There is a link between the thermal and electrical properties of metal. The equation which links these two properties is called the Wiedemann-Franz Law. Also there is an emerging technology within Additive Manufacturing called Binder Jet Printing which can print high purity copper without heat stress within the material. Due to the Binder Jet Printings ability to print high resolution prints without any print through, this makes future use of this technology a necessity for future electrical and thermal components within computers . However a thermal and electrical conductivity analysis of binder jetted copper has never been performed, and needs to be for simulation with this material. Therefore within this thesis the relationship of the thermal and electrical properties of printed binder jetted copper part will be researched. To find the electrical resistivity of binder jetted copper, three sets of 2mm diameter rods where printed and then placed within a modified four wire resistance method test. For the thermal conductivity measurements a laser flash diffusivity machine was used, and three sets of 11 copper disks of approximately 1cm diameter by 1mm where printed. The data shows a strong linear trend linking electrical resistivity to the density ratio of the copper. Within the thermal conductance measurement, a lot more variability was seen within the three different prints. The 70% density ratio prints saw a large 13% spread in density ratios throughout the prints, which is believed to be caused by improper sintering due to temperature gradients near the door of the kiln. The 82% density prints saw better grouping of density ratios by placing the specimens in the back of the kiln. Lastly, the 92% prints saw the best density ratio grouping but the largest thermal conductivity variance. Even though the scatter plot for the thermal conductivity measurements are not as precise as the electrical resistivity measurements, it still shows a linear trend which matches the NASA data from 1971. Overall, these linear trends can be modeled and compiled into a new form of the Wiedemann-Franz law, which accounts for the density ratio of the binder jetted print. / Master of Science

Medical practitioners rely heavily on visualization of medical imaging to get a better understanding of the patient's anatomy. Most cancer treatment and surgery today are performed using medical imaging. Medical imaging is therefore of great importance to the medical industry. Medical imaging continues to depend heavily on a series of 2D scans, resulting in a series of 2D photographs being displayed using light boxes and/or computer monitors. Today, these 2D images are increasingly combined into 3D solid models using software. These 3D models can be used for improved visualization and understanding of the problem at hand, including fabricating physical 3D models using additive manufacturing technologies. Generating precise 3D solid models automatically from 2D scans is non-trivial. Geometric and/or topologic errors are common, and often costly manual editing is required to produce 3D solid models that sufficiently reflect the actual underlying human geometry. These errors arise from the ambiguity of converting from 2D data to 3D data, and also from inherent limitations of the .STL fileformat used in additive manufacturing. This thesis proposes a new, robust method for automatically generating 3D models from 2D scanned data (e.g., computed tomography (CT) or magnetic resonance imaging (MRI)), where the resulting 3D solid models are specifically generated for use with additive manufacturing. This new method does not rely on complicated procedures such as contour evolution and geometric spline generation, but uses volume reconstruction instead. The advantage of this approach is that the original scan data values are kept intact longer, so that the resulting surface is more accurate. This new method is demonstrated using medical CT data of the human nasal airway system, resulting in physical 3D models fabricated via additive manufacturing. / Master of Science

Digital light Projection based Additive Manufacturing (AM) enables fabrication of complex three-dimensional (3D) geometries for applications ranging from rapid prototyping jet parts to scaffolds for cell cultures. Despite the ability in producing complex, three-dimensional architectures, the state of art DLP AM systems is limited to a single homogenous photo-polymer and it requires a large volume of resin bath to begin with. Extensible Multi-material Stereolithography (EMSL) is a novel high-resolution projection stereolithography system capable of manufacturing hybrid 3D objects. This system provides new capabilities, allowing more flexible design criteria through the incorporation of multiple feedstock materials throughout the structure. With EMSL manufacturing ability, multi-material programmable negative Poissons ratio honeycomb reentrant structures are realized. Researchers have been studying auxetic structures over decades, the mechanical property control of auxetic structure mainly relies on geometry design in previous studies. Now with the help of EMSL system, other design variables associated with auxetic structures, such as material properties of local structural members, are added into design process. The additional variables are then proved to have significant effects on the material properties of the auxetic structures. The ability to accurately manufacture multi-material digital design will not only allow for novel mechanical and material researches in laboratory, but also extend the additive manufacturing technology to numerous future applications with characteristics such as multiple electrical, electromechanical and biological properties. The design and optimization of EMSL system realizes novel structures have not been producible, therefore it will stimulate new possibilities for future additive manufacturing development. / Master of Science

