Ceramic Robocasting: Recent Achievements, Potential, and Future Developments

Peng, Erwin; Zhang, Danwei; Ding, Jun

doi:10.1002/adma.201802404

Cited by 247 publications

(172 citation statements)

References 109 publications

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“…3D architecture control in functional devices has opened up unprecedented opportunities beyond those offered by their 2D counterparts . Among various options, 3D printing stands out in their freedom to manipulate geometric shapes in an almost unlimited fashion . As such, 3D printing has shown great promises in a wide variety of engineering applications including medical devices, aerospace structures, energy devices, and soft robotics .…”

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confidence: 99%

Rapid Open‐Air Digital Light 3D Printing of Thermoplastic Polymer

et al. 2019

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printing is, however, limited by various factors, with printing speed and material versatility being the most decisive. From the standpoint of printing speed, layerwise printing by digital light processing (DLP) offers significant inherent advantage over point-wise printing by most other methods such as fused deposition modeling (FDM) and stereolithography (SLA). [20] Further innovations on DLP such as continuous building in the z-dimension allow achieving a printing speed far exceeding any other methods. [21][22][23] Recent attempt on direct forming 3D object in a volumetric fashion forgoes even the layer-wise printing, but the technique has yet to evolve into the mainstream. [24,25] Generally, DLP employs light curable liquid resins. Upon digital light exposure, the resin cross-links and forms a thermoset polymer that ensures its separation from the surrounding liquid precursors. This rapid liquid-solid separation is the key enabling characteristic for DLP. Although cross-linking ensures such, the resulting thermoset polymers cannot be reprocessed. This prohibits its broader utility in situations that require further processing of the printed materials. In principle, this limitation can be overcome if the DLP processing can be extended to reprocessable thermoplastic polymers. Although light curable thermoplastic polymers are known, meeting the unique DLP requirement for rapid separation between the liquid monomer and the un-crosslinked polymer is not straightforward because of their intrinsic good miscibility. Hereafter, we describe our successful attempt in DLP printing of a thermoplastic polymer and lay out key enabling factors for such a process. We further illustrate that the water dissolvable nature of the resulting polymer is advantageous in making various multifunctional 3D structures. We find that the oxygen naturally present in ambient air can inhibit the light curing process. This effect can be utilized to achieve rapid open-air printing without the complex interfacial engineering typically required for fast DLP printing methods. [21][22][23] We hypothesize that two key factors should be carefully considered for DLP printing of thermoplastic polymers (Figure 1a). Herein, two concurrent and competing processes occur: 1) the polymerization and 2) the diffusion/dissolution of the polymer into the surrounding uncured liquid monomer. Rapid liquidsolid separation is possible only if the first process dominates 3D printing has witnessed a new era in which highly complexed customized products become reality. Realizing its ultimate potential requires simultaneous attainment of both printing speed and product versatility. Among various printing techniques, digital light processing (DLP) stands out in its high speed but is limited to intractable light curable thermosets. Thermoplastic polymers, despite their reprocessibility that allows more options for further manipulation, are restricted to intrinsically slow printing methods such as fused deposition modeling. Extending DLP to thermoplastics is highly desirabl...

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confidence: 99%

Rapid Open‐Air Digital Light 3D Printing of Thermoplastic Polymer

et al. 2019

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“…The density of ZrO 2 samples is 97%, which is comparable with those of general reported ceramics fabricated by DIW. 20 For FEM simulation, the designed models were imported to ANSYS Workbench firstly. Then, the designed models were divided into nearly 20 000 small hexahedrons and these hexahedrons were contacted with each other by more than 100 000 nodes.…”

Section: Finite Element Methods Simulation and Failure Criterionmentioning

confidence: 99%

Application of artificial neural network optimization for resilient ceramic parts fabricated by direct ink writing

