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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Wavelet transform analysis of the small-scale X-ray structure of the cluster Abell 1367

We have developed a new technique based on a wavelet transform analysis to quantify the small-scale (less than a few arcminutes) X-ray structure of clusters of galaxies. We apply this technique to the ROSAT position sensitive proportional counter (PSPC) and Einstein high-resolution imager (HRI) images of the central region of the cluster Abell 1367 to detect sources embedded within the diffuse intracluster medium. In addition to detecting sources and determining their fluxes and positions, we show that the wavelet analysis allows a characterization of the sources extents. In particular, the wavelet scale at which a given source achieves a maximum signal-to-noise ratio in the wavelet images provides an estimate of the angular extent of the source. To account for the widely varying point response of the ROSAT PSPC as a function of off-axis angle requires a quantitative measurement of the source size and a comparison to a calibration derived from the analysis of a Deep Survey image. Therefore, we assume that each source could be described as an isotropic two-dimensional Gaussian and used the wavelet amplitudes, at different scales, to determine the equivalent Gaussian Full Width Half-Maximum (FWHM) (and its uncertainty) appropriate for each source. In our analysis of the ROSAT PSPC image, we detect 31 X-ray sources above the diffuse cluster emission (within a radius of 24 min), 16 of which are apparently associated with cluster galaxies and two with serendipitous, background quasars. We find that the angular extents of 11 sources exceed the nominal width of the PSPC point-spread function. Four of these extended sources were previously detected by Bechtold et al. (1983) as 1 sec scale features using the Einstein HRI. The same wavelet analysis technique was applied to the Einstein HRI image. We detect 28 sources in the HRI image, of which nine are extended. Eight of the extended sources correspond to sources previously detected by Bechtold et al. Overall, using both the PSPC and the HRI observations, we detect 16 extended features, of which nine have galaxies coincided with the X-ray-measured positions (within the positional error circles). These extended sources have luminosities lying in the range (3 - 30) x 10(exp 40) ergs/s and gas masses of approximately (1 - 30) x 10(exp 9) solar mass, if the X-rays are of thermal origin. We confirm the presence of extended features in A1367 first reported by Bechtold et al. (1983). The nature of these systems remains uncertain. The luminosities are large if the emission is attributed to single galaxies, and several of the extended features have no associated galaxy counterparts. The extended features may be associated with galaxy groups, as suggested by Canizares, Fabbiano, & Trinchieri (1987), although the number required is large.

Grebeney, S. A.↗
DOE OSTI2015

Weak Lensing by Galaxy Clusters: from Pixels to Cosmology

The story of the origin and evolution of our Universe is told, equivalently, by space-time itself and by the structures that grow inside of it. Clusters of galaxies are the frontier of bottom-up structure formation. They are the most massive objects to have collapsed at the present epoch. By that virtue, their abundance and structural parameters are highly sensitive to the composition and evolution of the Universe. The most common probe of cluster cosmology, abundance, uses samples of clusters selected by some observable. Applying a mass-observable relation (MOR), cosmological parameters can be constrained by comparing the sample to predicted cluster abundances as a function of observable and redshift. Arguably, however, cluster probes have not yet entered the era of per cent level precision cosmology. The primary reason for this is our imperfect understanding of the MORs. The overall normalization, the slope of mass vs. observable, the redshift evolution, and the degree and correlation of intrinsic scatters of observables at fixed mass have to be constrained for interpreting abundances correctly. Mass measurement of clusters by means of the differential deflection of light from background sources in their gravitational field, i.e. weak lensing, is a powerful approach for achieving this. This thesis presents new methods for and scientific results of weak lensing measurements of clusters of galaxies. The former include, on the data reduction side, (i) the correction of CCD images for non-linear effects due to the electric fields of accumulated charges and (ii) a method for masking artifact features in sets of overlapping images of the sky by comparison to the median image. Also, (iii) I develop a method for the selection of background galaxy samples based on their color and apparent magnitude that includes a new correction for contamination with cluster member galaxies. The main scientific results are the following. (i) For the Hubble Frontier Field cluster RXC J2248.7--4431 our lensing analysis constrains mass and concentration of the cluster halo and we confirm the large mass predicted by X-ray and Sunyaev-Zel’dovich (SZ) observations. The study of cluster members shows the relation of galaxy morphology to luminosity and environment. (ii) Our lensing mass measurements for 12 clusters are consistent with X-ray masses derived under the assumption of hydrostatic equilibrium of the intra-cluster gas. We confirm the MORs derived by the South Pole Telescope collaboration for the detection significance of the cluster SZ signal in their survey. We find discrepancies, however, with the Planck SZ MOR. We hypothesize that these are related either to a shallower slope of the MOR or a size-, redshift- or noise-dependent bias in SZ signal extraction. (iii) Finally, using a combination of simulations and theoretical models for the variation of cluster profiles at fixed mass, we find that the latter is a significant contribution to the uncertainty of cluster lensing mass measurements. A cosmic variance model, such as the one we develop, is necessary for MOR constraints to be accurate at the level required for future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

