Material Extrusion additive manufacturing (MEX) represents the most widely implemented form of additive manufacturing due to its high performance-cost ratio and robustness. Being an extrusion process in its essence, this process enables the free form fabrication of a wide range of thermoplastic materials. However, in most typical MEX processes, only amorphous polymers are being used as feedstock material owing to their smaller dimensional shrinkage during cooling and well-stablished process/structure/property (P/S/P) relationship. Semi-crystalline polymers, with their crystalline nature, possess unique properties such as enhanced mechanical properties and improved chemical resistance. However, due to the inherent processing challenges in MEX of semi-crystalline polymers, the P/S/P relationships are much less established, thus limits the application of semi-crystalline polymers in MEX. The overall aim of this thesis is to advance the understanding of P/S/P relationship of semi-crystalline polymers in MEX. This is accomplished through both experimental and simulation-based research. With a typical commodity semi-crystalline polymer, Poly (ethylene terephthalate) (PET), selected as the benchmark material. First, we experimentally explored the MEX printing of both neat and glass fiber (GF) reinforced recycled PET (rPET). Excellent MEX printability were shown for both neat and composite materials, with GF reinforced parts showing a significant improved mechanical property. Notably, a gradient of crystallinity induced by a different toolpathing time was highlighted. In the second project, to further investigate the impact of MEX parameter on crystallinity and mechanical properties, a series of benchmark parts were printed with neat PET and analyzed. The effect of part design and MEX parameter on thermal history during printing was revealed though a comparative analysis of IR thermography. Subsequent Raman spectroscopy and mechanical test indicated that crystallinity developed during the MEX process can adversely affects the interlayer adhesion. In the third project, a 3D heat transfer model was developed to simulate and understand the thermal history of MEX feedstock material during printing, this model is then thoroughly validated against the experimental IR thermography data. While good prediction accuracy was shown for some scenarios, the research identified and discussed several unreported challenges that significantly affect the model's prediction performance in certain conditions. In the fourth project, we employed a non-isothermal crystallization model to directly predict the development of crystallinity based on given temperature profiles, whether monitored experimentally or predicted by the heat transfer model. The research documented notable discrepancies between the model's predictions and actual crystallinity measurements, and the potential source of the error was addressed. In summary, this thesis explored the MEX printing of semi-crystalline polymer and its fiber reinforced composite. The influence of MEX parameters and part designs on the printed part's thermal history, crystallinity and mechanical performance was then thoroughly investigated. A heat transfer model and a non-isothermal crystallization model were constructed and employed. With rigorous validation against experimental data, previously unreported challenges in MEX thermal and crystallization modeling was highlighted. Overall, this thesis deepens the understanding of current semi-crystalline polymer's P/S/P relationship in MEX, and offers insights for the optimization and future research in the field of both experiment and simulation of MEX. / Doctor of Philosophy / Material extrusion additive manufacturing (MEX), also known as fused filament fabrication (FFF), is a popular form of 3D printing known for its cost-effectiveness and versatility in creating objects from plastic materials. Traditionally, MEX utilizes amorphous polymers because they are less prone to shrinkage and thus easier to print. However, semi-crystalline polymers, offer enhanced strength and chemicals resistance, yet they pose significant challenges in printing due to a limited understanding of their process/structure/property (P/S/P) relationships in MEX. This research aims to improve our understanding of P/S/P relationships of semi-crystalline polymers in MEX. The study utilizes a typical semi-crystalline polymer, Poly (ethylene terephthalate) (PET), as the benchmark material. The study begins with the exploration of the MEX printing of recycled PET (rPET) and its glass fiber composite, finding that with appropriate MEX parameters, both feedstocks are highly printable, and the incorporation of glass fibers substantially increased the strength of the printed parts. Subsequently, a comprehensive investigation regarding the intricate relationship between crystallinity development, mechanical properties, and the MEX printing process is conducted. Our research revealed that the MEX process and the design of the part both considerably affect the crystallinity of the final part, thereby influencing its mechanical properties. In the third chapter, a 3D heat transfer model is constructed to better understand and predict the temperature evolution of materials during MEX printing. Most importantly, the modeling results are rigorously validated against experimental data, showing promising results. However, it also reveals challenges in precisely predicting the temperature of parts under certain conditions. The research then evaluates the applicability of Nakamura non-isothermal crystallization model for MEX printing scenarios. It is found that this model underestimates crystallinity in MEX, primarily because it does not account for shear-induced crystallization, a critical factor in the process. This finding underscores the necessity for more advanced models that can effectively capture the complex dynamics of MEX. In summary, this dissertation significantly enhances our understanding of the behavior of semi-crystalline polymers in MEX printing. It sheds light on the complex relationship between the printing process, the structure of the material, and the final properties of the printed object. This work not only advances our knowledge in 3D printing but also paves the way for more sophisticated modeling approaches, optimizing the MEX process and expanding its potential applications.

