Data‐driven science and technology have helped achieve meaningful technological advancements in areas such as materials/drug discovery and health care, but efforts to apply high‐end data science algorithms to the areas of glass and ceramics are still limited. Many glass and ceramic researchers are interested in enhancing their work by using more data and data analytics to develop better functional materials more efficiently. Simultaneously, the data science community is looking for a way to access materials data resources to test and validate their advanced computational learning algorithms. To address this issue, The American Ceramic Society (ACerS) convened a Glass and Ceramic Data Science Workshop in February 2018, sponsored by the National Institute for Standards and Technology (NIST) Advanced Manufacturing Technologies (AMTech) program. The workshop brought together a select group of leaders in the data science, informatics, and glass and ceramics communities, ACerS, and Nexight Group to identify the greatest opportunities and mechanisms for facilitating increased collaboration and coordination between these communities. This article summarizes workshop discussions about the current challenges that limit interactions and collaboration between the glass and ceramic and data science communities, opportunities for a coordinated approach that leverages existing knowledge in both communities, and a clear path toward the enhanced use of data science technologies for functional glass and ceramic research and development.
This content will become publicly available on August 2, 2025
3D printing (3DP) technologies have transformed the processing of advanced ceramics for small‐scale and custom designs during the past three decades. Simple and complex parts are designed and manufactured using 3DP technologies for structural, piezoelectric, and biomedical applications. Manufacturing simple or complex geometries or one‐of‐a‐kind components without part‐specific tooling saves significant time and creates new applications for advanced ceramic materials. Although development and innovations in 3DP of ceramics are far behind compared with metals or polymers, with the availability of different commercial machines in recent years for 3DP of ceramics, exponential growth is expected in this field in the coming decade. This article details various 3DP technologies for advanced ceramic materials, their advantages and challenges for manufacturing parts for various applications, and perspectives on future directions. We envision this work will be helpful to advanced ceramic researchers in industry and academia who are using different 3DP processes in the coming days.
more » « less- Award ID(s):
- 1934230
- NSF-PAR ID:
- 10536407
- Publisher / Repository:
- Journal of the American Ceramic Society, Wiley
- Date Published:
- Journal Name:
- Journal of the American Ceramic Society
- ISSN:
- 0002-7820
- Subject(s) / Keyword(s):
- 3D Printing Ceramics Additive manufacturing
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Abstract -
null (Ed.)Ceramics derived from organic polymer precursors, which have exceptional mechanical and chemical properties that are stable up to temperatures slightly below 2000 °C, are referred to as polymer-derived ceramics (PDCs). These molecularly designed amorphous ceramics have the same high mechanical and chemical properties as conventional powder-based ceramics, but they also demonstrate improved oxidation resistance and creep resistance and low pyrolysis temperature. Since the early 1970s, PDCs have attracted widespread attention due to their unique microstructures, and the benefits of polymeric precursors for advanced manufacturing techniques. Depending on various doping elements, molecular configurations, and microstructures, PDCs may also be beneficial for electrochemical applications at elevated temperatures that exceed the applicability of other materials. However, the microstructural evolution, or the conversion, segregation, and decomposition of amorphous nanodomain structures, decreases the reliability of PDC products at temperatures above 1400 °C. This review investigates structure-related properties of PDC products at elevated temperatures close to or higher than 1000 °C, including manufacturing production, and challenges of high-temperature PDCs. Analysis and future outlook of high-temperature structural and electrical applications, such as fibers, ceramic matrix composites (CMCs), microelectromechanical systems (MEMSs), and sensors, within high-temperature regimes are also discussed.more » « less
-
null (Ed.)Emulating the unique combination of structural, compositional, and functional gradation in natural materials is exceptionally challenging. Many natural structures have proved too complex or expensive to imitate using traditional processing techniques despite recent advances. Recent innovations within the field of additive manufacturing (AM) or 3D Printing (3DP) have shown the ability to create structures that have variations in material composition, structure, and performance, providing a new design-for-manufacturing platform for the imitation of natural materials. AM or 3DP techniques are capable of manufacturing structures that have significantly improved properties and functionality over what could be traditionally-produced, giving manufacturers an edge in their ability to realize components for highly-specialized applications in different industries. To this end, the present work reviews fundamental advances in the use of naturally-inspired design enabled through 3DP / AM, how these techniques can be further exploited to reach new application areas and the challenges that lie ahead for widespread implementation. An example of how these techniques can be applied towards a total hip arthroplasty application is provided to spur further innovation in this area.more » « less
-
Abstract Despite groundbreaking advances in the additive manufacturing of polymers, metals, and ceramics, scaled and accurate production of structured carbons remains largely underdeveloped. This work reports a simple method to produce complex carbon materials with very low dimensional shrinkage from printed to carbonized state (less than 4%), using commercially available polypropylene precursors and a fused filament fabrication-based process. The control of macrostructural retention is enabled by the inclusion of fiber fillers regardless of the crosslinking degree of the polypropylene matrix, providing a significant advantage to directly control the density, porosity, and mechanical properties of 3D printed carbons. Using the same printed plastic precursors, different mechanical responses of derived carbons can be obtained, notably from stiff to highly compressible. This report harnesses the power of additive manufacturing for producing carbons with accurately controlled structure and properties, while enabling great opportunities for various applications.
-
The materials’ consolidation, especially ceramics, is very important in advanced research development and industrial technologies. Science of sintering with all incoming novelties is the base of all these processes. A very important question in all of this is how to get the more precise structure parameters within the morphology of different ceramic materials. In that sense, the advanced procedure in collecting precise data in submicro-processes is also in direction of advanced miniaturization. Our research, based on different electrophysical parameters, like relative capacitance, breakdown voltage, and [Formula: see text], has been used in neural networks and graph theory successful applications. We extended furthermore our neural network back propagation (BP) on sintering parameters’ data. Prognosed mapping we can succeed if we use the coefficients, implemented by the training procedure. In this paper, we continue to apply the novelty from the previous research, where the error is calculated as a difference between the designed and actual network output. So, the weight coefficients contribute in error generation. We used the experimental data of sintered materials’ density, measured and calculated in the bulk, and developed possibility to calculate the materials’ density inside of consolidated structures. The BP procedure here is like a tool to come down between the layers, with much more precise materials’ density, in the points on morphology, which are interesting for different microstructure developments and applications. We practically replaced the errors’ network by density values, from ceramic consolidation. Our neural networks’ application novelty is successfully applied within the experimental ceramic material density [Formula: see text] [kg/m 3 ], confirming the direction way to implement this procedure in other density cases. There are many different mathematical tools or tools from the field of artificial intelligence that can be used in such or similar applications. We choose to use artificial neural networks because of their simplicity and their self-improvement process, through BP error control. All of this contributes to the great improvement in the whole research and science of sintering technology, which is important for collecting more efficient and faster results.more » « less