THE JCMT GOULD BELT SURVEY: DENSE CORE CLUSTERS IN ORION A

The Orion A molecular cloud is one of the most well-studied nearby star-forming regions, and includes regions of both highly clustered and more dispersed star formation across its full extent. Here, we analyze dense, star-forming cores identified in the 850 and 450 μ m SCUBA-2 maps from the JCMT Gould Belt Legacy Survey. We identify dense cores in a uniform manner across the Orion A cloud and analyze their clustering properties. Using two independent lines of analysis, we find evidence that clusters of dense cores tend to be mass segregated, suggesting that stellar clusters may have some amount of primordial mass segregation already imprinted in them at an early stage. We also demonstrate that the dense core clusters have a tendency to be elongated, perhaps indicating a formation mechanism linked to the filamentary structure within molecular clouds.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Dependence of Cumulus Anvil Radiative Properties on Environmental Conditions in the Tropical West Pacific

Areally extensive, optically thick anvil clouds associated with mesoscale convective clusters dominate the shortwave cloud forcing in the tropics and provide longwave forcing comparable to that of thin cirrus. Changes in the cover and optical thickness of tropical anvils as climate warms can regulate the sign of cloud feedback. As a prelude to the study of MMCR data from the ARM TWP sites, we analyze ISCCP-derived radiative characteristics of anvils observed in the tropical west Pacific during the TOGA-COARE IOP. Anvils with radius greater than 100 km were identified and tracked from inception to decay using the Machado-Rossow algorithm. Corresponding environmental conditions just prior to the start of the convectove event were diagnosed using the Lin-Johnson objective analysis product. Small clusters (100-200 km radius) are observed to have a broad range of optical thicknesses (10-50), while intermediate optical thickness clusters are observed to range in size from 100 km to almost 1000 km. Large-size clusters appear to be favored by strong pre-storm large scale upward motion throughout the troposphere, moist low-to-midlevel relative humidities, environments with slightly higher CAPE than those for smaller clusters, and strong front-to-rear flow. Optically thick anvils are favored in situations of strong low-level moisture convergence and strong upper-level shear.

Ye, B.↗
DOE OSTI2022

The complex structural and chemical nature of monolithic U-10Mo fuel and Zr barrier layer

Nanoscale microstructural characterization by advanced transmission electron microscopy techniques on a U-10Mo/Zr barrier layer monolithic fuel plate was performed to evaluate the microstructural evaluation after high burn-up. Gas bubble superlattice evolution, grain restructuring, and evolution of the Zr interaction layer is investigated through detailed electron microscopy characterization. The use of automated crystallographic orientation mapping to irradiated U-10Mo fuel highlights that the restructured ultra-fine grains are separated by high angle grain boundaries at a burn up of 4.42 × 10 21 fissions/cm 3 . Additionally, advanced chemical analysis and multi-variable statistical analysis shows spatial clustering of solid fission product precipitates. Finally, characterization of a newly observed porous nanocrystalline Zr region in the barrier layer is studied. Finally, this work provides insights into the grain subdivision and restructuring process while using advanced microscopy techniques to analyze fission products in neutron-irradiated U-10Mo fuel.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Neural network acceleration of large-scale structure theory calculations