The layer-by-layer nature of additive manufacturing (AM) allows for access to the entire build volume of a component during manufacture including the internal structure. Voids are accessible during the build process and allow for components to be embedded and sealed with subsequently printed layers. This process, in conjunction with direct write (DW) of conductive materials, enables the direct manufacture of parts featuring embedded electronics, including interconnects and sensors. The scope of previous works in which DW and AM processes are combined has been limited to single material AM processes. The PolyJet process is assessed for hybridization with DW because of its multi-material capabilities. The PolyJet process is capable of simultaneously depositing different materials, including rigid and elastomeric photopolymers, which enables the design of flexible features such as membranes and joints. In this work, extrusion-based DW is integrated with PolyJet AM technology to explore opportunities for embedding conductive materials on rigid and elastomeric polymer substrates. Experiments are conducted to broaden the understanding of how silver-loaded conductive inks behave on PolyJet material surfaces. Traces of DuPont 5021 conductive ink as small as 750?m wide and 28?m tall are deposited on VeroWhite+ and TangoBlack+ PolyJet material using a Nordson EFD high-precision fluid dispenser. Heated drying at 55°C is found to accelerate material drying with no significant effect on the conductor's geometry or conductivity. Contact angles of the conductive ink on PolyJet substrates are measured and exhibit a hydrophilic interaction, indicating good adhesion. Encapsulation is found to negatively impact conductivity of directly written conductors when compared to traces deposited on the surface. Strain sensing components are designed to demonstrate potential and future applications. / Master of Science

Effective quality improvement in the manufacturing industry is continually pursued. There is an increasing demand for real-time fault detection, and avoidance of destructive post-process testing. Therefore, it is desirable to employ sensors for in-process monitoring, allowing for real-time quality assurance. Chapter 3 describes the application of sensor based monitoring to additive manufacturing, in which sensors are attached to a desktop model fused deposition modeling machine, to collect data during the manufacturing process. A design of experiments plan is conducted to provide insight into the process, particularly the occurrence of process failure. Subsequently, machine learning classification techniques are applied to detect such failure, and successfully demonstrate the future potential of this platform and methodology. Chapter 4 relates the application of online, image-based quantification of the surface quality of workpieces produced by cylindrical turning. Representative samples of cylindrical shafts, machined by turning under various conditions, are utilized, and an apparatus is constructed for acquiring images while the part remains mounted on a lathe. The surface quality of these specimens is analyzed, employing an algebraic graph theoretic approach, and preliminary regression modeling displays an average surface roughness (Ra) prediction error of less than 8%. Prediction occurs in less than 2 seconds, showing the capability for future application in a real-time, quality control setting. Both of these cases, in additive manufacturing and in turning, are validated using real experimental data and analysis, showing application of sensor-based online process monitoring in multiple manufacturing areas. / Master of Science

A quantitative understanding of thermal field evolution is vital for quality control in additive manufacturing (AM). Because of the unknown material parameters, high computational costs, and imperfect understanding of the underlying science, physically-based approaches alone are insufficient for component-scale thermal field prediction. Here, I present a new framework that integrates physically-based and data-driven approaches with quasi in situ thermal imaging to address this problem. The framework consists of (i) thermal modeling using 3D finite element analysis (FEA), (ii) surrogate modeling using functional Gaussian process, and (iii) Bayesian calibration using the thermal imaging data. Based on heat transfer laws, I first investigate the transient thermal behavior during AM using 3D FEA. A functional Gaussian process-based surrogate model is then constructed to reduce the computational costs from the high-fidelity, physically-based model. I finally employ a Bayesian calibration method, which incorporates the surrogate model and thermal measurements, to enable layer-to-layer thermal field prediction across the whole component. A case study on fused deposition modeling is conducted for components with 7 to 16 layers. The cross-validation results show that the proposed framework allows for accurate and fast thermal field prediction for components with different process settings and geometric designs. / Master of Science / This paper aims to achieve the layer to layer temperature monitoring and consequently predict the temperature distribution for any new freeform geometry. An engineering statistical synergistic model is proposed to integrate the pure statistical methods and finite element modeling (FEM), which is physically meaningful as well as accurate for temperature prediction. Besides, this proposed synergistic model contains geometry information, which can be applied to any freeform geometry. This paper serves to enable a holistic cyber physical systems-based approach for the additive manufacturing (AM) not only restricted in fused deposition modeling (FDM) process but also can be extended to powder-based process like laser engineered net shaping (LENS) and selective laser sintering (SLS). This paper as well as the scheduled future works will make it affordable for customized AM including customized geometries and materials, which will greatly accelerate the transition from rapid prototyping to rapid manufacturing. This article demonstrates a first evaluation of engineering statistical synergistic model in AM technology, which gives a perspective on future researches about online quality monitoring and control of AM based data fusion principles.

Additive Manufacturing (AM) is a unique method of fabrication that, in contrast to traditional manufacturing methods, builds objects layer by layer. The ability of AM (when partnered with 3D scanning) to clone physical objects has raised concerns in the area of intellectual property (IP). To address this issue, the goal of this dissertation is to characterize and model a method to incorporate unique security features within AM builds. By adding optically detectable nanoparticles into transparent AM media, Physical Unclonable Function (PUFs) can be embedded into AM builds and serve as an anti-counterfeiting measure. The nanoparticle selected for this work is a Quantum Dot (QD), which absorbs UV light and emits light in the visible spectrum. This unique interaction with light makes the QDs ideal for a security system since the challenge (UV light) is a different signal from the response (the visible light emitted by the QDs). PolyJet, the AM process selected for this work, utilizes inkjet to deposit a photopolymer into layers, which are then cured with a UV light. An investigation into the visibility of the QDs within the printed PolyJet media revealed that the QDs produce PUF patterns visible via fluorescent microscopy. Furthermore, rheological data shows that the ink-jetting properties of the printing media are not significantly affected by QDs in sufficient concentrations to produce PUFs. The final objective of this study is to characterize the effects of the QDs on photocuring. The mathematical model to predict the critical exposure of the QD-doped photopolymer utilizes light scattering theory, QD characterization results, and photopolymer-curing characterization results. This mathematical representation will contribute toward the body of knowledge in the area of Additive Manufacturing of nanomaterials in photopolymers. Overall, this work embodies the first investigations of the effects of QDs on rheological characteristics of ink-jetted media, the effects of QDs on curing of AM photopolymer media, visibility of nanoparticles within printed AM media, and the first attempt to incorporate security features within AM builds. Finally, the major scientific contribution of this work is the theoretical model developed to predict the effects of QDs on the curing properties of AM photopolymers. / Ph. D.

