Nanoparticles on surfaces are ubiquitous in nanotechnologies, especially in catalysis, where metal nanoparticles anchored to oxide supports are widely used to produce and use fuels and chemicals, and in pollution abatement. We show that for hemispherical metal particles of the same diameter, D, the chemical potentials of the metal atoms in the particles (μ) differ between two supports by approximately -2(E - E)V/D, where E is the adhesion energy between the metal and support i, and V is the molar volume of the bulk metal. This is consistent with calorimetric measurements of metal vapor adsorption energies onto clean oxide surfaces where the metal grows as 3D particles, which proved that μ increases with decreasing particle size below 6 nm and, for a given size, decreases with E. Since catalytic activity and sintering rates correlate with metal chemical potential, it is thus crucial to understand what properties of catalyst materials control metal/oxide adhesion energies. Trends in how E varies with the metal and the support oxide are presented. For a given oxide, E increases linearly from metal to metal with increasing heat of formation of the most stable oxide of the metal (per mole metal), or metal oxophilicity, suggesting that metal-oxygen bonds dominate interfacial bonding. For the two different stoichiometric oxide surfaces that have been studied on multiple metals (MgO(100) and CeO(111), the slopes of these lines are the same, but their offset is large (∼2 J/m). Adhesion energies increase as MgO(100) ≈ TiO(110) < α-AlO(0001) < CeO(111) ≈ FeO(111).

The morphology and interfacial energetics of vapor-deposited Cu on slightly reduced CeO 2 (111) surfaces at 300 K have been studied using single crystal adsorption calorimetry (SCAC), He + low-energy ion scattering spectroscopy (ISS), Xray photoelectron spectroscopy (XPS), and low energy electron diffraction (LEED). Copper grows as three-dimensional nanoparticles with a density of ∼10 13 particles/cm 2 on CeO 2−x (111) (x = 0.05, 0.1, and 0.2). The initial heat of adsorption of Cu decreased with the extent of reduction, showing that stoichiometric ceria adsorbs Cu more strongly than oxygen vacancies. On CeO 1.95 (111), the heat dropped quickly with coverage in the first 0.1 ML, attributed to nucleation of Cu clusters on stoichiometric steps, followed by the Cu particles spreading onto less favorable sites (step vacancies and terraces). Above ∼0.1 ML (>0.8 nm in diameter), the Cu adsorption energies showed no variation with extent of ceria reduction: the heat of adsorption increased slowly with coverage (particle size) due to the formation of more Cu−Cu bonds per adatom as the size grows, finally approaching the heat of sublimation of bulk Cu by 3.5 ML (2.5 nm). The adhesion energy of Cu(solid) to CeO 1.95 (111) was found to be 3.52 J/m 2 for 2.2 nm diameter particles, decreasing slightly with the extent of reduction. The Ce 3d XPS line shape showed an increase in the Ce 3+ /Ce 4+ ratio with Cu coverage, corresponding to donation of at most ∼0.17 and 0.06 electrons per Cu atom to CeO 1.95 (111) and CeO 1.8 (111), respectively. INTRODUCTIONHeterogeneous catalysts are generally composed of late transition metal nanoparticles dispersed over high surface area oxide supports. The interaction of the supported metal and underlying oxide can greatly influence catalytic properties such as long-term sinter resistance, activity, and selectivity. To improve our understanding of how the choice of metal and support can influence catalytic properties, detailed studies of model systems, where metal atoms are vapor deposited onto single crystal oxide supports, are often employed. With these model systems, the structure of the support surface, the size of the metal particles, and surface cleanliness can be better controlled. 1−5 Studies of this type provide the basic understanding necessary for the intelligent design of new, more efficient, and greener catalysts. Here we apply that approach to study model Cu/CeO 2 catalysts consisting of Cu nanoparticles grown by vapor deposition on CeO 2 (111) surfaces with controlled extents of reduction.We study the energies of the Cu atoms in this system using single crystal adsorption calorimetry (SCAC). This method directly measures the adsorption energy of the incoming metal atoms as they bind to the oxide surface, and to metal nanoparticles on that surface as they grow in size. 6−11 The Cu nanoparticle morphology is characterized using ion scattering spectroscopy (ISS) and X-ray photoelectron spectroscopy (XPS). Adsorption energies measured using SCAC along with detailed adsorbate structura...

Many catalysts consist of late transition metal nanoparticles dispersed across oxide supports. The chemical potential of the metal atoms in these particles correlate with their catalytic activity and long-term thermal stability. This chemical potential versus particle size, across the full size range between the single isolated atom and bulk-like limits, is reported here for the first time for any metal on any oxide. The chemical potential of Cu atoms on CeO 2 (111) surfaces, determined by single crystal adsorption calorimetry (SCAC) of gaseous Cu atoms onto slightly-reduced CeO 2 (111) at 100 and 300 K, is shown to decrease dramatically with increasing Cu cluster size. The Cu chemical potential is ~110 kJ/mol higher for isolated Cu adatoms on stoichometric terrace sites than for Cu in nanoparticles exceeding 2.5 nm diameter, where it reaches the bulk Cu(solid) limit. In Cu dimers, Cu's chemical potential is ~57 kJ/mol lower at step edges than on stoichiometric terrace sites. Since Cu avoids oxygen vacancies, these monomer and dimer results are not strongly influenced by the 2.5% oxygen vacancies present on this CeO 2 surface, and are thus considered representative of stoichiometric CeO 2 (111) surfaces.

Three dimensional bilateral imaging is the standard for most clinical breast dynamic contrast-enhanced (DCE) MRI protocols. Because of high spatial resolution (sRes) requirement, the typical 1–2 min temporal resolution (tRes) afforded by a conventional full-k-space-sampling gradient echo (GRE) sequence precludes meaningful and accurate pharmacokinetic analysis of DCE time-course data. The commercially available, GRE-based, k-space undersampling and data sharing TWIST (time-resolved angiography with stochastic trajectories) sequence was used in this study to perform DCE-MRI exams on thirty one patients (with 36 suspicious breast lesions) before their biopsies. The TWIST DCE-MRI was immediately followed by a single-frame conventional GRE acquisition. Blinded from each other, three radiologist readers assessed agreements in multiple lesion morphology categories between the last set of TWIST DCE images and the conventional GRE images. Fleiss’ κ test was used to evaluate inter-reader agreement. The TWIST DCE time-course data were subjected to quantitative pharmacokinetic analyses. With a four-channel phased-array breast coil, the TWIST sequence produced DCE images with 20 s or less tRes and ~ 1.0×1.0×1.4 mm3 sRes. There were no significant differences in signal-to-noise (P = 0.45) and contrast-to-noise (P = 0.51) ratios between the TWIST and conventional GRE images. The agreements in morphology evaluations between the two image sets were excellent with the intra-reader agreement ranging from 79% for mass margin to 100% for mammographic density and the inter-reader κ value ranging from 0.54 (P < 0.0001) for lesion size to 1.00 (P < 0.0001) for background parenchymal enhancement. Quantitative analyses of the DCE time-course data provided higher breast cancer diagnostic accuracy (91% specificity at 100% sensitivity) than the current clinical practice of morphology and qualitative kinetics assessments. The TWIST sequence may be used in clinical settings to acquire high spatiotemporal resolution breast DCE-MRI images for both precise lesion morphology characterization and accurate pharmacokinetic analysis.