Bibliographic Details
| Title: |
Digital manufacturing of advanced materials: Challenges and perspective. |
| Authors: |
Lin, Linhan1 (AUTHOR) linlh04@utexas.edu, Kollipara, Pavana Siddhartha1 (AUTHOR), Zheng, Yuebing1 (AUTHOR) zheng@austin.utexas.edu |
| Source: |
Materials Today. Sep2019, Vol. 28, p49-62. 14p. |
| Subjects: |
Manufacturing processes, Materials science, Materials, Three-dimensional printing, Production engineering, Three-dimensional display systems, Nanofabrics |
| Abstract: |
The rapid development in materials science and engineering requests the manufacturing of materials in a more rational and designable manner. Beyond traditional manufacturing techniques, such as casting and coating, digital control of material morphology, composition, and structure represents a highly integrated and versatile approach. Digital manufacturing systems enable users to fabricate freeform materials, which lead to new functionalities and applications. Digital additive manufacturing (AM), which is a layer-by-layer fabrication approach to create three-dimensional (3D) products with complex geometries, is changing the way materials manufacturing is approached in traditional industry. More recently, digital printing of chemically synthesized colloidal nanoparticles has paved the way toward manufacturing a class of designer nanomaterials with properties precisely tailored by the nanoparticles and their interactions down to atomic scales. Despite the tremendous progress being made so far, multiple challenges have prevented the broader applications and impacts of the digital manufacturing technologies. This review features cutting-edge research in the development of some of the most advanced digital manufacturing methods. We focus on outlining major challenges in the field and providing our perspectives on the future research and development directions. [ABSTRACT FROM AUTHOR] |
|
Copyright of Materials Today is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |