Development of Immunoassay Using Graphene and Microfluidic Platforms.

Protein, as one of the most important functional biomolecules in the human body, plays a significant role in physiological responses and molecular diagnostics. Detecting the existence of proteins, quantifying concentration, and identifying protein types are therefore important techniques in many fields. Immunoassays are one of the major techniques relied on for protein detection. Immunoassays have been broadly applied in disease diagnosis, pharmaceutical development, food science, and environmental protection. The first part of this dissertation describes studies aimed at developing chemical vapor deposition (CVD) graphene as a large size protein biosensing platform. To utilize graphene as a biosensing platform, techniques to immobilize proteins on graphene are critical. In this dissertation work, carboxyl functional groups (-COOH) were created by graphene functionalization, and the functionalized graphene was characterized using Raman spectroscopy, X-ray photo spectroscopy (XPS), and fluorescence microscopy. The approach developed here provides information about protein coupling density and uniformity on large scale graphene (> cm2). The second and the third parts of the thesis describe the application of a microfluidic technique to two widely used protein detection methods – immunoblotting and dot blotting. The microfluidic systems were designed and fabricated to be easily interfaced with a common type of protein blotting membrane called polyvinylidene fluoride (PVDF) membrane. The microfluidic device was specifically applied to the antibody incubation step, which reduces antibody consumption and therefore also significantly reduces the cost of the assay. In microfluidic immunoblotting, an approach to activate the PVDF membrane to increase its protein binding capacity was developed. This was achieved by adding a surfactant Tween-20 to the antibody solution. The concentration of Tween-20 was optimized so that only the portion of the membrane within the channel region was activated. The system has been shown to be able to profile inflammatory signaling pathways. In microfluidic dot blotting, the influence of substrate hydrophobicity and protein concentrations on device design constraints were studied. Inflammatory cytokine detection using the developed microfluidic dot blotting system was determined. Altogether these experiments demonstrate that applying microfluidic techniques to protein immunoblotting and dot blotting improves detection efficiency, and reduces cost by utilizing less antibodies.PhDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113501/1/huaining_1.pd

Computer Aided Design of Side Actions for Injection Molding of Complex Parts

Often complex molded parts include undercuts, patches on the part boundaries that are not accessible along the main mold opening directions. Undercuts are molded by incorporating side actions in the molds. Side actions are mold pieces that are removed from the part using translation directions different than the main mold opening direction. However, side actions contribute to mold cost by resulting in an additional manufacturing and assembly cost as well as by increasing the molding cycle time. Therefore, generating shapes of side actions requires solving a complex geometric optimization problem. Different objective functions may be needed depending upon different molding scenarios (e.g., prototyping versus large production runs). Manually designing side actions is a challenging task and requires considerable expertise. Automated design of side actions will significantly reduce mold design lead times. This thesis describes algorithms for generating shapes of side actions to minimize a customizable molding cost function. Given a set of undercut facets on a polyhedral part and the main parting direction, the approach works in the following manner. First, candidate retraction space is computed for every undercut facet. This space represents the candidate set of translation vectors that can be used by the side action to completely disengage from the undercut facet. As the next step, a discrete set of feasible, non-dominated retractions is generated. Then the undercut facets are grouped into undercut regions by performing state space search over such retractions. This search step is performed by minimizing the customizable molding cost function. After identifying the undercut regions that can share a side action, the shapes of individual side actions are computed. The approach presented in this work leads to practically an optimal solution if every connected undercut region on the part requires three or fewer side actions. Results of computational experiments that have been conducted to assess the performance of the algorithms described in the thesis have also been presented. Computational results indicate that the algorithms have acceptable computational performance, are robust enough to handle complex part geometries, and are easy to implement. It is anticipated that the results shown here will provide the foundations for developing fully automated software for designing side actions in injection molding