<p dir="ltr">Human-robotics teaming (HRT) has many highly impactful applications in industry, medical, rehabilitation, military, mixed reality, etc. High quality sensing technologies and communications are inevitable for the HRT development. Many commercial sensors, such as vision-based, audio-based and proximity sensors, are usually rigid and difficult for conformable and large-scale integration. Imperceptible soft sensing devices feasible for human/robot integration with high compliance are attractive for the HRT applications. In addition, ubiquitous sensing with good robustness, self-powered capability, high fidelity, and high SNR are desirable for future HRT.</p><p dir="ltr">This dissertation presents a comprehensive study of SITS theory, ink-based materials, scalable manufacturing methods to develop SITS devices for various applications, including spray coated SITS for human pulse analysis and robotic control, fabric smart glove for objects recognition, and plant triboelectric skin powered IoT sensing system. We develop the SITS theory and propose design strategies for high-performance SITS devices. We study the ink-based materials and scalable manufacturing methods for SITS. We also conduct materials modifications, device configuration and system integration to fabricate versatile SITS for different applications. The presented concepts and applications vast from human skin to plant skin, which shows great potentials to implement SITS technology for future HRT system.</p>

The application of glass fiber reinforced composites has grown rapidly due to their high strength-to-weight ratio, low cost, and chemical resistance. However, the increasing demand for fiber reinforced composites results in the generation of more composite wastes. Mechanical recycling is a cost-effective and environmentally-friendly recycling method, but the loss in the quality of recycled glass or carbon fiber composite hinders the wide-spread use of this recycling method. It is important to develop novel composite materials with higher recyclability. Thermotropic liquid crystalline polymers (TLCPs) are high-performance engineering thermoplastics, which have comparable mechanical performance to that of glass fiber. The TLCP reinforced composites, called in situ composites, can form the reinforcing TLCP fibrils during processing avoiding the fiber breakage problem. The first part of this dissertation is to study the influence of mechanical recycling on the properties of injection molded TLCP and glass fiber (GF) reinforced polypropylene (PP). The processing temperature of the injection molding process was optimized using a differential scanning calorimeter (DSC) and a rheometer to minimize the thermal degradation of PP. The TLCP and GF reinforced PP materials were mechanically recycled up to three times by repeated injection molding and grinding. The mechanical recycling had almost no influence on the mechanical, thermal, and thermo-mechanical properties of TLCP/PP because of the regeneration of TLCP fibrils during the mold filling process. On the other hand, glass fiber/PP composites decreased 30% in tensile strength and 5% in tensile modulus after three reprocessing cycles. The micro-mechanical modeling demonstrated the deterioration in mechanical properties of GF/PP was mainly attributed to the fiber breakage that occurred during compounding and grinding. The second part of this dissertation is concerned with the development of recyclable and light weight hybrid composites through the use of TLCP and glass fiber. Rheological tests were used to determine the optimal processing temperature of the injection molding process. At this processing temperature, the thermal degradation of matrix material was mitigated and the processability of the hybrid composite was improved. The best formulation of TLCP and glass fiber in the composite was determined giving rise to the generation of a recyclable hybrid composite with low melt viscosity, low mechanical anisotropy, and improved mechanical properties. Finally, TLCP reinforced polyamide composites were utilized in an additive manufacturing application. The method of selecting the processing temperature to blend TLCP and polyamide in the dual extrusion process was devised using rheological analyses to take advantage of the supercooling behavior of TLCP and minimize the thermal degradation of the matrix polymer. The composite filament prepared by dual extrusion was printed and the printing temperature of the composite filament that led to the highest mechanical properties was determined. Although the tensile strength of the TLCP composite was lower than the glass fiber or carbon fiber composites, the tensile modulus of 3D printed 60 wt% TLCP reinforced polyamide was comparable to traditional glass or carbon fiber reinforced composites in 3D printing. / Doctor of Philosophy / The large demand for high performance and light weight composite materials in various industries (e.g., automotive, aerospace, and construction) has resulted in accumulation of composite wastes in the environment. Reuse and recycling of fiber reinforced composites are beneficial from the environmental and economical point of view. However, mechanical recycling deteriorates the quality of traditional fiber reinforced composite (e.g., glass fiber and carbon fiber). There is a need to develop novel composites with greater recyclability and high-performance. Thermotropic liquid crystalline polymers (TLCP) are attractive high performance materials because of their excellent mechanical properties and light weight. The goal of this work is to generate recyclable thermotropic liquid crystalline polymer (TLCP) reinforced composites for use in injection molding and 3D printing. In the first part of this work, a novel recyclable TLCP reinforced composite was generated using the grinding and injection molding. Recycled TLCP composites were as strong as the virgin TLCP composites, and the mechanical properties of TLCP composites were found to be competitive with the glass fiber reinforced counterparts. In the second part, a hybrid TLCP and glass fiber reinforced composite with great recyclability and excellent processability was developed. The processing conditions of injection molding were optimized by rheological tests to mitigate fiber breakage and improve the processability. Finally, a high performance and light weight TLCP reinforced composite filament was generated using the dual extrusion process which allowed the processing of two polymers with different processing temperatures. This composite filament could be directly 3D printed using a benchtop 3D printer. The mechanical properties of 3D printed TLCP composites could rival 3D printed traditional fiber composites but with the potential to have a wider range of processing shapes.

