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: Control theory & Artificial neural network. 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.

Chemically durable iron phosphate glass wasteforms

Abstract: Up to 40 wt% of a simulated high level waste, whose major components were 54.6 wt% Na2O, 14.9 wt% P2O5 and 8.3 wt% Fe2O3, was successfully vitrified into iron phosphate wasteforms whose chemical durability was equivalent to that of borosilicate glass wasteforms. Because of their high fluidity, the iron phosphate wasteforms could be melted in as little as 30 min at temperatures between 1015°C and 1200°C. The addition of 3–7 wt% CaF2 to the batch decreased the melting time and temperature, by as much as 100°C, and improved the chemical durability, especially for crystallized iron phosphate wasteforms. Iron phosphate wasteforms are concluded to be a practical alternative for vitrifying those nuclear wastes not well suited for borosilicate glasses.

The structure of the high-energy spin excitations in a high-transition-temperature superconductor

Abstract: In conventional superconductors, lattice vibrations (phonons) mediate the attraction between electrons that is responsible for superconductivity1. The high transition temperatures (high-Tc) of the copper oxide superconductors has led to collective spin excitations being proposed as the mediating excitations in these materials2. The mediating excitations must be strongly coupled to the conduction electrons, have energy greater than the pairing energy, and be present at Tc. The most obvious feature in the magnetic excitations of high-Tc superconductors such as YBa2Cu3O6+x is the so-called ‘resonance’3,4,5,6. Although the resonance may be strongly coupled to the superconductivity3,4,5,6,7,8, it is unlikely to be the main cause, because it has not been found in the La2-x(Ba,Sr)xCuO4 family and is not universally present in Bi2Sr2CaCu2O8+δ (ref. 9). Here we use inelastic neutron scattering to characterize possible mediating excitations at higher energies in YBa2Cu3O6.6. We observe a square-shaped continuum of excitations peaked at incommensurate positions. These excitations have energies greater than the superconducting pairing energy, are present at Tc, and have spectral weight far exceeding that of the ‘resonance’. The discovery of similar excitations in La2–xBaxCuO4 (ref. 10) suggests that they are a general property of the copper oxides, and a candidate for mediating the electron pairing.

Resource Scheduling Under Uncertainty in a Smart Grid With Renewables and Plug-in Vehicles

Abstract: The power system and transportation sector are our planet's main sources of greenhouse gas emissions. Renewable energy sources (RESs), mainly wind and solar, can reduce emissions from the electric energy sector; however, they are very intermittent. Likewise, next generation plug-in vehicles, which include plug-in hybrid electric vehicles and electric vehicles with vehicle-to-grid capability, referred to as gridable vehicles (GVs) by the authors, can reduce emissions from the transportation sector. GVs can be used as loads, energy sources (small portable power plants) and energy storage units in a smart grid integrated with renewable energy sources. However, uncertainty surrounds the controllability of GVs. Forecasted load is used in unit commitment (UC); however, the actual load usually differs from the forecasted one. Thus, UC with plug-in vehicles under uncertainty in a smart grid is very complex considering smart charging and discharging to and from various energy sources and loads to reduce both cost and emissions. A set of valid scenarios is considered for the uncertainties of wind and solar energy sources, load and GVs. In this paper, an optimization algorithm is used to minimize the expected cost and emissions of the UC schedule for the set of scenarios. Results are presented indicating that the smart grid has the potential to maximally utilize RESs and GVs to reduce cost and emissions from the power system and transportation sector.