The removal of particles, on the order of a micrometer – nanometer in size, adhered to surfaces poses a challenge to Integrated Circuit (IC) fabrication, space optics, high resolution and high power optics, large area displays, magnetic storage device and other critical surfaces. The existing cleaning processes are unable to clean particulate contamination at the sub-micron level. Laser Particle Removal (LPR) is a novel technique to remove micron and submicron particulate contamination from the solid surface. In LPR, a vapor of an Energy Transfer Medium (ETM) is condensed on the Si substrate. The vapor forms a uniform film on and around the particles. After a short time lag a KrF laser beam is used to irradiate the Si substrate which causes explosive evaporation of the ETM and propels the particle off the substrate. The ETM film thickness should be a critical factor in the LPR process. In our experiments a KrF laser at 248 nm is used to remove polystyrene particles of 0.1 ìm, 0.25 ìm and 0.55 ìm in radius from a Si substrate using 2-propanol as the ETM. The Cleaning threshold fluence for these particles at varying ETM film thicknesses is measured. In the end of this work the molecular dynamics simulations of laser cleaning process is discussed. / A Thesis Submitted to the Department of Industrial Engineering in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Fall Semester, 2003. / November 1, 2003. / laser assisted particle removal, material science, ETM, shishir, shukla, Si material / Includes bibliographical references. / Hsu-Pin Wang, Professor Co-Directing Dissertation; Susan Allen, Professor Co-Directing Dissertation; Yousuff Hussaini, Committee Member.

Validation is an important step that is often left out of modeling due to lack of time, lack of funding, or just plain ignorance. Many industries that practice design of experiments leave out this important step because the benefits are not visible for the model that is often created. In addition, there appears to be no clear way to measure whether or not the validation points truly validate the model. This paper focuses on a new way of validation that will both refine the model, yielding more information, and validate the model. This new approach of validation is a simple way of improving the model and making sure that it does what it was designed to do. This validation procedure is only used for 2nd order models that are based off of a central composite design, but have the possibility of picking up 3rd order terms that the model was unable to identify without the extra validation points. Validation points are chosen through a genetic algorithm using space-filling and orthogonality criteria. A new set of points that is different from that of the design is derived. These points are better than just randomly selecting points that have no meaning. Validation is a necessary step to eliminate many risks. The procedure defined here is useful for determining 3rd order terms and their validity in a model. / A Thesis Submitted to the Department of Industrial and Manufacturing Engingeering in Partial Fulfillment of the Requirements for the Degree of Masters of Science. / Fall Semester, 2007. / October 18, 2007. / Augmentation, Second Order Desgins, Validation, Refinement / Includes bibliographical references. / James R. Simpson, Professor Directing Thesis; Joseph J. Pignatiello, Committee Member; Amy Chan Hilton, Committee Member.

Poly(methyl methacrylate) (PMMA) multi-walled carbon nanotubes (MWCNTs) nanocomposites were synthesized by several methods using both pristine and surface functionalized carbon nanotubes (CNTs). Fourier transform infrared (FTIR) spectroscopy was used to characterize the presence and types of functional groups in functionalized CNTs, while the dispersion of CNTs in PMMA was characterized using scanning electron microscopy (SEM). The prepared nanocomposites were foamed using carbon dioxide (CO2) as the foaming agent. The cell morphology was observed by SEM, and the cell size and cell density were calculated via image analysis. It was found that both the synthesis methods and CNTs surface functionalization affect the CNTs dispersion in the polymer matrix, which in turn profoundly influences the cell nucleation mechanism and cell morphology. The CNTs are efficient heterogeneous nucleation agents leading to increased cell density at low particle concentrations. A mixed mode of nucleation mechanism was observed in nanocomposite foams in which polymer rich and particle rich region co-exist due to insufficient particle dispersion. This leads to a bimodal cell size distribution. Uniform dispersion of CNTs can be achieved via synergistic combination of improving synthesis methodology and CNT surface functionalization. Foams from these nanocomposites exhibit single modal cell size distribution and remarkably increased cell density and reduced cell size. An increase in cell density of ~70 times and reduction of cell size of ~80% was observed in nanocomposite foam with 1% CNTs. The effect of CNT surface functionalization on the tensile properties of the PMMA/MWNT nanocomposite and nanocomposite foams were noticed. An increase of ~60% in elastic modulus and ~40% increase in the tensile strength was observed in nanocomposite foam with 0.5 % functionalized CNTs. / A Thesis submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester, 2010. / December 1, 2009. / Polymer Nanocomposite Foams, Microcellular Foams, Carbon Nanotubes / Includes bibliographical references. / Changchun Zeng, Professor Directing Thesis; Zhiyong Liang, Committee Member; Tao Liu, Committee Member.