The research presented in this dissertation supports the overall goal of creating piezoelectric measurement technology for the analysis and characterization of soft materials that serve as feedstocks (inputs) and products (outputs) of emerging biomanufacturing processes, including cell and additive biomanufacturing processes. The first objective was to define measurement challenges associated with real-time monitoring of material compositional profiles using biosensors in practical biomanufacturing and bioprocessing formats, as insight into a material's composition (i.e., concentration of a given biologic within a material or product) provides molecular-scale insight into processes and product quality. The second objective was to design, fabricate, and characterize continuous flow cell separation technology based on 3D printed self-exciting and -sensing millimeter-scale piezoelectric transducers and microfluidic networks for separation and characterization of expanded therapeutic cells. The third objective was to establish a sensor-based characterization approach for viscoelastic properties of hydrogels and gelation processes using high-order modes of piezoelectric-excited millimeter cantilever (PEMC) sensors and understand the influence of cantilever mode number on critical sensor characteristics, including sensitivity, dynamic range, and limit of detection. The first objective was addressed through a comprehensive review of recent progress in electrochemical and hybrid biosensors, which included discussions of measurement formats, sensor performance, and measurement challenges associated with use in practical bioprocessing environments. This critical review revealed that cost, disposability, form factor, complex measurement matrices, multiplexing, and sensor regeneration/reusability are among the most pressing challenges that require solutions through advancement of sensor design and manufacturing approaches before biosensors can facilitate high-confidence long-term continuous bioprocess monitoring. The second objective was addressed by creating a microextrusion-based additive manufacturing approach for fabrication of piezoelectric-based MEMS devices that enabled integration of 3D configurations of piezoelectric transducers and microfluidic networks in a one-pot manufacturing process. The devices contained orthogonal out-of-plane piezoelectric sensors and actuators and generated tunable bulk acoustic waves (BAWs) capable of size-selective manipulation, trapping, and separation of suspended particles in droplets and microchannels. This work suggests that additive manufacturing potentially provides new opportunities for the fabrication of sensor-integrated microfluidic platforms for cell culture analysis. The third objective was addressed through resonant frequency tracking of low- and high-order modes in dynamic-mode cantilevers to enable the real-time characterization of hydrogel viscoelastic properties and continuous monitoring of sol-gel phase transitions over a wide dynamic range using practically relevant hydrogel systems used commonly in additive biomanufacturing. This work suggests that high-order modes of PEMC sensors facilitate characterization of hydrogel viscoelastic properties and gelation processes with improved dynamic range and limit of detection that can complement the performance of low-order modes. Through this research, new approaches for sensor-based characterization of soft material composition and mechanical properties using millimeter-scale piezoelectric devices are presented as solutions for current challenges in biomanufacturing and biosensing to advance capability in real-time sensing of quality attributes among biomanufactured products. / Doctor of Philosophy / The research presented in this dissertation supports the overall goal of creating sensor-based measurement technology for quality assessment of soft materials within practical online biosensing and biomanufacturing processing formats. This technology seeks to enable monitoring and control of product quality in real-time. Soft biomaterials used in these processes, including cells and hydrogels, can be characterized by quality signatures such as concentration of analytes and physical and mechanical properties. Separation and fluid handling technologies aid real-time characterization when integrated with the processing system. By improving sensor-based measurement capability of soft materials, sensing platforms can provide online quality assurance and control, thereby increasing the product quality and process efficiency – or yield– at reduced cost. The first objective was to define measurement challenges and limitations associated with detection of biologics in practical biomanufacturing and bioprocessing formats (with focus on pathogen detection, as the detection of adventitious agents and pathogens remains a critical aspect of bioprocess monitoring). This was addressed through a comprehensive review of recent progress in the field of electrochemical and hybrid biosensors. The second objective was to design and fabricate sensor-integrated microfluidic technology for cell separation applications using a combination of multi-material 3D printing and pick-and-place techniques. The third objective was to improve measurement capability of piezoelectric sensors for characterization of viscoelastic properties of hydrogel formulations commonly used in additive biomanufacturing processes and tissue engineering. Through this research, new approaches for sensor-based characterization of soft materials using millimeter-scale piezoelectric devices are presented as solutions for current challenges in biomanufacturing and biosensing platforms in order to advance quality assessment capability.