Here, we make use of neural networks to accelerate the calculation of power spectra required for the analysis of galaxy clustering and weak gravitational lensing data. For modern perturbation theory codes, evaluation time for a single cosmology and redshift can take on the order of two seconds. In combination with the comparable time required to compute linear predictions using a Boltzmann solver, these calculations are the bottleneck for many contemporary large-scale structure analyses. Here, we construct neural network-based surrogate models for Lagrangian perturbation theory (LPT) predictions of matter power spectra, real and redshift space galaxy power spectra, and galaxy-matter cross power spectra that attain ~ 0.1% (at one sigma) accuracy over a broad range of scales in a ωCDM parameter space. The neural network surrogates can be evaluated in approximately one millisecond, a factor of 1000 times faster than the full Boltzmann code and LPT computations. In a simulated full-shape redshift space galaxy power spectrum analysis, we demonstrate that the posteriors obtained using our surrogates are accurate compared to those obtained using the full LPT model. We make our surrogate models public at https://github.com/sfschen/EmulateLSS, so that others may take advantage of the speed gains they provide to enable rapid iteration on analysis settings, something that is essential in complex contemporary large-scale structure analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The evolution of the intracluster medium metallicity in Sunyaev Zel'dovich-selected galaxy clusters at 0 < z < 1.5

Here, we present the results of an X-ray spectral analysis of 153 galaxy clusters observed with the Chandra, XMM-Newton, and Suzaku space telescopes. These clusters, which span 0 < z < 1.5, were drawn from a larger, mass-selected sample of galaxy clusters discovered in the 2500 square degree South Pole Telescope Sunyaev Zel'dovich (SPT-SZ) survey. With a total combined exposure time of 9.1 Ms, these data yield the strongest constraints to date on the evolution of the metal content of the intracluster medium (ICM). We find no evidence for strong evolution in the global (r < R 500 ) ICM metallicity (dZ/dz = –0.06 ± 0.04 Z ⊙), with a mean value at z = 0.6 of $\langle Z\rangle =0.23\pm 0.01$ Z ⊙ and a scatter of σ Z = 0.08 ± 0.01 Z ⊙. These results imply that the emission-weighted metallicity has not changed by more than 40% since z = 1 (at 95% confidence), consistent with the picture of an early (z > 1) enrichment. We find, in agreement with previous works, a significantly higher mean value for the metallicity in the centers of cool core clusters versus non-cool core clusters. We find weak evidence for evolution in the central metallicity of cool core clusters (dZ/dz = –0.21 ± 0.11 Z ⊙), which is sufficient to account for this enhanced central metallicity over the past ~10 Gyr. We find no evidence for metallicity evolution outside of the core (dZ/dz = –0.03 ± 0.06 Z ⊙), and no significant difference in the core-excised metallicity between cool core and non-cool core clusters. This suggests that strong radio-mode active galactic nucleus feedback does not significantly alter the distribution of metals at $r\gt 0.15{R}_{500}$. Given the limitations of current-generation X-ray telescopes in constraining the ICM metallicity at z > 1, significant improvements on this work will likely require next-generation X-ray missions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE OPTICAL COUNTERPART TO THE X-RAY TRANSIENT IGR J1824-24525 IN THE GLOBULAR CLUSTER M28

We report on the identification of the optical counterpart to the recently detected INTEGRAL transient IGR J1824-24525 in the Galactic globular cluster M28. From analysis of a multi-epoch Hubble Space Telescope data set, we have identified a strongly variable star positionally coincident with the radio and Chandra X-ray sources associated with the INTEGRAL transient. The star has been detected during both a quiescent and an outburst state. In the former case it appears as a faint, unperturbed main-sequence star, while in the latter state it is about two magnitudes brighter and slightly bluer than main-sequence stars. We also detected H{alpha} excess during the outburst state, suggestive of active accretion processes by the neutron star.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A Clustering Graph Generator

