A review on the advances in 3D printing and additive manufacturing of ceramics and ceramic matrix composites for optical applications

Goodman, William A.

doi:10.1117/12.2269394

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…(b) A layout of global morphology parameters (left) and the corresponding GAN-Synµ S. Foreground regions were "painted" with 1 in panel (a) while the background was painted with 0 . www.nature.com/scientificreports/ with the on-going micro-scale additive manufacturing (or micro 3D printing) techniques 13,21,27,66 , the present controlled micro-morphology generation technique can lead to the realization of microstructure-engineered materials, which is being pursued by the authors in ongoing work.…”

Section: Simulations Of Reactive Dynamics In Real and Synthetic Micromentioning

confidence: 99%

“…The frontier in computational energetic materials research is to develop predictive multi-scale models to guide the design process of novel materials with tailored performance via microstructural control 12,13 . Predictive frameworks of energetic material response to loads are a matter of concerted current development by several groups worldwide [14][15][16][17][18][19][20] ; such capabilities are needed to establish structure-property-performance (S-P-P) linkages as necessary precursors to materials-by-design of heterogeneous materials 12,21,22 . The work presented previous approaches.…”

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confidence: 99%

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Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

Chun

Roy

Nguyen

et al. 2020

Sci Rep

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the sensitivity of heterogeneous energetic (He) materials (propellants, explosives, and pyrotechnics) is critically dependent on their microstructure. initiation of chemical reactions occurs at hot spots due to energy localization at sites of porosities and other defects. emerging multi-scale predictive models of He response to loads account for the physics at the meso-scale, i.e. at the scale of statistically representative clusters of particles and other features in the microstructure. Meso-scale physics is infused in machine-learned closure models informed by resolved meso-scale simulations. Since microstructures are stochastic, ensembles of meso-scale simulations are required to quantify hot spot ignition and growth and to develop models for microstructure-dependent energy deposition rates. We propose utilizing generative adversarial networks (GAn) to spawn ensembles of synthetic heterogeneous energetic material microstructures. the method generates qualitatively and quantitatively realistic microstructures by learning from images of He microstructures. We show that the proposed GAn method also permits the generation of new morphologies, where the porosity distribution can be controlled and spatially manipulated. Such control paves the way for the design of novel microstructures to engineer He materials for targeted performance in a materials-by-design framework.

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Section: Simulations Of Reactive Dynamics In Real and Synthetic Micromentioning

confidence: 99%

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confidence: 99%

Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

Chun

Roy

Nguyen

et al. 2020

Sci Rep

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“…Since ceramics can now be 3D-printed (Goulas et al 2016;Costa et al 2017;Goodman 2017;Singh et al 2017;Ferrage et al 2018;Owen et al 2018) they should be considered as rock simulants since they have various mechanical properties that are closer to rocks than polymers. Up to the time of writing there have been no published investigations of the use of printed ceramic or natural rock materials in rock mechanics studies (Zhou and Zhu 2018).…”

Section: Studies Of Materials So Far Used In 3d Printing Of Rock Simumentioning

confidence: 99%

Review of the Validity of the Use of Artificial Specimens for Characterizing the Mechanical Properties of Rocks

2019

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The field of rock mechanics is concerned with the response of rocks to the forces acting on them, characterizing this behaviour in specific environments and under varying loading conditions. This review discusses the suitability of current mechanical testing methods for inhomogeneous rock bodies, with a specific focus on the use of artificial samples in place of real rocks in these tests. The use of artificial materials such as cement, resins, and sand-based mixtures is reviewed, as is the manufacture of three-dimensionally printed samples. The benefits and drawbacks of using such specimens in mechanical tests, and the validity of their simulation of real rock are discussed. There is evidence that 3D-printed samples have the advantage of overcoming the problems of specimen reproducibility and also make possible the ability to test the response of specific defects to loading. There is thus great potential for the use of 3D printing in this field. However, the review concludes that further post-processing and careful thought about the materials used must be carried out to ensure that printed samples are of adequate strength and brittleness to accurately simulate real rocks.

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“…VPP presents one of the greatest printing resolutions and best surface quality among other AM techniques, making it a suitable microfabrication technology for applications in photonics , and microfluidics. , The lack of a wide variety of processable materials is one of the main factors hindering the extensive application of VPP techniques, , since only acrylate, epoxy, and thiol-ene organic functions can react through the photopolymerization mechanism. , Recently, numerous studies have been conducted to expand the range of materials that can be processed by VPP, with a focus on ceramics and inorganic glasses. One of the most promising methods is the hybrid sol–gel process to achieve a photopolymerizable resin, resulting in a hybrid material, − which can be further heat-treated to remove the organic components, and form a ceramic material − or an inorganic glass. − …”

Section: Introductionmentioning

confidence: 99%

Correlation between Critical Energy, Penetration Depth, and Photopolymerization Kinetics in Aluminum–Phosphate–Silicate Hybrid Materials for Vat Photopolymerization

et al. 2023

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The photopolymerization of aluminum–phosphate–silicate resins obtained from the hybrid sol–gel route for Vat photopolymerization (VPP) process was investigated. The printing parameters derived from Jacob’s work curve model, critical energy (E c) and penetration depth (D p), were determined as a function of laser power and MPTMS (silicate) concentration for materials with stoichiometry Si(x)-(Al + P)(1–x), 0 ≤ x ≤ 0.7. The kinetics of photopolymerization was further explored using steady- and unsteady-state photo-DSC experiments. The oxygen inhibition and primary termination had similar contributions to the polymerization process for all compositions, while the propagation and bimolecular termination constants increased with MPTMS concentration. These experimental results were used to test the validity of the E c ∝ k t 1/2/k p and D p ∝ ϵ relationship derived from a photochemical model for VPP assuming steady-state kinetics. Both E c ∝ (k t 1/2/k p) and D p ∝ ϵ may be used to predict critical energy and penetration values for an arbitrary resin without calculating its work curve function, according to our study.

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A review on the advances in 3D printing and additive manufacturing of ceramics and ceramic matrix composites for optical applications

Cited by 5 publications

References 4 publications

Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

Review of the Validity of the Use of Artificial Specimens for Characterizing the Mechanical Properties of Rocks

Correlation between Critical Energy, Penetration Depth, and Photopolymerization Kinetics in Aluminum–Phosphate–Silicate Hybrid Materials for Vat Photopolymerization

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