Metal Chalcogenide Clusters with Closed Electronic Shells and the Electronic Properties of Alkalis and Halogens

Clusters with filled electronic shells and a large gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) are generally energetically and chemically stable. Enabling clusters to become electron donors with low ionization energies or electron acceptors with high electron affinities usually requires changing the valence electron count. Here we demonstrate that a metal cluster may be transformed from an electron donor to an acceptor by exchanging ligands while the neutral form of the clusters has closed electronic shells. Our studies on Co6Te8(PEt3),(CO) (m + n = 6) clusters show that Co6Te8(PEt3)(6) has a closed electronic shell and a low ionization energy of 4.74 eV, and the successive replacement of PEt3 by CO ligands ends with Co6Te8(CO)(6) exhibiting halogen-like behavior. Both the low ionization energy Co6Te8(PEt3)(6) and high electron affinity Co6Te8(CO)(6) have closed electronic shells marked by high HOMO-LUMO gaps of 1.24 and 1.39 eV, respectively. Further, the clusters with an even number of ligands favor a symmetrical placement of ligands around the metal core

The effect of substituted benzene dicarboxylic acid linkers on the optical band gap energy and magnetic coupling in manganese trimer metal organic frameworks

We have systematically studied a series of eight metal-organic frameworks (MOFs) in which the secondary building unit is a manganese trimer cluster, and the linkers are differently substituted benzene dicarboxylic acids (BDC). The optical band gap energy of the compounds vary from 2.62 eV to 3.57 eV, and theoretical studies find that different functional groups result in new states in the conduction band, which lie in the gap and lower the optical band gap energy. The optical absorption between the filled Mn 3d states and the ligands is weak due to minimal overlap of the states, and the measured optical band gap energy is due to transitions on the BDC linker. The Mn atoms in the MOFs have local moments of 5 mu B, and selected MOFs are found to be antiferromagnetic, with weak coupling between the cluster units, and paramagnetic above 10 K

Symmetry and magnetism in Ni9Te6 clusters ligated by CO or phosphine ligands

The removal of a single ligand from the magnetic Ni9Te6(L)(8) (L = P(CH3)(3), CO) clusters is found to quench the magnetic moment. The reduction in magnetic moment is caused by a geometric deformation of the Ni9Te6 core that breaks the octahedral symmetry of the cluster. This effect is observed in both the CO and phosphine based ligands. The octahedral symmetry bare cluster is also found to have a large magnetic moment. These results highlight the dilemma faced by magnetic ligand protected clusters whose symmetry has been broken: whether to break the spin symmetry as in Hund\u27s rules or to break the spatial symmetry as in the Jahn-Teller effect. The spatial symmetry breaking is found to be an oblate distortion that forms additional Ni-Te bonds resulting in the enhanced stability of the cluster

The effect of sulfur covalent bonding on the electronic shells of silver clusters

The nature of the bonding in Ag n S m 0/− clusters, n = 1–7; m = 1–4, has been analyzed to understand its effect on the electronic shell structure of silver clusters. First-principle investigations reveal that the sulfur atoms prefer 2 or 3-coordinate sites around a silver core, and that the addition of sulfur makes the planar structures compact. Molecular orbital analysisfinds that the 3p orbitals of sulfur form a bonding orbital and two weakly bonding lone pairs withsilver. We examine the electronic shell structures of Ag 6Sm, which are two electrons deficient of a spherical closed electronic shell prior to the addition of sulfur, and Ag 7Sm − clusters that contain closed electronic shells prior to the addition of sulfur. The Ag 6S4 cluster has a distorted octahedral silver core and an open shell with a multiplicity of 3, while the Ag 7Sn − clusters have compact geometries with enhanced stability, confirming that the clusters maintain their electronic shell structure after bonding with sulfur

Optimized routing of unmanned aerial systems for the interdiction of improvised explosive devices

As of September 2007, improvised explosive devices (IED) account for 43% of U.S. casualties in Iraq - the largest single cause of death. One reason for their high rate of effectiveness is that they are extremely difficult to detect. This research develops a tool for selecting routes that will best employ unmanned aerial systems (UAS) for the purpose of detecting IED or related activity. We refer to this tool as IED Search Optimization Model (ISOM). ISOM - which uses prediction model results as an underpinning - accounts for factors such as winds, sensor sweep-width, and aircraft deconfliction. We formulate the problem as an Integer Program and optimally solve it to select the best routes. Initial evaluation of ISOM through field experiments with actual UAS suggest that the tool produces realistic routes which can be flown in the expected amount of time. Furthermore, these routes result in a 42% increase in the likelihood of achieving a detection opportunity over searching nodes in a random manner. ISOM could be implemented as a "reach-back" capability with an analyst providing daily routes for tactical operators.http://archive.org/details/optimizedrouting109453242Outstanding ThesisUS Marine Corps (USMC) author.Approved for public release; distribution is unlimited

Using Regular Languages to Explore the Representational Capacity of Recurrent Neural Architectures

The presence of Long Distance Dependencies (LDDs) in sequential data poses significant challenges for computational models. Various recurrent neural architectures have been designed to mitigate this issue. In order to test these state-of-the-art architectures, there is growing need for rich benchmarking datasets. However, one of the drawbacks of existing datasets is the lack of experimental control with regards to the presence and/or degree of LDDs. This lack of control limits the analysis of model performance in relation to the specific challenge posed by LDDs. One way to address this is to use synthetic data having the properties of subregular languages. The degree of LDDs within the generated data can be controlled through the k parameter, length of the generated strings, and by choosing appropriate forbidden strings. In this paper, we explore the capacity of different RNN extensions to model LDDs, by evaluating these models on a sequence of SPk synthesized datasets, where each subsequent dataset exhibits a longer degree of LDD. Even though SPk are simple languages, the presence of LDDs does have significant impact on the performance of recurrent neural architectures, thus making them prime candidate in benchmarking tasks.Comment: International Conference of Artificial Neural Networks (ICANN) 201

Metallic and molecular orbital concepts in XMg8 clusters, X = Be-F

The electronic structure and stability of the XMg8 clusters (X = Be, B, C, N, O, and F) are studied using first principles theoretical calculations to understand the variation in bonding in heteroatomic clusters which mix simple divalent metals with main group dopants. We examine these progressions with two competing models, the first is a distorted nearly free electron gas model and the second is a molecular orbital picture examining the orbital overlap between the dopant and the cluster. OMg8 is found to be the most energetically stable cluster due to strong bonding of O with the Mg8 cluster. BeMg8 has the largest HOMO-LUMO gap due to strong hybridization between the Mg8 and the Be dopant states that form a delocalized pool of 18 valence electrons with a closed electronic shell due to crystal field effects. Be, B, and C are best described by the nearly free electron gas model, while N, O, and F are best described through molecular orbital concepts