Development of a high performance parallel computing platform and its use in the study of nanostructures : clusters, sheets and tubes .

Small clusters of gallium oxide, technologically important high temperature ceramic, together with interaction of nucleic acid bases with graphene and small-diameter carbon nanotube are focus of first principles calculations in this work. A high performance parallel computing platform is also developed to perform these calculations at Michigan Tech. First principles calculations are based on density functional theory employing either local density or gradient-corrected approximation together with plane wave and gaussian basis sets. The bulk Ga2O3 is known to be a very good candidate for fabricating electronic devices that operate at high temperatures. To explore the properties of Ga2O3 at nonoscale, we have performed a systematic theoretical study on the small polyatomic gallium oxide clusters. The calculated results find that all lowest energy isomers of GamOn clusters are dominated by the Ga-O bonds over the metal-metal or the oxygen-oxygen bonds. Analysis of atomic charges suggest the clusters to be highly ionic similar to the case of bulk Ga2O3. In the study of sequential oxidation of these slusters starting from Ga2O, it is found that the most stable isomers display up to four different backbones of constituent atoms. Furthermore, the predicted configuration of the ground state of Ga2O is recently confirmed by the experimental result of Neumark's group. Guided by the results of calculations the study of gallium oxide clusters, performance related challenge of computational simulations, of producing high performance computers/platforms, has been addressed. Several engineering aspects were thoroughly studied during the design, development and implementation of the high performance parallel computing platform, rama, at Michigan Tech. In an attempt to stay true to the principles of Beowulf revolutioni, the rama cluster was extensively customized to make it easy to understand, and use - for administrators as well as end-users. Following the results of benchmark calculations and to keep up with the complexity of systems under study, rama has been expanded to a total of sixty four processors. Interest in the non-covalent intereaction of DNA with carbon nanotubes has steadily increased during past several years. This hybrid system, at the junction of the biological regime and the nanomaterials world, possesses features which make it very attractive for a wide range of applicatioins. Using the in-house computational power available, we have studied details of the interaction between nucleic acid bases with graphene sheet as well as high-curvature small-diameter carbon nanotube. The calculated trend in the binding energies strongly suggests that the polarizability of the base molecules determines the interaction strength of the nucleic acid bases with graphene. When comparing the results obtained here for physisorption on the small diameter nanotube considered with those from the study on graphene, it is observed that the interaction strength of nucleic acid bases is smaller for the tube. Thus, these results show that the effect of introducing curvature is to reduce the binding energy. The binding energies for the two extreme cases of negligible curvature (i.e. flat graphene sheet) and of very high curvature (i.e. small diameter nanotube) may be considered as upper and lower bounds. This finding represents an important step towards a better understanding of experimentally observed sequence-dependent interaction of DNA with Carbon nanotubes.

Syntheses and characterization of monomeric Mo(VI) complexes with bidentate phosphine oxide ligands and dimeric and tetrameric Mo(V) clusters with benzoic acid and phosphinic acid derivatives, containing MoO2, Mo2O2(μ-O)2 and Mo4O4(μ3-O)4

