THE THREE DIMENSIONAL SHAPE AND ROUGHNESS OF MINERAL DUST

Mineral dust shape and roughness are important for a multitude of processes; it is known for aspherical shape but the true measurements in three dimensions are rare. Atomic Force Microscope was used for determine both 3D shape and roughness for two dust which are commonly used in laboratory experiments – Arizona Test Dust (ATD) and Kaolinite. We determined both of them are rather flat and round; an oblate spheroid would be a good model. Loess Filter was used to smooth the particles' surface and correlation analysis was used to examine the surfaces' properties of the dust; we found no features under 100nm scales. Also, our particles' surface area result is very similar to BET surface area.

Advanced Nanostructured Electro-Catalysts for Electricity Generation and Biorenewable Alcohol Conversion

In my Ph.D research, a wet chemistry-based organic solution phase reduction method was developed, and was successfully applied in the preparation of a series of advanced electro-catalysts, including 0-dimensional (0-D) Pt, Pd, Au, and Pd-Ni nanoparticles (NPs), 1-D Pt-Fe nanowires (NWs) and 2-D Pd-Fe nanoleaves (NLs), with controlled size, shape, and morphology. These nanostructured catalysts have demonstrated unique electro-catalytic functions towards electricity production and biorenewable alcohol conversion. The molecular oxygen reduction reaction (ORR) is a long-standing scientific issue for fuel cells due to its sluggish kinetics and the poor catalyst durability. The activity and durability of an electro-catalyst is strongly related with its composition and structure. Based on this point, Pt-Fe NWs with a diameter of 2 - 3 nm were accurately prepared. They have demonstrated a high durability in sulfuric acid due to its 1-D structure, as well as a high ORR activity attributed to its tuned electronic structure. By substituting Pt with Pd using a similar synthesis route, Pd-Fe NLs were prepared and demonstrated a higher ORR activity than Pt and Pd NPs catalysts in the alkaline electrolyte. Recently, biomass-derived alcohols have attracted enormous attention as promising fuels (to replace H2) for low-temperature fuel cells. From this point of view, Pd-Ni NPs were prepared and demonstrated a high electro-catalytic activity towards ethanol oxidation. Comparing to ethanol, the biodiesel waste glycerol is more promising due to its low price and high reactivity. Glycerol (and crude glycerol) was successfully applied as the fuel in an Au-anode anion-exchange membrane fuel cell (AEMFC). By replacing Au with a more active Pt catalyst, simultaneous generation of both high power-density electricity and value-added chemicals (glycerate, tartronate, and mesoxalate) from glycerol was achieved in an AEMFC. To investigate the production of valuable chemicals from glycerol electro-oxidation, two anion-exchange membrane electro-catalytic reactors were designed. The research shows that the electro-oxidation product distribution is strongly dependent on the anode applied potential. Reaction pathways for the electro-oxidation of glycerol on Au/C catalyst have been elucidated: continuous oxidation of OH groups (to produce tartronate and mesoxalate) is predominant at lower potentials, while C-C cleavage (to produce glycolate) is the dominant reaction path at higher potentials.

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.

A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

DIFFUSE-INTERFACE FIELD APPROACH TO MODELING SELF-ASSEMBLY OF HETEROGENEOUS COLLOIDAL SYSTEMS AND RELATED DIPOLE-DIPOLE INTERACTION PHENOMENA

Colloid self-assembly under external control is a new route to fabrication of advanced materials with novel microstructures and appealing functionalities. The kinetic processes of colloidal self-assembly have attracted great interests also because they are similar to many atomic level kinetic processes of materials. In the past decades, rapid technological progresses have been achieved on producing shape-anisotropic, patchy, core-shell structured particles and particles with electric/magnetic charges/dipoles, which greatly enriched the self-assembled structures. Multi-phase carrier liquids offer new route to controlling colloidal self-assembly. Therefore, heterogeneity is the essential characteristics of colloid system, while so far there still lacks a model that is able to efficiently incorporate these possible heterogeneities. This thesis is mainly devoted to development of a model and computational study on the complex colloid system through a diffuse-interface field approach (DIFA), recently developed by Wang et al. This meso-scale model is able to describe arbitrary particle shape and arbitrary charge/dipole distribution on the surface or body of particles. Within the framework of DIFA, a Gibbs-Duhem-type formula is introduced to treat Laplace pressure in multi-liquid-phase colloidal system and it obeys Young-Laplace equation. The model is thus capable to quantitatively study important capillarity related phenomena. Extensive computer simulations are performed to study the fundamental behavior of heterogeneous colloidal system. The role of Laplace pressure is revealed in determining the mechanical equilibrium of shape-anisotropic particles at fluid interfaces. In particular, it is found that the Laplace pressure plays a critical role in maintaining the stability of capillary bridges between close particles, which sheds light on a novel route to in situ firming compact but fragile colloidal microstructures via capillary bridges. Simulation results also show that competition between like-charge repulsion, dipole-dipole interaction and Brownian motion dictates the degree of aggregation of heterogeneously charged particles. Assembly and alignment of particles with magnetic dipoles under external field is studied. Finally, extended studies on the role of dipole-dipole interaction are performed for ferromagnetic and ferroelectric domain phenomena. The results reveal that the internal field generated by dipoles competes with external field to determine the dipole-domain evolution in ferroic materials.