Additive manufacturing (AM) creates 3D objects out of polymers, ceramics, and metals to enable cost-efficient and rapid production of products from aerospace to biomedical applications. Personalized products manufactured using AM, such as personalized dosage pharmaceuticals, tissue scaffolds, and medical devices, require specific material properties such as biocompatibility and biodegradability, etc. Polymers possess many of these qualities and tuning molecular structure enables a functional material to successfully deliver the intended application. For example, water-soluble polymers such as poly(vinyl pyrrolidone) and poly(ethylene glycol) both function as drug delivery materials because of their inherit water-solubility and biocompatibility. Other polymers such as polylactide and polyglycolide possess hydrolytically cleavable functionalities, which enables degradation in the body. Non-covalent bonds, such as hydrogen bonding and electrostatic interactions, enable strong connections capable of holding materials together, but disconnect with heat or solvation. Taking into consideration some of these polymer functionalities, this dissertation investigates how to utilize them to create functional biomedical products using AM. The investigation of structure-property-processing relationships of polymer molecular structures, physical properties, and processing behaviors is transforming the field of new materials for AM. Even though novel, functional materials for AM continue to be developed, requirements that render a polymeric material printable remain unknown or vague for most AM processes. Materials and printers are usually developed separately, which creates a disconnect between the material printing requirements and fundamental physical properties that enable successful printing. Through the interface of chemistry, biology, chemical engineering, and mechanical engineering, this dissertation aims to relate printability of polymeric materials with three types of AM processes, namely vat photopolymerization, binder jetting, and powder bed fusion. Binder jetting, vat photopolymerization, and powder bed fusion require different viscosity and powder requirements depending on the printer capabilities, and if the material is neat or in solution. Developing scaling relationships between solution viscosity and concentration determined critical overlap (C*) and entanglement (Ce) concentrations, which are related to the printability of the materials. For example, this dissertation discusses and investigates the maximum printable concentration in binder jetting of multiple polymer architectures in solution as a function of C* values of the polymer. For thermal-type printheads, C* appeared to be the highest jettable concentration, which asserted an additional method of material screening for binder jetting. Another investigation of the photokinetics as a function of concentration of photo-active polymers in solution revealed increased viscosity leads to decreased acrylate/acrylamide conversion. Lastly, investigating particle size and shape of poly(stearyl acrylate) particles synthesized through suspension polymerization revealed a combination of crosslinked and linear polymers produced high resolution parts for phase change materials. These analytical screening methods will help the progression of AM and provide future scientists and engineers a better guideline for material screenings. / Doctor of Philosophy / Additive manufacturing (AM), also known as 3D printing, enables the creation of 3D objects in a rapid and cost-efficient manner for applications from aerospace to biomedical sectors. AM particularly benefits the field of personalized biomedical products, such as personalized dosage pharmaceuticals, hearing aids, and prosthetic limbs. In the future, advanced detection and prevention medical screenings will provide doctors, pharmacists, and engineers very precise data to enable personalized healthcare. For example, a patient can take three different medications in one pill with the exact dosage to prevent side-effects and drug-drug interactions. AM enables the delivery and manufacturing of these personalized systems and will improve healthcare in every sector. Investigations of the most effective materials is needed for personalized medicine to become a reality. Polymers, or macromolecules, provide a highly tunable material to become printable with slight chemical modifications. Investigation of how chemical structure affects properties, such as strength, stretchability, or viscosity, will dictate how they perform in a manufacturing setting. This process of investigation is called "structure-property-processing" relationships, which connects scientists and engineers through all disciplines. This method is used to discover which polymers will not only 3D print, but also carry medication to a patient or deliver therapeutics within the body.

