Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process

Salary, Roozbeh; Lombardi, Jack P.; Tootooni, Mohammad Samie; Donovan, Ryan; Rao, Prahalada; Børgesen, Peter; Poliks, Mark D.

doi:10.1115/1.4034591

Cited by 81 publications

(64 citation statements)

References 45 publications

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“…In addition to materials and structural optimization, the process parameters should be adjusted and optimized to manufacture scaffolds with desired attributes. Numerous studies investigated the effect of process parameters on different responses such as mechanical properties (strength, elongation, Young's modulus), surface roughness, resolution and dimensional accuracy, and printing quality in different techniques including SLA [221][222][223][224], SLS [225][226][227][228][229][230][231][232][233][234], EBM [235][236][237][238][239][240][241], LENS [242,243], SLM [39,[244][245][246][247][248][249][250], 2PP [251][252][253], FDM [254][255][256], MJ [257,258], AJP [259][260][261][262], and IJP [263]…”

Section: D Printing Process Optimizationmentioning

confidence: 99%

Challenges on optimization of 3D-printed bone scaffolds

Bahraminasab

2020

BioMed Eng OnLine

145

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Background Bones in human body are prone to damage due to different causes such as fractures, diseases, and infections. Nevertheless, they have a remarkable capacity to repair and heal themselves after trauma and illness. Large defects, however, are never completely reinstated because their sizes are beyond the limit up to which the bones can repair [1]. In these conditions, therefore, a medical remedy is required to stabilize, align and support the damaged bone region to restore the lost function. Bone autografts are considered the gold standard treatment. However, they have a number of shortcomings including the limited sources and donor site morbidity. Allografts also have the risk of immune rejection and disease transmission [2, 3]. Therefore, the research has headed for other solutions via tissue engineering. Bone tissue engineering provides three-dimensional (3D)

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Section: D Printing Process Optimizationmentioning

confidence: 99%

Challenges on optimization of 3D-printed bone scaffolds

Bahraminasab

2020

BioMed Eng OnLine

145

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“…While AJP provides significant versatility from its compatibility with a broad range of materials, consistency and reproducibility are challenges that need to be overcome. For experienced users, optimizing print parameters to mitigate these challenges can require extreme measures which include, but are not limited to, frequent replacement of ink and extensive time spent towards empirical optimization for this sensitive process 21,23,35,37,38 .…”

Section: Printed Csg Designmentioning

confidence: 99%

Aerosol jet printed capacitive strain gauge for soft structural materials

et al. 2020

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Soft structural textiles, or softgoods, are used within the space industry for inflatable habitats, parachutes and decelerator systems. Evaluating the safety and structural integrity of these systems occurs through structural health monitoring systems (SHM), which integrate non-invasive/non-destructive testing methods to detect, diagnose, and locate damage. Strain/load monitoring of these systems is limited while utilizing traditional strain gauges as these gauges are typically stiff, operate at low temperatures, and fail when subjected to high strain that is a result of high loading classifying them as unsuitable for SHM of soft structural textiles. For this work, a capacitance based strain gauge (CSG) was fabricated via aerosol jet printing (AJP) using silver nanoparticle ink on a flexible polymer substrate. Printed strain gauges were then compared to a commercially available high elongation resistance-based strain gauge (HE-RSG) for their ability to monitor strained Kevlar straps having a 26.7 kN (6 klbf) load. Dynamic, static and cyclic loads were used to characterize both types of strain monitoring devices. Printed CSGs demonstrated superior performance for high elongation strain measurements when compared to commonly used HE-RSGs, and were observed to operate with a gauge factor of 5.2 when the electrode arrangement was perpendicular to the direction of strain.

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“…Despite the aforementioned unique advantages and the broad range of applications engendered by AJP, the process is highly unstable, complex, and prone to gradual drifts in machine behavior, leading to suboptimal (and sometimes unsatisfactory) material deposition and device fabrication [21,22]. Formation of overspray (and satellite particles), deposition of lines with discontinuous edges, excess generation of aerosols, and inconsistent flow collimation are examples of adverse phenomena, which cause a deviation from optimal regimes in AJP process.…”

Section: Introductionmentioning

confidence: 99%

“…To a great extent, changes in material formulation and properties are the leading cause of the AJP process complexity. The fluctuation of material properties stems from, for example, ink temperature instability as well as solvent evaporation, leading to ink predrying and/or particle accumulation within the deposition head [22,23]. Consequently, implementation of physics-driven in situ process monitoring and control in the AJP process is inevitably a need.…”

Section: Introductionmentioning

confidence: 99%

“…To realize this objective, the authors have already introduced an image-based platform for near real-time process monitoring as well as closed-loop control in AJP, as delineated in Refs. [21], [22], and [24][25][26][27][28][29]. The AJP system (machine) was integrated with temporal and image-based sensors, allowing for near real-time data acquisition from the process.…”

Section: Introductionmentioning

confidence: 99%

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A Computational Fluid Dynamics Investigation of Pneumatic Atomization, Aerosol Transport, and Deposition in Aerosol Jet Printing Process

Salary

Lombardi

Weerawarne

et al. 2021

Journal of Micro and Nano-Manufacturing

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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.

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Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process

Cited by 81 publications

References 45 publications

Challenges on optimization of 3D-printed bone scaffolds

Challenges on optimization of 3D-printed bone scaffolds

Aerosol jet printed capacitive strain gauge for soft structural materials

A Computational Fluid Dynamics Investigation of Pneumatic Atomization, Aerosol Transport, and Deposition in Aerosol Jet Printing Process

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