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Density Functional Study Of Structural Trends For Late-Transition-Metal 13-Atom Clusters, Lin-Lin Wang, Duane D. Johnson
Density Functional Study Of Structural Trends For Late-Transition-Metal 13-Atom Clusters, Lin-Lin Wang, Duane D. Johnson
Duane D. Johnson
Because reactivity increases as particle size decreases and competition between numerous structures are possible, which affects catalytic and magnetic properties, we study the structural trends of late-transition-metal 13-atom clusters using density functional theory within the generalized gradient approximation to exchange-correlation functional. We consider open structural motifs, such as bilayer and cubic (recently found to have lower energy), and find new bilayer candidates that are even lower in energy. To study the influence of d-orbital filling on structural trends, we focus on Pt, Pd, and Rh clusters and find several new, low-energy structures for Pt13 and Pd13 from searches using a …
First-Principles Prediction Of Phase-Segregating Alloy Phase Diagrams And A Rapid Design Estimate Of Their Transition Temperatures, Nikolai A. Zarkevich, Teck L. Tan, Duane D. Johnson
First-Principles Prediction Of Phase-Segregating Alloy Phase Diagrams And A Rapid Design Estimate Of Their Transition Temperatures, Nikolai A. Zarkevich, Teck L. Tan, Duane D. Johnson
Nikolai A. Zarkevich
We calculate the transition temperature versus concentration (Tc vs c) phase diagrams of several phase-segregating alloys [fcc Ca-Sr, Au-Pt, and Rh-(Pd,Cu,Ag,Au)] using a multiscale method combining first-principles calculations and Monte Carlo via the cluster expansion (CE). We study Pd-Rh, with its well-known high-T miscibility gap, to verify the method’s reliability. We predict that Ca-Sr segregates at low temperatures. We then show that a rapid estimate of Tc is obtained from enthalpies analytically derived from a CE, and, using thermodynamic integration, we determine under what circumstances this mean-field estimate is accurate compared to Monte Carlo results. Also, we discuss how an …
Markov Chain Monte Carlo Defect Identification In Nde Images, Aleksandar Dogandžić, Benhong Zhang
Markov Chain Monte Carlo Defect Identification In Nde Images, Aleksandar Dogandžić, Benhong Zhang
Aleksandar Dogandžić
We derive a hierarchical Bayesian method for identifying elliptically‐shaped regions with elevated signal levels in NDE images. We adopt a simple elliptical parametric model for the shape of the defect region and assume that the defect signals within this region are random following a truncated Gaussian distribution. Our truncated‐Gaussian model ensures that the signals within the defect region are higher than the baseline level corresponding to the noise‐only case. We derive a closed‐form expression for the kernel of the posterior probability distribution of the location, shape, and defect‐signal distribution parameters (model parameters). This result is then used to develop Markov …