Additive manufacturing (AM) has received much attention from researchers over the past decades because of its diverse applications in various industries. AM is an advanced manufacturing process that facilitates the fabrication of complex geometries represented by computer-aided design (CAD) models. Traditionally, designed parts are fabricated by extruding material layer-by-layer using a tool path planning obtained from slicing programs by using CAD models as an input. Recently, there has been a growing interest in non-planar AM technologies, which offer the ability to fabricate multilayer constructs conforming to freeform surfaces. Non-planar AM processes have been utilized in various applications and involved objects of varying material properties and geometric characteristics. Although the current state of the art suggests AM can provide novel opportunities in conformal manufacturing, several challenges remain to be addressed. The identified challenges in non-planar AM fall into three categories: 1) conformal 3D printing on substrates with complex topography of which CAD model representation is not readily available, 2) understanding the relationship between the tool path planning and the quality of the 3D-printed construct, and 3) conformal 3D printing in the presence of mechanical disturbances. An open-loop non-planar tool path planning algorithm based on point cloud representations of object geometry and a closed-loop non-planar tool path planning algorithm based on position sensing were proposed to address these limitations and enable conformal 3D printing and spatiotemporal 3D sensing on objects of near-arbitrary organic shape. Three complementary studies have been completed towards the goal of improving the conformal tool path planning capabilities in various applications including fabrication of conformal electronics, in situ bioprinting, and spatiotemporal biosensing: i. A non-planar tool path planning algorithm for conformal microextrusion 3D printing based on point cloud data representations of object geometry was presented. Also, new insights into the origin of common conformal 3D printing defects, including tool-surface contact, were provided. The impact and utility of the proposed conformal microextrusion 3D printing process was demonstrated by the fabrication of 3D spiral and Hilbert-curve loop antennas on various non-planar substrates, including wrinkled and folded Kapton films and origami. ii. A new method for closed-loop controlled 3D printing on moving substrates, objects, and unconstrained human anatomy via real-time object position sensing was proposed. Monitoring of the tool position via real-time sensing of nozzle-surface offset using 1D laser displacement sensors enabled conformal 3D printing on moving substrates and objects. The proposed control strategy was demonstrated by microextrusion 3D printing on oscillating substrates and in situ bioprinting on an unconstrained human hand. iii. A reverse engineering-driven collision-free path planning program for automated inspection of macroscale biological specimens, such as tissue-based products and organs, was proposed. The path planning program for impedance-based spatiotemporal biosensing was demonstrated by the characterization of meat and fruit tissues using two impedimetric sensors: a cantilever sensor and a multifunctional fiber sensor. / Doctor of Philosophy / Additive Manufacturing (AM), commonly referred to as 3D printing, is a computer-aided manufacturing process that facilitates the fabrication of personalized and customized models, tissues, devices, and wearables. AM has several advantages over traditional manufacturing processes. For example, directing computer-driven robotics enables control over spatial structure and composition of parts. While 3D printing is typically performed using layer-by-layer planar tool paths generated by slicing programs, non-planar 3D printing is an emerging area that has recently been examined for various post-processing applications. Processes that enable material deposition conforming to complex geometric and freeform objects (e.g., anatomical structures), are central to various industries, including additive manufacturing, electronics manufacturing, and biomanufacturing. In this dissertation, tool path planning methods and real-time control strategies for non-planar 3D printing onto stationary and moving arbitrary surfaces, and various conformal electronics and in situ bioprinting applications will be presented. In addition to the tool path planning methods for 3D printing, a collision-free path planning program will be proposed for the inspection of large tissues and organs. The utility of the proposed method will be demonstrated through electrical impedance-based biosensing of meat and fruit to characterize their compositional and physiochemical properties which are used for quality assessment.