Lightweight composite actuators with large bending displacement and high blocking force have great potentials for various engineering applications. Carbon nanotube thin film or Buckypaper-based composite actuators (BCAs) have been developed and tested in an open air environment to demonstrate their use as electromechanochemical actuation devices. The actuator is a bimorph structure fabricated with Nafion, a solid electrolyte layer capable of ion diffusion, sandwiched between two buckypaper (BP) electrode layers. Actuation mechanisms were studied, revealing that ionic current flow is the major actuation mechanism. To further improve actuation performance, Nafion doping has been studied. LiCl and Imidazolium (IL) solutions have been used to dope the Nafion and both cases have demonstrated substantial increases of BCA displacement. With the dimensions of the BCA held constant(30 mm × 5 mm × 0.07 mm), a non-doped BCA with a 3 V stimulation input at 200 mHz only can generate a total bilateral displacement of up to 0.09 mm; but LiCl-doped and IL-doped BCAs can produce ×100 and ×150 more displacement than that of the non-doped BCAs, respectively. The effect of driving voltages and frequencies with respect to displacement and blocking force generation of IL-doped BCAs were characterized. BCA thickness variation was introduced to evaluate the effect of the BCA structure on actuation performance. The improved BCAs have achieved a maximum strain and stress of 0.1% and 0.175 MPa, respectively. This is comparable to other polymer-based actuators. Finally, a preliminary model of BCA blocking force estimation was proposed to predict and further optimize the BCA actuation properties. The predicted results of the model are in agreement with the experimental data. / A Thesis submitted to the Department of Industrial Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester, 2010. / June 11, 2010. / Nanotube, Buckypaper, Actuator, Blocking Force, Conductive Polymers / Includes bibliographical references. / Richard Liang, Professor Directing Thesis; Chuck Zhang, Committee Member; William Oates, Committee Member.

With the advancement in technology and the constant need for optimization, a lot of resources are directed towards analyzing information collected. This information is in the form of large amounts of data that is gathered at every instant. The analysis of this data is often expressed in the form of linear system equations, where the size of the equations increases proportionally to the size of the data. Many methods have been developed to solve these systems. The main challenge in solving such large systems is to get an accurate solution along with computational eciency. The goal of this thesis is to develop a method which addresses both accuracy and computational eciency in solving large-scale linear systems. Our method will improve existing iterative techniques particularly for a linear equation system i.e. Ax = b where A is a positive denite and sparse full rank matrix. Linear systems of such kinds are commonly found in applications of Spatial regression. Hence, we will be using spatial data available publicly to test our method and present results of our method in this thesis. / A Thesis submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester 2016. / April 1, 2016. / Gauss Seidel method, Iterative methods, linear system, sparse symmetric data, Spatial data / Includes bibliographical references. / Chiwoo Park, Professor Directing Thesis; Abhishek K. Shrivastava, Committee Member; Arda Vanli, Committee Member.

Health condition monitoring and failure detection play a crucial role in estimating the performance of solar panels such as degradation trend over time and occurrence of failures. Monitoring and detecting significant degradation can help solar panel owners establish as-needed maintenance strategies on a timely manner. But in some occasions, degradation trend estimation becomes challenging due to limited availability of training data such as many missing observations in time series over a large time span and a lack of history of failure records that are sufficient to establish statistical models. To fill the gap, this thesis proposes a new approach of iterative multi-task learning of Gaussian process in time series data (MTL-GP-TS) by sharing information among similar-but-not-identical datasets from multiple solar panel locations. The proposed MTL-GP-TS model learns unobserved or missing values in a particular time series dataset to forecast the future trend with autoregressive integrated moving average (ARIMA) model, resulting in substantial improvement of forecast over conventional time series modeling approaches. Moreover, the estimated degradation trend with proposed MTL-GP-TS method has the potential to improve the monitoring of significant performance degradation compared with the conventional time series model. This thesis also studies the effect of temporal dependent weather factors on the solar panel performance by integrating a covariate with the MTL-GP-TS algorithm. A case study has demonstrated that inclusion of weather factors into the monitoring of degradation with PV-Weather data integration model can significantly improve the solar panel performance prediction. / A Thesis submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester 2016. / April 12, 2016. / Forecasting and monitoring, Multi-task learning, Solar panels, Time series / Includes bibliographical references. / Hui Wang, Professor Directing Thesis; Mei Zhang, Committee Member; Abhishek K. Shrivastava, Committee Member.