In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps to understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Cosmology with stacked cluster weak lensing and cluster–galaxy cross-correlations

ABSTRACT Cluster weak lensing is a sensitive probe of cosmology, particularly the amplitude of matter clustering σ8 and matter density parameter Ωm. The main nuisance parameter in a cluster weak lensing cosmological analysis is the scatter between the true halo mass and the relevant cluster observable, denoted $\sigma _{\ln M_\mathrm{ c}}$. We show that combining the cluster weak lensing observable ΔΣ with the projected cluster–galaxy cross-correlation function wp,cg and galaxy autocorrelation function wp,gg can break the degeneracy between σ8 and $\sigma _{\ln M_\mathrm{ c}}$ to achieve tight, per cent-level constraints on σ8. Using a grid of cosmological N-body simulations, we compute derivatives of ΔΣ, wp,cg, and wp,gg with respect to σ8, Ωm, $\sigma _{\ln M_\mathrm{ c}}$, and halo occupation distribution (HOD) parameters describing the galaxy population. We also compute covariance matrices motivated by the properties of the Dark Energy Survey cluster and weak lensing survey and the BOSS CMASS galaxy redshift survey. For our fiducial scenario combining ΔΣ, wp,cg, and wp,gg measured over 0.3−30.0 h−1 Mpc, for clusters at z = 0.35−0.55 above a mass threshold Mc ≈ 2 × 1014 h−1 M⊙, we forecast a $1.4{{\ \rm per\ cent}}$ constraint on σ8 while marginalizing over $\sigma _{\ln M_\mathrm{ c}}$ and all HOD parameters. Reducing the mass threshold to 1 × 1014 h−1 M⊙ and adding a z = 0.15−0.35 redshift bin sharpens this constraint to $0.8{{\ \rm per\ cent}}$. The small-scale (rp < 3.0 h−1 Mpc) ‘mass function’ and large-scale (rp > 3.0 h−1 Mpc) ‘halo-mass cross-correlation’ regimes of ΔΣ have comparable constraining power, allowing internal consistency tests from such an analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Solving the structure of “single-atom” catalysts using machine learning – assisted XANES analysis

We show that "single-atom” catalysts (SACs) have demonstrated excellent activity and selectivity in challenging chemical transformations such as photocatalytic CO 2 reduction. For heterogeneous photocatalytic SAC systems, it is essential to obtain sufficient information of their structure at the atomic level in order to understand reaction mechanisms. In this work, a SAC was prepared by grafting a molecular cobalt catalyst on a light-absorbing carbon nitride surface. Due to the sensitivity of the X-ray absorption near edge structure (XANES) spectra to subtle variances in the Co SAC structure in reaction conditions, different machine learning (ML) methods, including principal component analysis, K-means clustering, and neural network (NN), were utilized for in situ Co XANES data analysis. As a result, we obtained quantitative structural information of the SAC nearest atomic environment thereby extending the NN-XANES approach previously demonstrated for nanoparticles and size-selective clusters.

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

Application of prophage sequence analysis to investigate a disease outbreak involving Salmonella Adjame, a rare serovar and implications for the population structure