Projection Stereolithography (PSL) is an Additive Manufacturing process that digitally patterns light to selectively expose and layer photopolymer into three dimensional objects. Nanomaterials within the photopolymer are therefore embedded inside fabricated objects. Adding varying concentrations of multi-walled carbon nanotubes (MWCNT) to the photopolymer may allow for the engineering of an objects tensile strength and electric conductivity. This research has two goals (i) the fabrication of three-dimensional structures using PSL and (ii) the material characterization of nanocomposite photopolymers. A morphological matrix design tool was developed and used to categorically analyze published PSL systems. These results were used to justifying design tradeoffs during the design and fabricate of a new PSL system. The developed system has 300μm resolution, 45mm x 25mm fabrication area, 0.23mW/cm2 intensity, and 76.2mm per hour vertical build rate. Nanocomposite materials were created by mixing Objet VeroClear FullCure 810 photopolymer with 0.1, 0.2, and 0.5 weight percent MWCNT using non-localized bath sonication. The curing properties of these nanocomposite mixtures were characterized; adding 0.1 weight-percent MWCNT increases the critical exposure by 10.7% and decreases the depth of penetration by 40.1%. The material strength of these nanocomposites were quantified through tensile testing; adding 0.1 weight-percent MWCNT decreases the tensile stress by 45.89%, the tensile strain by 33.33%, and the elastic modulus by 28.01%. Higher concentrations always had exaggerated effects. Electrical conductivity is only measurable for the 0.5 weight-percent nanocomposite with a 8k/mm resistance. The 0.1 weight-percent nanocomposite was used in the PSL system to fabricate a three-dimensional nanocomposite structure. / Master of Science

Additive manufacturing introduces a new design paradigm that allows the fabrication of geometrically complex parts that cannot be produced by traditional manufacturing and assembly methods. Using a cellular heat exchanger as a motivational example, this thesis investigates the creation of a hybrid manufacturing approach that combines selective laser sintering with an electroforming process to produce complex, hollow, metal geometries. The developed process uses electroless nickel plating on laser sintered parts that then undergo a flash burnout procedure to remove the polymer, leaving a complex, hollow, metal part. The resulting geometries cannot be produced directly with other additive manufacturing systems. Copper electroplating and electroless nickel plating are investigated as metal coating methods. Several parametric parts are tested while developing a manufacturing process. Copper electroplating is determined to be too dependent on the geometry of the part, with large changes in plate thickness between the exterior and interior of the tested parts. Even in relatively basic cellular structures, electroplating does not plate the interior of the part. Two phases of electroless nickel plating combined with a flash burnout procedure produce the desired geometry. The tested part has a density of 3.16g/cm3 and withstands pressures up to 25MPa. The cellular part produced has a nickel plate thickness of 800µm and consists of 35% nickel and 65% air (empty space). Detailed procedures are included for the electroplating and electroless plating processes developed. / Master of Science

One emerging application of additive manufacturing is building parts with embedded electronics, but the thermal management of these assemblies is a potential issue. Electrical components have efficiency losses, and a significant portion of that lost energy is converted into heat. Embedding electronics in PolyJet parts is of particular interest since material jetting additive manufacturing has the ability to deposit multiple, functionally graded materials on a pixel by pixel basis. Although there is existing literature on other PolyJet material properties, there is limited research on their thermal characterization. The goal of this work is to determine the thermal conductivities of select PolyJet photopolymers (VeroWhitePlus, TangoBlackPlus, and Grey60) by using the heat flow meter method. The resulting thermal conductivities are then applied in finite element analysis (FEA) simulations to model the thermal distribution of heated PolyJet parts. Two FEA models of one-dimensional conduction in PolyJet parts are defined and compared to a corresponding physical model to verify the thermal conductivity measurements; one simulation expresses thermal conductivity as a function of temperature and the other uses an average value of thermal conductivity. The thermal conductivities were determined for a range of temperatures, and the average values were 0.2376 W/(m•K), 0.2307 W/(m•K), and 0.2272 W/(m•K) for VeroWhitePlus, TangoBlackPlus, and Grey60, respectively. When applying the thermal conductivity results to an FEA model, it was concluded that defining thermal conductivity as a function of temperature (as opposed to a constant value), reduced the average error in the predicted temperatures by less than 1%. / Master of Science