Fan

Feng

Yang

et al. 2019

Int J Applied Ceramic Tech

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Geometries of ceramic parts for high-temperature sealing have great influence on their compression-resilience behaviors. In this work, an accurate and large-scale artificial neural network (ANN) was established to match the relationship between structural parameters and mechanical properties of ZrO 2 parts fabricated by 3D printing. Four geometry parameters of the designed ZrO 2 parts were imported as input and apparent Young's modulus and maximum deformation simulated by finite element method (FEM) were imported as output. FEM calculation provided 400 groups of data for the training of ANN, which greatly improved the predicted accuracy of the network. The predicted results show the mechanical performance of the parts with a range of modulus from 9.24 × 10 −3 GPa to 100.35 × 10 −3 GPa and a range of maximum deformation from 2.32% to 5.80% can be forecasted with error less than 8%. Based on the optimized structural parameters, the designed ZrO 2 parts were fabricated by Direct Ink Writing (DIW) technique. The experimental compressionrebound property is comparable to that of ANN prediction. It demonstrates that the combined method of ANN and FEM is a preferable way to optimize the structure and guide the fabrication of complex ceramic parts by 3D printing method. K E Y W O R D Sadditive manufacturing, artificial neural network, finite element analysis, sealing 218 | FAN et Al. where N is the number of output, y n is the predicted value of the n th item, d n is the target value of the n th , and Q is the number of training cycle. Then the 400 groups of data were divided randomly into three parts: training groups, validation groups, and test groups with the ratio of 70%, 15%, and 15%. The network would stop training when the MSE of validation did not decrease continuously more than six times, otherwise the network was not good at generalization. Similarly, the network would also stop training when the training epochs came to 100 or the value of MSE was less than 0.00001.

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“…[22][23][24] Although 3D-printing is an inherently slow process, its greatest virtue is the application of prototyping processes and miniaturization: the modulation of the shape and size of monoliths with precision is made possible, including cross sections, pore size and wall thicknesses, thus maximizing the catalytic surface. [25,26] The main manufacturing techniques used by 3D-printing for the synthesis of monolithic catalysts include fused deposition modeling (FDM), [27] direct ink writing (robocasting) [28] and stereo-lithography (SLA). [29] Several groups recently described the use of 3D printing techniques and different strategies to obtain monolithic structures in which different metal species are immobilized.…”

Section: Introductionmentioning

confidence: 99%

Integrating Reactors and Catalysts through Three‐Dimensional Printing: Efficiency and Reusability of an Impregnated Palladium on Silica Monolith in Sonogashira and Suzuki Reactions

et al. 2020

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For this work, an integrated system composed of a polypropylene reactor and a palladium on silica monolithic catalyst was designed and manufactured by 3D‐printing. These devices are able to perform solution phase chemistry in a robotic orbital shaker. The capped reactor was obtained in its entirety by 3D‐printing, using polypropylene and fused deposition modeling. The monolithic catalyst was also obtained by 3D‐printing ‐robocasting‐ of a silica support, sintering and subsequent palladium deposition through the wet impregnation method. The catalytic efficiency in Sonogashira or Suzuki reactions as well as the recyclability of the entire system – catalyst+reactor – were studied. The strong electrostatic adsorption (SEA) of the palladium on sintered silica and the reduced mechanical stress produced by the convenient adjustment of the catalyst into the polypropylene reactor makes the catalytic system reusable without significant loss of catalytic activity.

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Ceramic Robocasting: Recent Achievements, Potential, and Future Developments

Cited by 247 publications

References 109 publications

Rapid Open‐Air Digital Light 3D Printing of Thermoplastic Polymer

Rapid Open‐Air Digital Light 3D Printing of Thermoplastic Polymer

Application of artificial neural network optimization for resilient ceramic parts fabricated by direct ink writing

Integrating Reactors and Catalysts through Three‐Dimensional Printing: Efficiency and Reusability of an Impregnated Palladium on Silica Monolith in Sonogashira and Suzuki Reactions

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