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Hybrid organic/inorganic solar cells such as ZnO/P3HT offer promise in increasing efficiency of organic-based devices. However there are many unresolved issues such as poor short-circuit current and open-circuit voltage that are hampering their widespread, commercial use. It is thought that surface trap states on ZnO are providing an open avenue for carrier recombination thus creating devices with poor current transport characteristics. Using self assembled monolayers (SAMs) may provide some key answers and solutions to this problem by passivating trap states. In the course of this work, benzoic acid, 4-aminobenzoic acid, 4-methoxybenzoic acid, phenylphosphonic acid, and 4-methoxyphenylphosphonic acid SAMs were studied in large part due to their commercial availability. It was found that the phenylphosphonic acids had a clear impact on decreasing dark current; therefore strongly suggesting that exciton recombination has been inhibited to some degree. These molecules also caused a decrease in efficiency by an order of magnitude as compared to a plain ZnO/P3HT bilayer cell (standard). There were pronounced negative effects on the other device parameters such as open circuit voltage and short circuit current. In the case of 4-methoxybenzoic acid and benzoic acid the effects are not so clear in that parts of the dark J-V curve indicate a decrease in dark current while other regions show an increase. Interestingly for the negative effect on efficiency and other device parameters was not as pronounced as the phenylphosphonic acids. In both cases it is hypothesized that because of their wide band gaps and poor energy level matching, they ultimately impact device performance negatively. In the future, use of simulations to determine optimal SAM molecular structures that can be synthesized in the lab or purchased commercially is suggested.

No description available.

CLEARFIELD® rice, which is a non-genetically modified crop that is tolerant to herbicides in the imidazolinone family has helped producers combat red rice problems in rice since itʼs introduction in 2002. Recently, breeders introduced hybrid CLEARFIELD® lines hoping to maintain the desired herbicide-resistant traits while having the added benefits of a hybrid. Soon after the hybrid line was released, farmers noticed herbicide injury to these new varieties while following the label recommendations. Research was performed to test the hybrids on the effect of planting date, planting density, and imazethapyr application rate on visual plant injury at Beaumont and Eagle Lake, TX in 2008 and 2009. A secondary experiment was designed to test the effect of imazethapyr application timing and rate on plant height, fresh weight, and dry weight in Eagle Lake and Beaumont, TX in 2010 with a greenhouse experiment in College Station, TX in 2009. The 2008 and 2009 field trials were planted at three different densities, (28, 39, and 50 kg ha-1) with two different planting dates representing the months of March and April. Herbicide treatments consisted of four 1- to 2-leaf rates of imazethapyr that included 0.035, 0.07, 0.105, and 0.14 kg ha-1, followed by two 4- to 6-leaf rates of imazethapyr of 0.07 and 0.105 kg ha-1. Rice showed injury symptoms two weeks after the second application of imazethapyr but was able to recover soon after nitrogen fertilizer application and flood establishment. Grain yield was not significantly different in plots that received a full labeled rate of imazethapyr or more for either location in either year. The 2009 greenhouse study and 2010 field studies included treatments that had one early post at 1- to 2-leaf and one of two different late post applications that included either a 3- to 4-leaf or a 5- to 6-leaf treatment. The three rates included in the early 1- to 2-leaf application were 0, 0.035 and 0.07 kg ai ha-1. The four rates included in the late application were 0, 0.07, 0.105, and 0.14 kg ai ha-1. Plants treated with the labeled rate, 0.07 to 0.105 kg ai ha-1 at each 1- to 2-leaf and 3- to 6-leaf stage, showed no significant differences in yield, or quality; however, significant differences were recorded in height. According to this data, hybrid rice seems to be tolerant to imazethapyr applications and timings.

Imaging and image processing have been used in variety of applications, such as medical, astronomy, forensic, and industry. Numerous techniques have been proposed to solve speci c problems faced in particular applications which are comprised of a series of processes such as, image enhancement, ltering, segmentation, representation, and recognition. However, there is no a universal algorithm which can be applied to variant image modalities with corresponding applications. With the aim of learning image processing tasks, as supervised learning techniques, we can develop e ective algorithms which are image and task oriented. Learning image processing comprises two main phases, namely: training and testing phases. During training phase, the algorithm has the capability of discovering and adjusting an optimum transformation function or optimal mathematical morphology chain by utilizing a user-prepared ground-truth (gold) sample. Later on, in testing phase, the obtained transform function of morphological chain is applied to untrained test images. The current thesis has three main parts as follows. In the rst part, genetic programming (GP) is employed to obtain an optimum transformation function. The GP utilizes one user-prepared gold sample to learn from. The magni cent feature of this method is that it does not require a prior knowledge or large training set to learn from. The performance of the proposed approach has been examined on 147 X-ray lung images. The results for image thresholding (i.e., Otsu's method) after applying optimal transformation are promising. In the second part, an optimum mathematical morphology (MM) chain is obtained by applying GP to localize the object of interest in a binary image. Morphology operations use 27 regular structuring elements along with commonly used morphological operations (i.e., erosion, dilation, opening, and closing) to build an optimal MM chain. The obtained chains are tested against challenging test cases, such as, object translation, scaling, and rotation. In the third part, a hybrid genetic programming - di erential evolutionary (GP-DE) algorithm is proposed to optimize not only the morphology chain but also the utilized structuring elements. GP as an outer layer optimizer is responsible to optimize the morphology chain while the di erential evolutionary (DE) as an inner layer optimizer optimizes the structure elements. Similarly in the testing phase, the obtained morphology chain is applied on test images. In term of utilized test images, the two test cases have been employed : synthesis and music note images. The results indicate that the proposed method is able to locate the object of interest. For the music note images, the proposed approach is able to extract the head notes, sta s, and vertical lines correctly. The training phase is iii time consuming, but it is acceptable; because one time training is required to obtain an optimal chain for a speci c image processing task.

Thesis (M.S.)--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references.

Thesis (M.S.)--Ohio University, March, 2003. / Title from PDF t.p. Includes bibliographical references (leaves 79-82).

Thesis (Ph.D.)--University of Waikato, 2007. / Title from PDF cover (viewed October 6, 2008) Includes bibliographical references (p. 304-332)