Effects of carbonation on the mineral composition of cement kiln dust

Due to their relatively high calcium oxide content, industrial mineral oxide wastes are potential candidates for mineral sequestration of carbon dioxide (CO2). Cement kiln dust (CKD), a byproduct of cement manufacturing contains 20-60% CaO making it a possible candidate for CO2 sequestration. In this study, three types of CKD are characterized, before and after carbonation, using environmental scanning electron microscopy and energy dispersive x-ray microanalysis to determine the mineralogical and morphological changes occurring due to carbonation. The reactants, products, and precipitation mechanisms were investigated to enhance understanding of the governing processes and allow better utilization of CKD for CO2 sequestration. The results of multiple independent analyses confirmed the formation of CaCO3 during carbonation. Examinations of the reaction pathways found that CaO and calcium hydroxide (Ca(OH)2) were the major reactants. Three types of CaCO3 precipitation mechanisms were observed: (1) diffusion of CO2 into Ca(OH)2 particles causing precipitation in the pores of the particle and the growth of a CaCO3 ring from the outside inward, (2) precipitation onto existing particles, and (3) precipitation from aqueous solution. The growth of a CaCO3 ring on the outside of a particle may slow further diffusion of CO2 into a particle slowing iv the overall sequestration rate. Additionally, changes caused by carbonation in the solubility of trace metals were studied by mixing pre- and post-carbonated CKD with water and analyzing the solution using inductively coupled plasma mass spectrometry. Decreases in the leaching of chromium, lead, and copper were observed, and is an incentive for use of CKD for CO2 sequestration. Equilibrium modeling using PHREEQC confirmed that CaO and Ca(OH)2 would carbonate readily and form CaCO3.

Development of room temperature operating single electron transistor using FIB etching and deposition technology

The single-electron transistor (SET) is one of the best candidates for future nano electronic circuits because of its ultralow power consumption, small size and unique functionality. SET devices operate on the principle of Coulomb blockade, which is more prominent at dimensions of a few nano meters. Typically, the SET device consists of two capacitively coupled ultra-small tunnel junctions with a nano island between them. In order to observe the Coulomb blockade effects in a SET device the charging energy of the device has to be greater that the thermal energy. This condition limits the operation of most of the existing SET devices to cryogenic temperatures. Room temperature operation of SET devices requires sub-10nm nano-islands due to the inverse dependence of charging energy on the radius of the conducting nano-island. Fabrication of sub-10nm structures using lithography processes is still a technological challenge. In the present investigation, Focused Ion Beam based etch and deposition technology is used to fabricate single electron transistors devices operating at room temperature. The SET device incorporates an array of tungsten nano-islands with an average diameter of 8nm. The fabricated devices are characterized at room temperature and clear Coulomb blockade and Coulomb oscillations are observed. An improvement in the resolution limitation of the FIB etching process is demonstrated by optimizing the thickness of the active layer. SET devices with structural and topological variation are developed to explore their impact on the behavior of the device. The threshold voltage of the device was minimized to ~500mV by minimizing the source-drain gap of the device to 17nm. Vertical source and drain terminals are fabricated to realize single-dot based SET device. A unique process flow is developed to fabricate Si dot based SET devices for better gate controllability in the device characteristic. The device vi parameters of the fabricated devices are extracted by using a conductance model. Finally, characteristic of these devices are validated with the simulated data from theoretical modeling.

A COMPARATIVE STUDY OF HEURISTIC OPTIMIZATION ALGORITHMS

Heuristic optimization algorithms are of great importance for reaching solutions to various real world problems. These algorithms have a wide range of applications such as cost reduction, artificial intelligence, and medicine. By the term cost, one could imply that that cost is associated with, for instance, the value of a function of several independent variables. Often, when dealing with engineering problems, we want to minimize the value of a function in order to achieve an optimum, or to maximize another parameter which increases with a decrease in the cost (the value of this function). The heuristic cost reduction algorithms work by finding the optimum values of the independent variables for which the value of the function (the “cost”) is the minimum. There is an abundance of heuristic cost reduction algorithms to choose from. We will start with a discussion of various optimization algorithms such as Memetic algorithms, force-directed placement, and evolution-based algorithms. Following this initial discussion, we will take up the working of three algorithms and implement the same in MATLAB. The focus of this report is to provide detailed information on the working of three different heuristic optimization algorithms, and conclude with a comparative study on the performance of these algorithms when implemented in MATLAB. In this report, the three algorithms we will take in to consideration will be the non-adaptive simulated annealing algorithm, the adaptive simulated annealing algorithm, and random restart hill climbing algorithm. The algorithms are heuristic in nature, that is, the solution these achieve may not be the best of all the solutions but provide a means to reach a quick solution that may be a reasonably good solution without taking an indefinite time to implement.