The objectives of this paper in the context of aerosol jet printing (AJP)—an additive manufacturing (AM) process—are to: (1) realize in situ online monitoring of print quality in terms of line/electronic trace morphology; and (2) explain the causal aerodynamic interactions that govern line morphology based on a two-dimensional computational fluid dynamics (2D-CFD) model. To realize these objectives, an Optomec AJ-300 aerosol jet printer was instrumented with a charge coupled device (CCD) camera mounted coaxial to the nozzle (perpendicular to the platen). Experiments were conducted by varying two process parameters, namely, sheath gas flow rate (ShGFR) and carrier gas flow rate (CGFR). The morphology of the deposited lines was captured from the online CCD images. Subsequently, using a novel digital image processing method proposed in this study, six line morphology attributes were quantified. The quantified line morphology attributes are: (1) line width, (2) line density, (3) line edge quality/smoothness, (4) overspray (OS), (5) line discontinuity, and (6) internal connectivity. The experimentally observed line morphology trends as a function of ShGFR and CGFR were verified with computational fluid dynamics (CFD) simulations. The image-based line morphology quantifiers proposed in this work can be used for online detection of incipient process drifts, while the CFD model is valuable to ascertain the appropriate corrective action to bring the process back in control in case of a drift.

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The goal of this research is online monitoring of functional electrical properties, e.g., resistance, of electronic devices made using aerosol jet printing (AJP) additive manufacturing (AM) process. In pursuit of this goal, the objective is to recover the cross-sectional profile of AJP-deposited electronic traces (called lines) through shape-from-shading (SfS) analysis of their online images. The aim is to use the SfS-derived cross-sectional profiles to predict the electrical resistance of the lines. An accurate characterization of the cross section is essential for monitoring the device resistance and other functional properties. For instance, as per Ohm’s law, the electrical resistance of a conductor is inversely proportional to its cross-sectional area (CSA). The central hypothesis is that the electrical resistance of an AJP-deposited line estimated online and in situ from its SfS-derived cross-sectional area is within 20% of its offline measurement. To test this hypothesis, silver nanoparticle lines were deposited using an Optomec AJ-300 printer at varying sheath gas flow rate (ShGFR) conditions. The four-point probes method, known as Kelvin sensing, was used to measure the resistance of the printed structures offline. Images of the lines were acquired online using a charge-coupled device (CCD) camera mounted coaxial to the deposition nozzle of the printer. To recover the cross-sectional profiles from the online images, three different SfS techniques were tested: Horn’s method, Pentland’s method, and Shah’s method. Optical profilometry was used to validate the SfS cross section estimates. Shah’s method was found to have the highest fidelity among the three SfS approaches tested. Line resistance was predicted as a function of ShGFR based on the SfS-estimates of line cross section using Shah’s method. The online SfS-derived line resistance was found to be within 20% of offline resistance measurements done using the Kelvin sensing technique.

Pneumatic micro-extrusion (PME) is a direct-write additive manufacturing process, which has emerged as a robust, high-resolution method for the fabrication of a broad spectrum of biological tissues and organs. PME allows for non-contact multi-material deposition of functional inks for tissue engineering applications. In spite of the advantages and engendered potential applications, the PME process is inherently complex, governed by not only complex physical phenomena, but also material-process interactions. Consequently, investigation of the influence of PME process parameters as well as the underlying physical phenomena behind material transport and deposition in PME would be inevitably a need. The overarching goal of this research work is to fabricate biocompatible, porous bone tissue scaffolds for the treatment of osseous fractures, defects, and diseases. In pursuit of this goal, the objectives of the work are: (i) to investigate the influence of seven consequential scaffold design factors and PME process parameters on the mechanical properties of fabricated bone tissue scaffolds; (ii) to explore the underlying dynamics behind material transport in the PME process, using a 3D computational fluid dynamics (CFD) model. To investigate the effects of the design and process parameters, a series of experiments were designed and conducted. Layer height was identified as the most significant factor in this study. An increase in the layer height led to less overlap between subsequent layers, which allowed for more shrinkage and ultimately a reduction in scaffold diameter. In addition, print speed appeared as an influential factor in this study. An increase in the print speed resulted in a decline in linear mass density and thus in the extent of fusion between subsequent deposited layers. Besides, it was observed that there was a strong correlation between deposition mass and compression modulus. Overall, the results of this study pave the way for future investigation of PME-deposited PCL scaffolds with optimal functional and medical properties for incorporation of stem cells toward the treatment of osseous fractures and defects.

Aerosol jet printing (AJP) is a direct-write additive manufacturing technique, which has emerged as a high-resolution method for the fabrication of a broad spectrum of electronic devices. Despite the advantages and critical applications of AJP in the printed-electronics industry, the AJP process is intrinsically unstable, complex, and prone to unexpected gradual drifts, which adversely affect the morphology and consequently the functional performance of a printed electronic device. Therefore, in situ process monitoring and control in AJP is an inevitable need. In this respect, in addition to experimental characterization of the AJP process, physical models would be required to explain the underlying aerodynamic phenomena in AJP. The goal of this research work is to establish a physics-based computational platform for prediction of aerosol flow regimes and ultimately, physics-driven control of AJP process. In pursuit of this goal, the objective is to forward a 3D compressible, turbulent, multi-phase CFD model to investigate the aerodynamics behind: (i) aerosol generation, (ii) aerosol transport, and (iii) aerosol deposition on a moving free surface in the AJP process. The complex geometries of the deposition head as well as the pneumatic atomizer were modeled in the ANSYS-Fluent environment, based on patented designs and also accurate measurements, obtained from 3D X-ray computed tomography (CT) imaging. The entire volume of the constructed geometries was subsequently meshed, using a mixture of smooth and soft quadrilateral elements, with consideration of layers of inflation to obtain an accurate solution near the walls. A combined approach - based upon the density-based and pressure-based Navier-Stokes formation - was adopted to obtain steady-state solutions and to bring the conservation imbalances below a specified linearization tolerance (i.e., ?10?^(-6)). Turbulence was modeled, using the realizable k-? viscous model with scalable wall functions. A coupled two-phase flow model was, in addition, set up to track a large number of injected particles. The boundary conditions were defined based on experimental sensor data, recorded from the AJP setup. The accuracy of the model was validated using a factorial experiment, composed of AJ-deposition of silver nanoparticles on a polyimide substrate. The outcomes of this study pave the way for the implementation of physics-driven in situ control of AJP.