Missouri University of Science and Technology

About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Artificial neural network & Control theory. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.

Efficient Utilization of Renewable Energy Sources by Gridable Vehicles in Cyber-Physical Energy Systems

Abstract: The main sources of emission today are from the electric power and transportation sectors. One of the main goals of a cyber-physical energy system (CPES) is the integration of renewable energy sources and gridable vehicles (GVs) to maximize emission reduction. GVs can be used as loads, sources and energy storages in CPES. A large CPES is very complex considering all conventional and green distributed energy resources, dynamic data from sensors, and smart operations (e.g., charging/discharging, control, etc.) from/to the grid to reduce both cost and emission. If large number of GVs are connected to the electric grid randomly, peak load will be very high. The use of conventional thermal power plants will be economically expensive and environmentally unfriendly to sustain the electrified transportation. Intelligent scheduling and control of elements of energy systems have great potential for evolving a sustainable integrated electricity and transportation infrastructure. The maximum utilization of renewable energy sources using GVs for sustainable CPES (minimum cost and emission) is presented in this paper. Three models are described and results of the smart grid model show the highest potential for sustainability.

A “Star” Antiferromagnet: A Polymeric Iron(III) Acetate That Exhibits Both Spin Frustration and Long‐Range Magnetic Ordering

Abstract: The preparation of new geometrically spin-frustrated magnetic materials that approximate theoretical models is a challenge. Although theMermin–Wagner theorem indicates that long-range magnetic order can exist in two dimensions at zero Kelvin, order can be destroyed either by quantum fluctuations or geometric frustration even at this temperature. Theoretical studies indicate that the ground state of a spin-1/2 Heisenberg antiferromagnet is most likely to be semiclassically ordered. However, the interplay of geometric frustration and quantum fluctuations has been found to give rise to a paramagnetic ground state without semi-classical long-range order in two types of lattice. The first of these lattices is the famous Kagom+ lattice (T8) and the second is the so-called “star” lattice (T9; Scheme 1), which may serve as a new example of a quantum paramagnet. 5] The triangles are corner-sharing in the Kagom+ lattice whereas they are separated by a bridge in the star lattice, which means that their next-nearest-neighbor exchange interactions are different. 5] The magnetic J exchange pathways in the Kagom+ lattice are all equivalent, whereas the intra-triangular JT pathway in the star lattice is weaker than the inter-triangular JD pathway. In contrast to the rapid development of Kagom+-type antiferromagetic lattices 7] and related, geometrically spin-frustrated lattices, there appears to date to be no report of a compound with a genuine star lattice. Triangular clusters with superexchange pathways, such as the widely employedM3(m3-O) clusters, whereMmay be Fe , Fe, Co, Ni, Cu, V, or Cr, can be used to generate frustrated lattices, including the desired magnetically frustrated star lattice. This star lattice can be described in vertex notation as 3.12 (see Scheme S1 in the Supporting Information), a lattice that is a uniform, three-connected twodimensional net with large voids. Three-connected node subunits that prefer to bond in a planar fashion, such as the basic cationic iron(III) carboxylate cluster [Fe3(m3-O)(mO2CR)6L3] , where L may be water, methanol, or pyridine, must be used to avoid three-dimensional connections. These carboxylate clusters are good potential building blocks because they are easily prepared, prefer planar bonding, and the R groups and L ligands can easily be varied. The cationic [Fe3(m3-O)(m-O2CR)6L3] + moiety has previously served as a sixor three-connected node (see Scheme S2 in the Supporting Information) to form either threeor zero-dimensional porous frameworks depending upon the nature of the carboxylate, which may be either fully or partially substituted by dicarboxylates; the L ligands are usually retained as terminal ligands. Although no example is known to date, it should be possible to substitute the L ligands located in the triangular [Fe3(m3-O)(m-O2CR)6L3] + cation plane with other bridging bidentate ligands that are better at both mediating antiferromagnetic interactions and producing a two-dimensional star lattice. Herein, we report the use of bidentate acetate bridging ligands to link [Fe3(m3-O)(mOAc)6] + cations together to form [Fe3(m3-O)(m-OAc)6(H2O)3][Fe3(m3-O)(m-OAc)7.5]2·7H2O (1), a new compound with the desired star lattice. Single-crystal X-ray diffraction studies of 1 at 293 and 90 K revealed that isolated [Fe3(m3-O)(m-OAc)6(H2O)3] + cations (Figure 1) occupy the dodecagonal channels formed by the stacking of acetate-bridged [Fe3(m3-O)(m-OAc)7.5] 1/2 anionic layers; the dihedral angle between the triangular [Fe3(m3-O)(m-OAc)6(H2O)3] + cations and the [Fe3(m3-O)(mScheme 1. A comparison of the Kagom (T8, left) and star (T9, right) lattices with indication of the magnetic J exchange pathways.

Generalized Hamilton–Jacobi–Bellman Formulation -Based Neural Network Control of Affine Nonlinear Discrete-Time Systems

Abstract: In this paper, we consider the use of nonlinear networks towards obtaining nearly optimal solutions to the control of nonlinear discrete-time (DT) systems. The method is based on least squares successive approximation solution of the generalized Hamilton-Jacobi-Bellman (GHJB) equation which appears in optimization problems. Successive approximation using the GHJB has not been applied for nonlinear DT systems. The proposed recursive method solves the GHJB equation in DT on a well-defined region of attraction. The definition of GHJB, pre-Hamiltonian function, HJB equation, and method of updating the control function for the affine nonlinear DT systems under small perturbation assumption are proposed. A neural network (NN) is used to approximate the GHJB solution. It is shown that the result is a closed-loop control based on an NN that has been tuned a priori in offline mode. Numerical examples show that, for the linear DT system, the updated control laws will converge to the optimal control, and for nonlinear DT systems, the updated control laws will converge to the suboptimal control.

Electrodeposited ceramic single crystals

Abstract: Single-crystal films are essential for devices because the intrinsic properties of the material, rather than its grain boundaries, can be exploited. Cubic bismuth oxide has the highest known oxide ion mobility, which makes it useful for fuel cells and sensors, but it is normally only stable from 729° to 825°C. The material has not been previously observed at room temperature. Single-crystal films of the high-temperature cubic polymorph of bismuth oxide were epitaxially electrodeposited from an aqueous solution onto single-crystal gold substrates. The 35.4 percent lattice mismatch was accommodated by forming coincidence lattices in which the bismuth oxide film was rotated in relation to the gold substrate. These results provide a method for producing other nonequilibrium phases that cannot be accessed by traditional thermal processing.