Algorithms for generating multi-stage molding plans for articulated assemblies

Plastic products such as toys with articulated arms, legs, and heads are traditionally produced by first molding individual components separately, and then assembling them together. A recent alternative, referred to as in-mold assembly process, performs molding and assembly steps concurrently inside the mold itself. The most common technique of performing in-mold assembly is through multi-stage molding, in which the various components of an assembly are injected in a sequence of molding stages to produce the final assembly. Multi-stage molding produces better-quality articulated products at a lower cost. It however, gives rise to new mold design challenges that are absent from traditional molding. We need to develop a molding plan that determines the mold design parameters and sequence of molding stages. There are currently no software tools available to generate molding plans. It is difficult to perform the planning manually because it involves evaluating large number of combinations and solving complex geometric reasoning problems. This dissertation investigates the problem of generating multi-stage molding plans for articulated assemblies. The multi-stage molding process is studied and the underlying governing principles and constraints are identified. A hybrid planning framework that combines elements from generative and variant techniques is developed. A molding plan representation is developed to build a library of feasible molding plans for basic joints. These molding plans for individual joints are reused to generate plans for new assemblies. As part of this overall planning framework, we need to solve the following geometric subproblems -- finding assembly configuration that is both feasible and optimal, finding mold-piece regions, and constructing an optimal shutoff surface. Algorithms to solve these subproblems are developed and characterized. This dissertation makes the following contributions. The representation for molding plans provides a common platform for sharing feasible and efficient molding plans for joints. It investigates the multi-stage mold design problem from the planning perspective. The new hybrid planning framework and geometric reasoning algorithms will increase the level of automation and reduce chances of design mistakes. This will in turn reduce the cost and lead-time associated with the deployment of multi-stage molding process

Procedimiento para el análisis automatizado de la manufactura de la pieza de plástico y del molde de inyección

El proceso de manufactura mediante moldes de inyección de plástico es uno de los métodos de producción más versátiles y extendidos para la fabricación de piezas de plástico. Actualmente, existe una amplia variedad de software tipo CAD/CAE/CAM para el análisis y diseño asistido de piezas de plástico y moldes de inyección. Sin embargo, estas herramientas comerciales aún requieren de interacción humana y acceso a información geométrica interna de la pieza de plástico vinculada a su modelo CAD. La presente tesis doctoral propone una metodología universal basada en algoritmos automatizados de tipo geométrico – experto que, mediante el análisis de la geometría discreta de la pieza de plástico (malla en formato discreto definida por los elementos notables nodos y facetas), mejore y optimice el proceso actual de análisis, diseño y dimensionamiento del molde de inyección, sin recurrir a técnicas heurísticas e interacción manual por parte del usuario.Plastic injection molding is one of the most versatile and widespread manufacturing process for the plastic parts manufacture. Nowadays, there is a wide variety of CAD/CAE/CAM type software for the analysis and aided design of plastic parts and injection molds. However, these commercial tools still require human interaction and access to internal geometric information (geometric features) of the plastic part linked to their CAD model. The present PhD thesis proposes a universal methodology based on automated geometrical - expert algorithms that, by means of the analysis of the plastic part discrete geometry (mesh in discrete format defined by notable elements nodes and facets), improve and optimize the current analysis, design and dimensioning process of the injection mold, without resorting to heuristic techniques and manual interaction by the user.Tesis Univ. Jaén. Departamento Ingeniería Gráfica, Diseño y Proyectos. Leída el 3 de mayo de 2019

Fabrication of Nanotopographic Ophthalmic Device

Corneal disease is the second most prevalent cause of blindness in the world. Keratoplasty or corneal transplant is available as the last treatment resort and extended drug delivery following the procedure are preferred to be delivered by a drug eluting contact lens. Patients using either device in the wounded eye are prone to microbial infection that could complicate the outcome of the sight recovery. Thus, nanotopography, a physical surface modification studied to have potential antimicrobial effect and wound healing promotion, is considered to be integrated in novel design of both devices. Due to the spherical nature of the eye, conventional nanotechnology could not produce such surface, or requires heavy cost and resources. In this thesis, I : 1) improve a nanopatterning technique for spherical surface and apply it on a novel cornea device, 2) validate its biological responses in vivo, 3) apply the patterning technique for a contact lens design with a new class of material, 4) analyze the economic and commercial benefits of both device in current ophthalmic market. This thesis consists universal protocol for adaptive patterning methods on various material platform and outline validation method for future regulatory works. This thesis shall set the foundation for a medical device startups that could restore sights for millions around the world

