rich coatings containing silicon oxides, of which SiO 2 is the dominant component. No evidence of SiC was found, which is attributed to low divertor surface temperatures. The in-situ and ex-situ analysis found that Si-rich coatings of at least 0.4–1.2 nm thickness have been deposited at 0.4–0.7 nm s −1 . The technique is estimated to coat a surface area of at least 0.94 m 2 on the outer divertor. These results demonstrate the potential of using real-time material injection to form Si-enriched layers on divertor PFCs during reactor operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Characterizing Spatial and Temporal Variability of California’s Coastal Upwelling Using a Satellite-Derived CUTI Index

Ocean upwelling off California is a wind-driven coastal process with complex interactions between spatial wind patterns and sea surface temperatures. Large-scale spatial and temporal upwelling characterizations are traditionally based on numerical models, while quantifying upwelling with direct observations is not straightforward. To complement model-based upwelling characterizations, here we use satellite estimates of winds, sea surface temperatures, and ocean currents along the California coast to calculate the coastal upwelling transport index (CUTI), originally calculated from a numerical ocean model. The CUTI framework accounts for both Ekman and geostrophic offshore-directed ocean transport, the latter of which is often neglected in satellite-based upwelling assessments. The approach yields the CUTI over a 30-yr period at a daily temporal and 0.25° spatial resolution to analyze upwelling patterns, with focus on potential Morro Bay and Humboldt wind energy areas. Morro Bay (CUTI median of 0.63 m 2 s −1 ) exhibits stronger, more consistent upwelling throughout the year, whereas Humboldt (CUTI median of 0.45 m 2 s −1 ) exhibits a pronounced seasonal cycle with strongest upwelling in the summer and occasional downwelling in winter. The cluster analysis of 1993–2022 satellite maps of CUTI identifies four characteristic spatial upwelling patterns along the coast, corresponding to distinct spatial distributions of sea surface temperature anomalies, Ekman transport, and geostrophic ocean water transport. This dataset provides an observation-based foundation for characterizing natural coastal upwelling off the California coast, showing good agreement with the original model CUTI while being based on satellite data and offering increased spatial resolution.

16 TIDAL AND WAVE POWER↗

Calibrating radar wind profiler reflectivity factor using surface disdrometer observations

Abstract. This study uses surface disdrometer reflectivity factor estimates to calibrate the vertical and off-vertical pointing radar beams produced by an ultra high frequency (UHF) band radar wind profiler (RWP) deployed at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) Central Facility in northern Oklahoma from April 2011 through July 2019. The methodology consists of five steps. First, the recorded Doppler velocity power spectra are adjusted to account for Nyquist velocity aliasing and coherent integration filtering effects. Second, the spectrum moments are calculated. The third step increases the signal-to-noise ratio (SNR) due to inflated noise power estimates during convective rain events that cause SNR to be biased low. The fourth step determines the RWP calibration constant for one radar beam (called the “reference” beam) by comparing uncalibrated RWP reflectivity factors at 500 m above the ground to 1 min resolution surface disdrometer reflectivity factors. The last step uses the calibrated reference beam reflectivity factor to calibrate the other radar beams during precipitation. There are two key findings. The RWP sensitivity decreased by approximately 3 to 4 dB yr−1 as the hardware aged. This drift was slow enough that the reference calibration constant can be estimated over 3-month intervals using episodic rain events. The calibrated moments are available on the DOE ARM data archive, and the Python processing code is available on public repositories.

54 ENVIRONMENTAL SCIENCES↗

Comprehensive study of radon progeny attachment to surfaces

Low energy, low rate experiments, such as searches for neutrinoless double β decay and dark matter, require unprecedentedly low levels of background in order to deliver their full science potential. 210 Po driven, neutron induced background, caused by nuclear (α, n) reactions on low-Z materials, direct background contributions of the 210 Po α radiation and desorption of the 210 Pb progeny 210 Bi from surfaces into the detector medium are of particular of concern. These backgrounds depend on details of the components’ exposure to radon-loaded laboratory air and, thus, their handling history. The attachment rates of airborne radon progeny to surfaces, needed for the estimation of these background rates, are poorly understood. This article reports the results of a campaign comprising of more than 1200 attachment measurements, performed for nine different materials. Correlations of the attachment with environmental parameters such as air exchange rate, electrical surface potential, temperature, atmospheric pressure, and relative humidity have been studied and found to be significant only in case of the first two. Attachment modeling, using the Jacobi model, is compared to data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Activation of propane on Ag–PdO(101) model surfaces

Oxidation of alkanes remains a central challenge in catalysis due to the high activation barriers of C–H bonds and the thermodynamic favorability of complete oxidation. Palladium oxide (PdO), particularly its (101) facet, is known for its high reactivity in alkane oxidation, which is attributed to its coordinatively unsaturated palladium (Pd) and O atoms. In this study, we investigate the effect of silver (Ag) incorporation on the oxidation behavior of propane over PdO(101) using temperature-programmed reaction spectroscopy (TPRS) under controlled conditions. While pristine PdO(101) exhibits complete oxidation of propane with CO₂ and H₂O desorption at high temperatures (approximately 475 K), Ag incorporation induces a new CO₂ desorption peak at significantly lower temperatures (approximately 330 K). This shift is attributed to the formation of new active sites at the Ag–PdO(101) interface. Quantitative analysis reveals that low-temperature activity correlates with Ag coverage, while overall CO₂ production decreases, suggesting a redistribution of reactivity rather than an increase in active surface area. Activation energy estimations using the Redhead method confirm that C–H bond activation becomes more facile at the interface, with a 46 kJ/mol reduction compared to pristine PdO(101). These findings demonstrate that incorporating a less reactive metal such as Ag into PdO surfaces not only modifies the reaction energetics but also enables the design of bimetallic catalysts with improved selectivity for partial oxidation reactions.

Chemistry↗