The synthesis and characterization of step-growth polymers with novel monomers provided materials with tailored properties for emerging technologies. Specifically, multiphase materials (i.e., microphase separated block copolymers) exploit the synergistic relationship of combining polymers with disparate thermal and mechanical properties. The introduction of intramolecular interactions such as hydrogen and ionic bonding into these polymers further tailored their properties for applications including elastomers, electromechanical transducers, and additive manufacturing (AM). A review of recent literature revealed the material properties required for polymeric materials in electromechanical transducers, which aided in the design of polymers for this application. An isocyanate-, catalyst-, and solvent-free approach facilitated the synthesis of segmented polyureas with tunable thermal and mechanical properties. These materials found use as high dielectric elastomers and water-soluble polymers for extrusion-based AM dependent on the backbone composition. Vat photopolymerization (VP) AM served as a technique to 3D printed novel unsaturated polyester resins (UPR). Incorporating a phosphonium ionic liquid as a reactive diluent replaced styrene and reduced the volatility of commonly used UPRs. VP successfully provided 3D structures from these UPRs that demonstrated limited ionic conductivities. An extensive review of the literature surrounding the structure-property relationships of charged block copolymers with varying architectures helped to inform the synthesis of novel, cationic step-growth polymers. The synthesis of a new phosphonium IL facilitated the synthesis of a segmented polyurethane containing a phosphonium-functionalized soft segment for the first time. This phosphonium polyurethane exhibited ionic conductivities comparable to literature examples of block copolymers used for ionic polymer transducers, which suggests that these materials may serve for this application as well. Carbonyldiimidazole provides a novel route towards synthesizing imidazolium ionenes with unique backbone structures. The coupling of poly(ethylene glycol) dibromides with a bis-carbonylimidazole monomer and a commercial aliphatic dibromide led to the formation of segmented imidazolium ionenes. These polymers exhibited significant atmospheric water uptake as well as water solubility. However, the physical properties of the materials suggested that the synthetic procedure resulted in low molecular weights. Suggested future work provides methods for circumventing this issue and proposes next steps for all the projects discussed herein. / Doctor of Philosophy / Emerging technologies require new polymeric materials with intentionally designed properties. Step-growth polymers such as polyesters, polyurethanes, and polyureas find use in many applications of our everyday lives. Although these materials have served mainly as commodity plastics historically, a reimagining of their syntheses and chemical structures makes them accessible for modern technologies. For example, applying green chemistry principles to the synthesis of polyureas resulted in a less toxic synthetic procedure. Polyureas synthesized through this method exhibited elastic properties comparable to classical polyureas and displayed high dielectric constants, which lend them towards use in dielectric elastomer actuators. This chemistry also allowed for the synthesis of water-soluble polyureas, which served as a material for low temperature extrusion additive manufacturing, colloquially known as 3D printing. Vat photopolymerization describes another type of 3D printing that involves the selective curing of liquid resins with light to form a 3D structure. Employing a reactive ionic liquid monomer with a commercially-relevant unsaturated polyester allowed for a nontoxic method of printing these materials, which also imparted ionic conductivity. Finally, the synthesis of positively charged polyurethanes and ionenes led to the production of ionically conductive materials that may find use in polymeric transducers.

Material jetting (MJ) is an additive manufacturing (AM) process that involves the selective jetting of a liquid material into the shape of a layer and subsequent solidification, often via ultraviolet (UV) irradiation, in a layer-wise fashion. The MJ process has the potential to emerge as a robust fabrication method: the inherent, facile, multi-material capability in a high-resolution process should distinguish the technology as a competitive, multi-functional, manufacturing process. However, it is mainly constrained to prototyping use, limited by both material and process constraints. This research expands material and process knowledge by characterizing the multi-material process-structure-property relationships in photopolymer-based MJ, which provides a basis for advancing the capability of MJ to fabricate accurate and consistent multi-material parts for functional applications. One of the challenges for advancing MJ is the general lack of processable materials. For example, MJ is increasingly being used for fabricating anatomic models for use as pre-procedural planning or medical student trainee tools, but commercial MJ elastomers are unable to mimic human tissues' mechanical properties, which limits the instructional value of printed anatomic models. By combining photo-curing and non-curing materials, a cardiac tissue-mimicking material was achieved and integrated into a fully-printed heart model used to practice the transseptal puncture procedure. Several mechanical properties of this multi-material combination were evaluated to facilitate quicker screening of future tissues that would be