Mold Feature Recognition using Accessibility Analysis for Automated Design of Core, Cavity, and Side-Cores and Tool-Path Generation of Mold Segments

Injection molding is widely used to manufacture plastic parts with good surface finish, dimensional stability and low cost. The common examples of parts manufactured by injection molding include toys, utensils, and casings of various electronic products. The process of mold design to generate these complex shapes is iterative and time consuming, and requires great expertise in the field. As a result, a significant amount of the final product cost can be attributed to the expenses incurred during the product’s design. After designing the mold segments, it is necessary to machine these segments with minimum cost using an efficient tool-path. The tool-path planning process also adds to the overall mold cost. The process of injection molding can be simplified and made to be more cost effective if the processes of mold design and tool-path generation can be automated. This work focuses on the automation of mold design from a given part design and the automation of tool-path generation for manufacturing mold segments. The hypothesis examined in this thesis is that the automatic identification of mold features can reduce the human efforts required to design molds. It is further hypothesised that the human effort required in many downstream processes such as mold component machining can also be reduced with algorithmic automation of otherwise time consuming decisions. Automatic design of dies and molds begins with the part design being provided as a solid model. The solid model of a part is a database of its geometry and topology. The automatic mold design process uses this database to identify an undercut-free parting direction, for recognition of mold features and identification of parting lines for a given parting direction, and for generation of entities such as parting surfaces, core, cavity and side-cores. The methods presented in this work are analytical in nature and work with the extended set of part topologies and geometries unlike those found in the literature. Moreover, the methods do not require discretizing the part geometry to design its mold segments, unlike those found in the literature that result in losing the part definition. Once the mold features are recognized and parting lines are defined, core, cavity and side-cores are generated. This work presents algorithms that recognize the entities in the part solid model that contribute to the design of the core, cavity and side-cores, extract the entities, and use them in the design of these elements. The developed algorithms are demonstrated on a variety of parts that cover a wide range of features. The work also presents a method for automatic tool-path generation that takes the designed core/cavity and produces a multi-stage tool-path to machine it from raw stock. The tool-path generation process begins by determining tool-path profiles and tool positions for the rough machining of the part in layers. Typically roughing is done with large aggressive tools to reduce the machining time; and roughing leaves uncut material. After generating a roughing tool-path for each layer, the machining is simulated and the areas left uncut are identified to generate a clean-up tool-path for smaller sized tools. The tool-path planning is demonstrated using a part having obstacles within the machining region. The simulated machining is presented in this work. This work extends the accessibility analysis by retaining the topology information and using it to recognize a larger domain of features including intersecting features, filling a void in the literature regarding a method that could recognize complex intersecting features during an automated mold design process. Using this information, a larger variety of new mold intersecting features are classified and recognized in this approach. The second major contribution of the work was to demonstrate that the downstream operations can also benefit from algorithmic decision making. This is shown by automatically generating roughing and clean-up tool-paths, while reducing the machining time by machining only those areas that have uncut material. The algorithm can handle cavities with obstacles in them. The methodology has been tested on a number of parts