Introduction Outbreak investigation of foodborne salmonellosis is hindered when the food source is contaminated by multiple strains of Salmonella , creating difficulties matching an incriminated organism recovered from patients with the specific strain in the suspect food. An outbreak of the rare Salmonella Adjame was caused by multiple strains of the organism as revealed by single-nucleotide polymorphism (SNP) variation. The use of highly discriminatory prophage analysis to characterize strains of Salmonella should enable a more precise strain characterization and aid the investigation of foodborne salmonellosis. Methods We have carried out genomic analysis of S. Adjame strains recovered during the course of a recent outbreak and compared them with other strains of the organism ( n = 38 strains), using SNPs to evaluate strain differences present in the core genome, and prophage sequence typing (PST) to evaluate the accessory genome. Phylogenetic analyses were performed using both total prophage content and conserved prophages. Results The PST analysis of the S. Adjame isolates showed a high degree of strain heterogeneity. We observed small clusters made up of 2-6 isolates ( n = 27) and singletons ( n = 11) in stark contrast with the three clusters observed by SNP analysis. In total, we detected 24 prophages of which only four were highly prevalent, namely: Entero_p88 (36/38 strains), Salmon_SEN34 (35/38 strains), Burkho_phiE255 (33/38 strains) and Edward_GF (28/38 strains). Despite the marked strain diversity seen with prophage analysis, the distribution of the four most common prophages matched the clustering observed using core genome. Discussion Mutations in the core and accessory genomes of S. Adjame have shed light on the evolutionary relationships among the Adjame strains and demonstrated a convergence of the variations observed in both fractions of the genome. We conclude that core and accessory genomes analyses should be adopted in foodborne bacteria outbreak investigations to provide a more accurate strain description and facilitate reliable matching of isolates from patients and incriminated food sources. The outcomes should translate to a better understanding of the microbial population structure and an 46 improved source attribution in foodborne illnesses.

Gao, Ruimin↗
DOE OSTI2020

Metabolic Pathway Engineering

Modern microbial and enzyme engineering and their advancement are increasingly dependent on the marriage of a wide range of sophisticated technologies. For students entering the field of biotechnology, the outlook is indeed daunting. Expertise at levels beyond that of simple familiarity will be needed to conduct competitive research. It goes without saying that to be competitive, all new researchers in this field will need basic preparation in molecular biology, biochemistry, and genetics. Further, experience working with concepts and experimental tools in enzyme biochemistry and kinetics, gene editing, computational metabolic pathway modeling, experimental pathway flux analysis, and computational clustering tools to process complex data sets will be vital for success. We speculate that most biotechnology researchers in early career at this time will build teams of collaborators to address these disparate science fields rather than attempt to become experts in one lab.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2022

High-throughput investigation of structural evolution upon solid-state in Cu–Cr–Co combinatorial multilayer thin-film

Cu-Cr-Co combinatorial multilayer thin-films were prepared by a high-throughput ion beam sputtering system. Based on the thickness ratio among the individual nanoscale monolayers (Cu, Cr, Co), the resulting stoichiometry covered the entire phase diagram. The chemical composition and structure of Cu-Cr-Co combinatorial chip upon solid-state reaction were studied by lab-based micro-X-ray fluorescence (mu-XRF) and high-throughput synchrotron X-ray diffraction (XRD), respectively. A composition-structure map for Cu-Cr-Co combinatorial chip was developed through automated data analysis employing hierarchical clustering techniques. The structural evolution of Cu-Cr-Co combinatorial chip as a function of heat-treatment temperature, time, and modulation period were studied systematically. Furthermore, the effect of the elemental distribution in-depth direction was investigated to gain more insights regarding phase transformation. This work provides an efficient method and new perspectives for the design and optimization of the composition and structure of high-performance thin-films.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Actin cytoskeleton organization, cell surface modification and invasion rate of 5 glioblastoma cell lines differing in PTEN and p53 status

