EDUCATIONAL AND OCCUPATIONAL PLANS OF FARM BOYS IN 1967

Labor and Human Capital,

MEASURING PRODUCTIVITY CHANGE IN U.S. AGRICULTURE

Productivity Analysis,

Micro-Fabricated Hydrogen Sensors Operating at Elevated Temperatures

In this dissertation, three types of microfabricated solid-state sensors had been designed and developed on silicon wafers, aiming to detect hydrogen gas at elevated temperatures. Based on the material properties and sensing mechanisms, they were operated at 140°C, 500°C, and 300°C. The MOS-capacitor device working at 140°C utilized nickel instead of the widely-used expensive palladium, and the performance remained excellent. For very-high temperature sensing (500°C), the conductivity of the thermally oxidized TiO2 thin film based on the anodic aluminum oxide (AAO) substrate changed 25 times in response to 5 ppm H2 and the response transient times were just a few seconds. For medium-high temperatures (~300°C), very high sensitivity (over 100 times’ increment of current for H2 concentration at 10 ppm) was obtained through the reversible reduction of the Schottky barrier height between the Pt electrodes and the SnO2 nano-clusters. Fabrication approaches of these devices included standard silicon wafer processing, thin film deposition, and photolithography. Materials characterization methods, such as scanning electron microscopy (SEM), atomic force microscopy (AFM), surface profilometry, ellipsometry, and X-ray diffractometry (XRD), were involved in order to investigate the fabricated nano-sized structures. Selectivities of the sensors to gases other than H2 (CO and CH4) were also studied. The first chapter reviews and evaluates the detection methodologies and sensing materials in the current research area of H2 sensors and the devices presented this Ph.D. research were designed with regard to the evaluations

Interpretation of Nuclear Magnetic Resonance Measurements in Formations with Complex Pore Structure

Nuclear Magnetic Resonance (NMR) measurement as an unconventional well logging method, is among the most accurate approaches to estimate formation porosity. Petrophysicists use NMR to evaluate petrophysical properties such as pore size distribution, permeability, and fluid saturation, of various formations. However, the NMR responses in complex formations, such as fractured carbonate and organicrich mudrocks, have not been thoroughly investigated. NMR pore-scale simulations using a random-walk algorithm enable us to model the NMR relaxometry in porous rock samples, and to improve interpretation of NMR relaxometry in complex formations. Based on pore-scale simulations and theoretical analysis of NMR relaxometry, this research estimated petrophysical properties that have been challenging when using conventional NMR interpretation, including micro-fracture volumetric concentration, directional pore connectivity and directional permeability, and the impact of wettability alteration. This dissertation (a) quantified the impacts of micro-fractures on NMR relaxation times by pore-scale simulations and developed an analytical model for fracture-pore diffusional coupling in multiple-pore-type systems (i.e. composed of intra-/inter-granular pores and micro-fractures); (b) investigated the viability of using the NMR analytical model to estimate the volumetric concentrations and apertures of micro-fractures in fractured formations; (c) developed an innovative NMR-based directional permeability model to estimate anisotropic permeability of rock samples with complex pore structure; (d) investigated the impacts of fracturepore diffusional coupling on NMR permeability assessment and evaluated reliability of NMR permeability models in fractured formations; and (e) developed a two-phase NMR pore-scale simulation method to model the NMR responses in organicrich mudrocks, as well as investigated the impact of wettability alteration on NMR relaxometry in organic-rich mudrocks. The methods used in this research include pore-scale image processing, single-phase and two-phase NMR simulations in porous media, fluid flow simulations in porous media, and theoretical analysis of NMR relaxation mechanisms in porous media. Results show that the introduced methods for interpretation of NMR relaxometry can enhance reservoir characterization in challenging reservoirs, including carbonates and organic-rich mudrocks

Playing Stackelberg Opinion Optimization with Randomized Algorithms for Combinatorial Strategies

From a perspective of designing or engineering for opinion formation games in social networks, the "opinion maximization (or minimization)" problem has been studied mainly for designing subset selecting algorithms. We furthermore define a two-player zero-sum Stackelberg game of competitive opinion optimization by letting the player under study as the first-mover minimize the sum of expressed opinions by doing so-called "internal opinion design", knowing that the other adversarial player as the follower is to maximize the same objective by also conducting her own internal opinion design. We propose for the min player to play the "follow-the-perturbed-leader" algorithm in such Stackelberg game, obtaining losses depending on the other adversarial player's play. Since our strategy of subset selection is combinatorial in nature, the probabilities in a distribution over all the strategies would be too many to be enumerated one by one. Thus, we design a randomized algorithm to produce a (randomized) pure strategy. We show that the strategy output by the randomized algorithm for the min player is essentially an approximate equilibrium strategy against the other adversarial player