Polymeric Additive Manufacturing: The Necessity and Utility of Rheology

Elbadawi, Moe

doi:10.5772/intechopen.77074

Cited by 25 publications

(30 citation statements)

References 62 publications

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“…The shear thinning index (STI)-the ratio of viscosity at two different shear rates-was used to estimate the extent of non-Newtonian behavior exhibited by the magnetic paste formulations [23]. Rheological analysis of magnetic pastes is essential for understanding the paste behavior at different shear rates experienced by the paste inside the cylinder barrel and nozzle for 3D printing processes [24]. Moreover, to understand the influence of temperature on flow behavior, the viscosity of the magnetic pastes was measured at different temperatures (i.e.…”

Section: Rheological Characterizationmentioning

confidence: 99%

Development and Characterization of Stable Polymer Formulations for Manufacturing Magnetic Composites

Nagarajan

Kamkar

Schoen

et al. 2020

JMMP

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Polymer bonded permanent magnets find significant applications in a multitude of electrical and electronic devices. In this study, magnetic particle-loaded epoxy resin formulations were developed for in-situ polymerization and material jetting based additive manufacturing processes. Fundamental material and process issues like particle settling at room temperature and elevated temperature curing, rheology control and geometric stability of the magnetic polymer during the thermal curing process are addressed. Control of particle settling, modifications in rheological behavior and geometric stability were accomplished using an additive that enabled the modification of the formulation behavior at different process conditions. The magnetic particle size and additive loading were found to influence the rheological properties significantly. The synergistic effect of the additive enabled the developing of composites with engineered magnetic filler loading. Morphological characterization using scanning electron microscopy revealed a homogenous particle distribution in composites. It was observed that the influence of temperature was profound on the coercive field and remanent magnetization of the magnetic composites. The characterization of magnetic polymers and composites using rheometry, scanning electron microscopy, X-ray diffraction and superconducting quantum interference device (SQUID) magnetometry analysis enabled the correlating of the behavior observed in different stages of the manufacturing processes. Furthermore, this fundamental research facilitates a pathway to construct robust materials and processes to develop magnetic composites with engineered properties.

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Section: Rheological Characterizationmentioning

confidence: 99%

Development and Characterization of Stable Polymer Formulations for Manufacturing Magnetic Composites

Nagarajan

Kamkar

Schoen

et al. 2020

JMMP

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“…One characterization technique that captures the essence of FDM extrusion, and is a staple in formulation development, is rheology (Elbadawi et al, 2018;Isreb et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

3D printing tablets: Predicting printability and drug dissolution from rheological data

Elbadawi

Gustaffson

Gaisford

et al. 2020

International Journal of Pharmaceutics

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Rheology is an indispensable tool for formulation development, which when harnessed, can both predict a material's performance and provide valuable insight regarding the material's macrostructure. However, rheological characterizations are under-utilized in 3D printing of drug formulations. In this study, viscosity measurements were used to establish a mathematical model for predicting the printability of fused deposition modelling 3D printed tablets (Printlets). The formulations were composed of polycaprolactone (PCL) with different amounts of ciprofloxacin and polyethylene glycol (PEG), and different molecular weights of PEG. With all printing parameters kept constant, both binary and ternary blends were found to extrude at nozzle temperatures of 130, 150 and 170 C. In contrast PCL was unextrudable at 130 and 150 C. Three standard rheological models were applied to the experimental viscosity measurements, which revealed an operating viscosity window of between 100-1000 Pa.s at the apparent shear rate of the nozzle. The drug profile of the printlets were experimentally measured over seven days. As a proof-of-concept, machine learning models were developed to predict the dissolution behaviour from the viscosity measurements. The machine learning models were discovered to accurately predict the dissolution profile, with the highest f2 similarity score value of 90.9 recorded. Therefore, the study demonstrated that using only the viscosity measurements can be employed for the simultaneous high-throughput screening of formulations that are printable and with the desired release profile.

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“…Obviously, in the 3D-printed oil painting model shown in Figure 5d with our proposed reverse-sequence method, the staircase effect of the corresponding positions is not easily detectable by the human eye. This can be explained by the actual phase change characteristics of the jetting droplets array; for instance, some droplets in upper ink layer with planar droplets array are slightly flowing due to the lack of support prior to sufficient solidification [43,44], thus easing the adjacent boundary between the upper large ink layer and the lower smaller slice layer.…”

Section: Physical Visualization Of Three Photogrammetry-based Oil Painting Modelsmentioning

confidence: 99%

3D Printing of Oil Paintings Based on Material Jetting and Its Reduction of Staircase Effect

et al. 2020

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Material jetting is a high-precision and fast 3D printing technique for color 3D objects reproduction, but it also suffers from color accuracy and jagged issues. The UV inks jetting processes based on the polymer jetting principle have been studied from printing materials regarding the parameters in the default layer order, which is prone to staircase effects. In this work, utilizing the Mimaki UV inks jetting system with a variable layer thickness, a new framework to print a photogrammetry-based oil painting 3D model has been proposed with the tunable coloring layer sequence to improve the jagged challenge between adjacent layers. Based on contour tracking, a height-rendering image of the oil painting model is generated, which is further segmented and pasted to the corresponding slicing layers to control the overall printing sequence of coloring layers and white layers. The final results show that photogrammetric models of oil paintings can be printed vividly by UV-curable color polymers, and that the proposed reverse-sequence printing method can significantly improve the staircase effect based on visual assessment and color difference. Finally, the case of polymer-based oil painting 3D printing provides new insights for optimizing color 3D printing processes based on other substrates and print accuracy to improve the corresponding staircase effect.

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Polymeric Additive Manufacturing: The Necessity and Utility of Rheology

Cited by 25 publications

References 62 publications

Development and Characterization of Stable Polymer Formulations for Manufacturing Magnetic Composites

Development and Characterization of Stable Polymer Formulations for Manufacturing Magnetic Composites

3D printing tablets: Predicting printability and drug dissolution from rheological data

3D Printing of Oil Paintings Based on Material Jetting and Its Reduction of Staircase Effect

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