Manufacturability analysis for non-feature-based objects

This dissertation presents a general methodology for evaluating key manufacturability indicators using an approach that does not require feature recognition, or feature-based design input. The contributions involve methods for computing three manufacturability indicators that can be applied in a hierarchical manner. The analysis begins with the computation of visibility, which determines the potential manufacturability of a part using material removal processes such as CNC machining. This manufacturability indicator is purely based on accessibility, without considering the actual machine setup and tooling. Then, the analysis becomes more specific by analyzing the complexity in setup planning for the part; i.e. how the part geometry can be oriented to a cutting tool in an accessible manner. This indicator establishes if the part geometry is accessible about an axis of rotation, namely, whether it can be manufactured on a 4th-axis indexed machining system. The third indicator is geometric machinability, which is computed for each machining operation to indicate the actual manufacturability when employing a cutting tool with specific shape and size. The three manufacturability indicators presented in this dissertation are usable as steps in a process; however they can be executed alone or hierarchically in order to render manufacturability information. At the end of this dissertation, a Multi-Layered Visibility Map is proposed, which would serve as a re-design mechanism that can guide a part design toward increased manufacturability

The effect of polymer grafting in the dispersibility of alumina/polysulfone nanocomposites

γ-Alumina nanoparticles have been modified with polysulfone (PSU) chains via 1,3-dipolar cycloaddition reaction between functionalized alumina with vinyl groups and terminal azide polysulfone chains of two different molecular weights. Homopolymer nanocomposites have been prepared for the first time by extrusion and microinjection. The effectiveness of the grafts on the dispersiblity has been analyzed in terms of the parameters that govern the wettability between grafted and matrix chains: graft density (σ), graft molecular weight (N) at constant matrix molecular weight (P). The dispersion state and interfacial adhesion of PSU grafted-nanoparticles have been evaluated from laser scanning confocal, FESEM and SEM microscopy. Results show that the incorporation of the modified g-alumina improves the dispersion state in comparison with bare alumina nanoparticles, reducing the average particle size from 5±9 to 1.3±1 microns. Although aggregates are still present the size of the aggregates are also substantially reduced even with low or moderate graft density used in this work, but further improves the interfacial adhesion between nanoparticle and matrix when long PSU chains are grafted even with low-moderate grafting density. These results can be explained by enthalpic compatibility between polysulfone grafted layer and host polysulfone matrix.Authors wish to acknowledge funding from Spanish Ministerio de Economía y Competitividad under grant MAT2014-57557-R. Authors also thank to I. García and A. Cervera from Euroortodoncia for their invaluable help in nanocomposite processing

A heuristic algorithm for determining the part set in a powder-bed additive manufacturing machine.

The goal of this research is to develop a procedure for the placement of a priority part into a planned build in a powder-bed additive manufacturing machine. Toward that goal, a heuristic procedure was developed that seeks to maximize the revenue in a scheduled build, subject to due-date constraints; i.e., all parts with the closest due date will not only be included in the build, but will be placed near the bottom of the build. Likewise, any part in the scheduled build that does not have an immediate due date is a candidate for removal in order to accommodate a higher priority part, the order for which arrives after the build is underway. The build volume for this experiment with the SLS2500+ machine is 13-inch x 15-inch x 18-inch rectilinear container. To achieve this optimization of the build, the experiment for this research involved a penalty which is based on failure to meet the due date constraint. The m parts in the build are placed such that are placed the highest priority parts, including those with immediate due date constraints, are positioned near the bottom of the build volume. The focus of this study is to determine which “unbuilt” parts x(i) will be removed to make room for higher priority parts. Toward that end, each part is assigned a priority p(i), i = 1, …,m until the build is full. If an order for a part having a higher priority p(i)than any of the parts in the build, the procedure developed here seeks to replace at least one of the parts in the scheduled build. Hence, the dimensions of the lower priority parts are key, since the part that is removed must provide sufficient space for the new part. Importantly, the enactment of the procedure developed here takes place in real time, with little or no interruption of the progress of the build. The resulting Excel file will be sorted as to place the immediate items at the bottom on the build. The solution is valid for a single and also for a multiple build. Simulations of this heuristic procedure were shown to substantially increase the revenue desired from the planned build by adding higher priority parts