Glioblastoma cells exhibit highly invasive behavior whose mechanisms are not yet fully understood. The present study explores the relationship between the invasion capacity of 5 glioblastoma cell lines differing in p53 and PTEN status, expression of mTOR and several other marker proteins involved in cell invasion, actin cytoskeleton organization and cell morphology. We found that two glioblastoma lines mutated in both p53 and PTEN genes (U373-MG and SNB19) exhibited the highest invasion rates through the Matrigel or collagen matrix. In DK-MG (p53wt/PTENwt) and GaMG (p53mut/PTENwt) cells, F-actin mainly occurred in the numerous stress fibers spanning the cytoplasm, whereas U87-MG (p53wt/PTENmut), U373-MG and SNB19 (both p53mut/PTENmut) cells preferentially expressed F-actin in filopodia and lamellipodia. Scanning electron microscopy confirmed the abundant filopodia and lamellipodia in the PTEN mutated cell lines. Interestingly, the gene profiling analysis revealed two clusters of cell lines, corresponding to the most (U373-MG and SNB19, i.e. p53 and PTEN mutated cells) and less invasive phenotypes. The results of this study might shed new light on the mechanisms of glioblastoma invasion. - Highlights: • We examine 5 glioblastoma lines on the invasion capacity and actin cytoskeleton. • Glioblastoma cell lines mutated in both p53 and PTEN were the most invasive. • Less invasive cells showed much less lamellipodia, but more actin stress fibers. • A mechanism for the differences in tumor cell invasion is proposed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Classical Optimal Control for Energy Minimization Based On Diffeomorphic Modulation under Observable-Response-Preserving Homotopy

In this work, we introduce the so-called “Classical Optimal Control Optimization” (COCO) method for global energy minimization based on the implementation of the diffeomorphic modulation under observable-response-preserving homotopy (DMORPH) gradient algorithm. A probe particle with time-dependent mass $m(t;β)$ and dipole $μ(r,t;β)$ is evolved classically on the potential energy surface $V(r)$ coupled to an electric field $E(t;β)$, as described by the time-dependent density of states represented on a grid, or otherwise as a linear combination of Gaussians generated by the k-means clustering algorithm. Control parameters $β$ defining $m(t;β), μ(r,t;β),$ and $E(t;β)$ are optimized by following the gradients of the energy with respect to $β,$ adapting them to steer the particle toward the global minimum energy configuration. We find that the resulting COCO algorithm is capable of resolving near-degenerate states separated by large energy barriers and successfully locates the global minima of golf potentials on flat and rugged surfaces, previously explored for testing quantum annealing methodologies and the quantum optimal control optimization (QuOCO) method. Preliminary results show successful energy minimization of multidimensional Lennard-Jones clusters. Beyond the analysis of energy minimization in the specific model systems investigated, we anticipate COCO should be valuable for solving minimization problems in general, including optimization of parameters in applications to machine learning and molecular structure determination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Identifying the Unique Properties of α-Bi 2 Mo 3 O 12 for the Activation of Propene

In order to understand the remarkable activity of α-Bi 2 Mo 3 O 12 for selective oxidation and ammoxidation of propene, the propene activation ability of four molybdenum-based mixed metal oxides - Bi 2 Mo 3 O 12 , PbMoO 4 , Bi 2 Pb 5 Mo 8 O 32 , and MoO 3 - was investigated using density functional theory. Propene activation is considered to occur via abstraction of a hydrogen atom from the methyl group of physisorbed propene by lattice oxygen. For each material, the apparent activation energy was estimated by summing the heat of adsorption of propene, the C-H bond dissociation energy, and the hydrogen attachment energy (HAE) for hydrogen addition to lattice oxygen; this sum provides a lower bound for the apparent activation energy. It was found that two structural features of oxide surfaces are essential to achieve low activation barriers: under-coordinated surface cation sites enable strong propene adsorption, and suitable 5- or 6-coordinate geometries at molybdenum result in favorable HAEs. The impact of molybdenum coordination on HAE was elucidated by carrying out a molecular orbital analysis using a cluster model of the molybdate unit. This effort revealed that, in 5- and 6-coordinate molybdates, oxygen donor atoms trans to molybdenyl oxo atoms destabilize the molybdate prior to H addition but stabilize the molybdate after H addition, thereby providing an HAE ~15 kcal/mol more favorable than that on 4-coordinate molybdate oxo atoms. Bi 3+ cations in Bi 2 Mo 3 O 12 thus promote catalytic activity by providing both strong adsorption sites for propene and forcing molybdate into 5-coordinate geometries that lead to particularly favorable values of the HAE. (Graph Presented).

36 MATERIALS SCIENCE↗