desired to be mimicked. Also impeding technological advancement of MJ systems is a lack of understanding the effects of indiscriminate UV exposure on material properties. Depending on factors such as part design and build layout, an indiscriminate UV toolpathing strategy poses the risk for providing inconsistent UV dosing to parts and causing unintended variations in mechanical performance. Experiments were conducted to quantify these effects, and an empirical model was developed to predict the accumulated exposure parts receive. A connection was then made between accumulated exposure received by material voxels and final part properties, where it was observed that overexposure effects exist, and are largely dependent on material, build layout, and toolpathing. This work will lead to improved design guidelines and process modifications to ensure consistency of UV dosing and achieve desired mechanical performance. This knowledge will enable future photopolymer AM systems to account for potential overcuring effects toward fabricating repeatable and reproducible functional products. Finally, documented in this work are efforts toward expanding the knowledge about the use of AM to safely produce personal protective equipment during the COVID-19 pandemic. Amid prospects of large-scale, distributed production of respirators via AM, the lack of filtration efficiency testing generated concerns about the respirators' effectiveness. The goal of this work was to measure particle transmission through respirators fabricated with powder bed fusion and fused filament fabrication processes and compare their performance to that of cloth masks and standardized N95 respirators. Through systematic post-processing, the connection between printed respirator deficiencies and changes in filtration efficiency were discerned. Identifying the system-level quality control challenges responsible for the respirator failure modes highlights some the current limitations in AM for fabricating functional parts. The findings will assist future efforts toward both creating enhanced designs and optimizing printer parameters, ultimately working toward qualifiable, end-use parts. / Doctor of Philosophy / The material jetting (MJ) additive manufacturing (AM) process operates in a similar fashion to inkjet printing. For MJ of photopolymer materials, liquid droplets are selectively deposited onto a build plate, and an ultraviolet (UV) light bulb provides the energy to solidify the droplets into a three-dimensional layer by curing the materials. Droplets are then deposited on top of these solidified droplets to fabricate a part layer by layer. Multiple materials and colors can be jetted simultaneously within a single part layer. If these materials exhibit different mechanical behavior, such as one material being rigid and another being flexible, a printed part could have regions with different material properties, as well as intermediate gradients of these properties. The MJ process offers high resolution, smooth surface finishing, a large build volume, and the opportunity to print multiple parts in one build. However, the process is mainly limited to prototypes and non-functional applications. One of the challenges for advancing MJ is the general lack of processable materials. In the medical field, surgeons are increasingly looking to MJ to fabricate physical, patient-specific models to assist in pre-surgical planning and to serve as practice models for medical student trainees. In particular, a printed cardiovascular model was sought to enable the practice of the transseptal puncture procedure; however, the available materials were not able to mimic the heart tissue. In this work, a non-curing liquid was patterned into an elastomer to soften the material and attain tissue-mimicking performance for a model to practice the transseptal puncture procedure. By characterizing this expanded material space, this work enables the potential for mimicking a broader spectrum of tissues in future anatomic models. Another aspect limiting widespread functional use for MJ is the lack of understanding how UV exposure affects material performance. For the MJ process, the UV light is on the same assembly as the printheads and remains on throughout the duration of a print, which means that the amount of administered energy is not consistent across the build plate. If, for example, parts have different heights, the shorter part will finish printing first and receive excess UV exposure, which has been shown to alter the mechanical performance for some materials. A model was developed to predict the accumulated exposure received by parts of different materials and build scenarios. Observed changes in mechanical properties could then be connected to specific instances of overexposure. With this knowledge, future strategies can be implemented to achieve consistency of UV exposure and thus better ensure reliable, functional parts. Additionally presented in this work is a study involving the use of AM to safely produce personal protective equipment for COVID-19 relief efforts. During the initial stages of the pandemic, AM was sought to address respirator shortages; however, there were no studies measuring printed respirators' effectiveness. By measuring particle transmission through respirators fabricated with a variety of AM processes, it was found that even when N95 filters were inserted, printed respirators were not able to consistently filter 95% of virus-sized particles, even with modifications. The quality control challenges for the AM processes identified in this study will assist future efforts in part design and printer parameter optimization to work toward accurate and qualifiable products.