Mo(VI) oxo complexes have been persistently sought after as epoxidation catalysts. Further, Mo(V) oxo clusters of the form M4(µ3-X)4 (M = transition metal, X = O, S) have been rigorously studied due to their remarkable structures and also their usefulness as models for electronic studies. The syntheses and characterizations of new Mo(VI) and Mo(V) oxo complexes have been described in this dissertation. Two new complexes MoO2Cl2Ph2P(O)CH2COOH and MoO2Cl2Ph2P(O)C6H4tBuS(O) were synthesized from reactions of “MoO2Cl2” with ligands Ph2P(O)CH2COOH and Ph2P(O)C6H4tBuS(O). Tetrameric packing arrangements comprised of hydrogen bonds were obtained for the complex MoO2Cl2Ph2P(O)CH2COOH and the ligand Ph2P(O)CH2COOH. Further the stability of an Mo-O bond was preferred over the Mo-S bond even though this resulted in the formation of a more strained seven membered ring. Tetranuclear Mo(V) complexes of the form [Mo4(µ3-O)4(µ-O2PR2)4O4], (PR2 = PPh2, PMe2) were synthesized using reactions of MoO2(acac)2 with diphenyl and dimethyl phosphinic acids, in ethanol. In the crystal structure of these complexes four Mo=O units are interconnected by four triply bridging oxygen atoms and bridging phosphinate ligands. The complex exhibited fourfold symmetry as evidenced by a single 31P NMR peak for the P atoms in the coordinated ligands. Reaction of WO2(acac)2 with Ph2POOH in methanol resulted in a dimeric W(VI) complex [(CH3O)2(O)W(µ-O)( µ-O2PPh2)2W(O)(CH3O)2] which contained a packing disorder in its crystal structure. Similar reactions of MoO2(acac)2 with benzoic acid derivatives resulted in dimeric complexes of the form [Mo2O2(acac)2(µ-O)(µ-OC2H5)(µ-O2CR)] (R = C6H5, (o-OH)C6H4, (p-Cl)C6H4, (2,4-(OH)2)C6H3, (o-I)C6H4) and one tetrameric complex [Mo2O2(acac)2(µ-O)(µ-OC2H5)(µ-O2C)C6H4(p-µ-O2C)Mo2O2(acac)2(µ-O)(µ-OC2H5)] with terephthalic acid. 1H NMR proved very useful in the prediction of the formation of dimers with the substituted benzoic acids, which were also confirmed by elemental analyses. The reductive capability of ethanol proved instrumental in the syntheses of Mo(V) tetrameric and dimeric clusters. Synthetic details, IR, 1H and 31P NMR spectroscopy and elemental analyses are reported for all new complexes. Further, single crystal X-ray structures of MoO2Cl2Ph2P(O)CH2COOH, MoO2Cl2Ph2P(O)C6H4tBuS(O), [Mo4(µ3-O)4(µ-O2PR2)4O4], (PR2 = PPh2, PMe2), [(CH3O)2(O)W(µ-O)( µ-O2PPh2)2W(O)(CH3O)2] and [Mo2O2(acac)2(µ-O)(µ-OC2H5)(µ-O2CR)] (R = C6H5, (o-OH)C6H4) are also presented.

Understanding volcanic processes using UV camera measurements of sulfur dioxide and coincident infrasound and seismicity

The exsolution of volatiles from magma maintains an important control on volcanic eruption styles. The nucleation, growth, and connectivity of bubbles during magma ascent provide the driving force behind eruptions, and the rate, volume, and ease of gas exsolution can affect eruptive activity. Volcanic plumes are the observable consequence of this magmatic degassing, and remote sensing techniques allow us to quantify changes in gas exsolution. However, until recently the methods used to measure volcanic plumes did not have the capability of detecting rapid changes in degassing on the scale of standard geophysical observations. The advent of the UV camera now makes high sample rate gas measurements possible. This type of dataset can then be compared to other volcanic observations to provide an in depth picture of degassing mechanisms in the shallow conduit. The goals of this research are to develop a robust methodology for UV camera field measurements of volcanic plumes, and utilize this data in conjunction with seismoacoustic records to illuminate degassing processes. Field and laboratory experiments were conducted to determine the effects of imaging conditions, vignetting, exposure time, calibration technique, and filter usage on the UV camera sulfur dioxide measurements. Using the best practices determined from these studies, a field campaign was undertaken at Volcán de Pacaya, Guatemala. Coincident plume sulfur dioxide measurements, acoustic recordings, and seismic observations were collected and analyzed jointly. The results provide insight into the small explosive features, variations in degassing rate, and plumbing system of this complex volcanic system. This research provides useful information for determining volcanic hazard at Pacaya, and demonstrates the potential of the UV camera in multiparameter studies.

Plenoptic camera : theory and experimental results

The purpose of this research was to develop a working physical model of the focused plenoptic camera and develop software that can process the measured image intensity, reconstruct this into a full resolution image, and to develop a depth map from its corresponding rendered image. The plenoptic camera is a specialized imaging system designed to acquire spatial, angular, and depth information in a single intensity measurement. This camera can also computationally refocus an image by adjusting the patch size used to reconstruct the image. The published methods have been vague and conflicting, so the motivation behind this research is to decipher the work that has been done in order to develop a working proof-of-concept model. This thesis outlines the theory behind the plenoptic camera operation and shows how the measured intensity from the image sensor can be turned into a full resolution rendered image with its corresponding depth map. The depth map can be created by a cross-correlation of adjacent sub-images created by the microlenslet array (MLA.) The full resolution image reconstruction can be done by taking a patch from each MLA sub-image and piecing them together like a puzzle. The patch size determines what object plane will be in-focus. This thesis also goes through a very rigorous explanation of the design constraints involved with building a plenoptic camera. Plenoptic camera data from Adobe © was used to help with the development of the algorithms written to create a rendered image and its depth map. Finally, using the algorithms developed from these tests and the knowledge for developing the plenoptic camera, a working experimental system was built, which successfully generated a rendered image and its corresponding depth map.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.