A major challenge to the study of the structure-property relationship of carbon nanotube (CNT) networks is to characterize the complex nanostructure with complicated nanoscale contacts and pore structures. An image-based characterization methodology was proposed to extract CNT network information directly from scanning electron microscope (SEM) images of various CNT thin films to characterize critical topological factors including bundle size, diameter, and orientation from the CNT networks. This approach provided high-fidelity and fast analysis of CNT network structures with low false positive rate (FPR) of ~3% and ~90% accuracy in most of our case studies. We applied the new approach to study different networks of multi-walled carbon nanotube (MWNT), single-walled carbon nanotube (SWNT), MWNT-SWNT mixed, and stretched MWNTs with different CNT alignments, which revealed the electrical conductivity-structure relationships of MWNT networks. On the other hand, controlling the transfer of electrical and mechanical properties of nanotubes into nanocomposites remains one of the major challenges due to the lack of adequate measurement systems to quantify the variations in bulk properties while the nanotubes were used as the reinforcement material. One-way analysis of variance (ANOVA) on thickness and conductivity measurements were conducted. By analyzing the data collected from both experienced and inexperienced operators, we found some operation details users might overlook that resulted in variations, since conductivity measurements of CNT thin films are very sensitive to thickness measurements. In addition, we demonstrated how issues in measurements damaged samples and limited the number of replications resulting in large variations in the electrical conductivity measurement results. Based on this study, we proposed a faster, more reliable approach to measure the thickness of CNT thin films that operators can follow to make these measurement processes less dependent on operator skills. / A Dissertation submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2015. / June 6, 2015. / Includes bibliographical references. / Zhiyong (Richard) Liang, Professor Co-Directing Dissertation; Chiwoo Park, Professor Co-Directing Dissertation; Petru Andrei, University Representative; Mei Zhang, Committee Member.

Establishing accurate processing models to characterize and study the suspension preparation for manufacturing carbon nanotube (CNT) thin films or buckypaper (BP) is a challenging task. Acquiring a fundamental understanding of quantifiable dispersion quality and time-dependent dispersion quality changes during and after the dispersion processes of CNT suspensions are critical for many suspension-based CNT manufacturing processes. In this research, a novel in-line dispersion quality monitoring system was developed. The monitoring was carried out using an integration of dynamic light scattering (DLS) and UV-Vis spectroscopy of a continuous flow during the CNT sonication dispersion process. This system can provide real-time monitoring of the quality of the suspension during the dispersion process and the stability of the suspension at post-dispersion stage. Monitoring the actual particle-size distribution can help determine the effective dispersion time and post-dispersion shelf life for potential use in process control and optimizing for scale-up manufacturing processes. We studied different CNT suspension systems, including MWNTs, SWNTs, graphene nanoplates, and their mixtures. For longer MWNTs with smaller diameters, the dispersion process achieved a steady agglomerate size around 100 nm with 40 minutes of sonication; for shorter and larger diameter MWNTs, due to their more packed agglomerate density, it took 60 minutes of sonication to reach the 100 nm agglomerate size. At the post-dispersion stage, the stability of CNT suspension showed nonlinear behavior due to the thermodynamic activity of CNT agglomerates. Under refrigerated storage condition, the increase of agglomerate size was reduced and the process of the CNT re-aggregation was prolonged by more than five times of the shelf life compared to the samples stored under room temperature. The study of dispersion of the carbon nanomaterial mixtures showed that MWNTs had helped the dispersion of SWNTs and graphene nanoplates throughout the sonication process to achieve a smaller agglomerate size after 75 minutes sonication. Quantitative quality baselines of the individual nanomaterials were established and used for controlling and optimizing the dispersion process and evaluating suspension stability. The dispersion mechanisms of different materials can be compared through the monitoring system. / A Dissertation submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2016. / May 19, 2016. / Carbon Nanotube, Dispersion, Process monitoring, Suspension / Includes bibliographical references. / Zhiyong Richard Liang, Professor Directing Dissertation; Lisa Spainhour, University Representative; Arda Vanli, Committee Member; Changchun Chad Zeng, Committee Member.

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