According to data provided by the U.S. Department of Health and Human Services, the waiting list of organ transplantation as of April 2021 is approximately 107,550 out of which 90,908 patients are waiting for a kidney and 11,871 are waiting for a liver. In 2020, only 39,000 transplants were performed. A promising potential solution to this organ shortage crisis is rapid development of drugs for end-stage kidney and liver failure and the fabrication of organs using additive biomanufacturing (Bio-AM) processes. While progress toward industrial-scale production of 3D-bioprinted tissue models and organs remains hindered by various biological and tissue engineering challenges, such as vascularization and innervation, quality Bio-AM is impeded by lack of integrated process monitoring and control strategies. This dissertation aims to address the compelling need to incorporate sensing and control with Bio-AM processes, which are currently open-loop processes and improve the scalability and reliability of additively biomanufactured products. The specific aim is to develop a closed loop-controlled additive biomanufacturing process capable of fabricating 3D-bioprinted biological constructs (mini-tissues) of controlled mechanical properties. The proposed methodology is based on the use of embedded sensors and real-time material property sensing for feedback control of the bioprinted constructs mechanical property. There are three objectives of this dissertation: (1) experimenting and modeling the processes to understand the causal effect of process-material interactions on Bio-AM defects, (2) use of sensors to detect defects during printing, (3) prevention of the propagation of defects through closed-loop process control. This will help us understand the fundamentals of the bio-physical process interactions that govern the quality of printed biological tissue through empirical investigation of the sensor-based data This will also provide us with a real-time monitoring, closed-loop quality control strategy to prevent the propagation of quality defects by executing corrective actions during the whole duration of the printing process. / Doctor of Philosophy / As of April 2021, there are 107,550 patients on the national transplant list out of which approximately 39,000 patients received a transplant. Simultaneously, drug development remains an expensive and time-consuming endeavor. These burden on the public and healthcare system are expected to further increase compounded by the rapidly aging population in the United States with 80 million people expected to be older than 65 years old by 2040. Additive biomanufacturing processes, commonly referred to as 3D bioprinting processes, are automated biofabrication processes that offer great potential toward manufacturing future therapeutics and models for drug discovery. Despite all the benefits and the versatility that 3D printing provides, it does not come without its own shortcomings. Additive biomanufacturing is traditionally an open-loop process, meaning the process parameters are not adjusted during the biofabrication process making it challenging to detect and correct defects during processing and achieve high reproducibility and product quality. While the dimensional characteristics and material properties are important quality signatures of a cell-based products, there are additional signatures associated with the cell quality. Some of these quality attributes include cell viability, cell proliferation, metabolic activity, morphology, and gene expression profile. Given the clinical importance and invasive nature of bio-products such as scaffolds for tissue regeneration and stem cell therapy, rigorous approaches for characterization, monitoring, and control of quality are critical to future additive bio-manufacturing paradigms. In particular, the elastic modulus of the extracellular matrix has been found to have an influence on the cell morphology, proliferation, and differentiation process. Hence, it is an excellent parameter to monitor as a measure of tissue quality. However, the traditional techniques used to characterize tissue elastic modulus are low-throughput, offline techniques and face challenges with tissue integration. Thus, there is a need for integrated sensors that can measure the modulus of tissues during 3D bioprinting. This dissertation aims to address some of these issues by developing a multi-material 3D printing and pick-and-place approach to develop smart tissue cultureware and designing a tissue integrated closed-loop feedback sensor system for polymerization of hydrogels.

Metal additive manufacturing (AM) provides a platform for microstructure optimization via process control, the ability to model the evolution of microstructures from changes in processing condition or even predict the microstructures from given processing condition would greatly reduce the time frame and the cost of the optimization process. In 1, we present a deep learning framework to quantitatively analyze the microstructural variations of metals fabricated by AM under different processing conditions. We also demonstrate the capability of predicting new microstructures from the representation with deep learning and we can explore the physical insights of the implicitly expressed microstructure representations. We validate our framework using samples fabricated by a solid-state AM technology, additive friction stir deposition, which typically results in equiaxed microstructures. In 2, we further improve and generalize the generating framework, a set of metrics is used to quantitatively analyze the effectiveness of the generation by comparing the microstructure characteristics between the generated samples and the originals. We also take advantage of image processing techniques to aid the calculation of metrics that require grain segmentation. / Master of Science / Different from the traditional manufacturing technique which removes material to form the desired shape, additive manufacturing (AM) adds material together to form the shapes usually layer by layer. AM which is sometimes also referred to as 3-D printing enables the optimization of material property through changing the processing conditions. The microstructure is structures formed by materials on a microscopic scale. Crystals like metal usually form a crystalline structure composed of grains where atoms have the same orientation. Especially for metal AM, changes in the processing condition will usually result in changes in microstructures and material properties. To better optimize for the desired material properties, in 1 we present a microstructure representation method that allows projection of microstructure onto the representation space and prediction from an arbitrary point from the representation space. This representation method allows us to better analyze the changes in microstructure in relation to the changes in processing conditions. In 2, we validate the representation and prediction using EBSD data collected from copper samples manufactured with AM under different processing conditions.