AI for Manufacturing of Micro and Nano-Structures and Devices
A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D：Materials and Processing".
Deadline for manuscript submissions: closed (1 July 2021) | Viewed by 4284
Special Issue Editor
Special Issue Information
Dear Colleagues,
In the last few decades, the development of machine-learning algorithms, AI systems coupled with robotics, and data-driven technologies has propelled development in the fields of industry production, autonomous vehicles, medicine, defense, telecommunications, the software industry, and business. The basis of this development goes back to the early 1950s, but in the last fifteen years it has reached full expansion thanks to a multi-fold increase of computing power. In recent years, AI technologies with robotics timidly started to emerge in the field of materials research, mainly focusing on unmanned processes of new materials discovery and, more rarely, the manufacturing of simple micro-and nano-scale objects. Consequently, progress in this field could accelerate the development of reproducible complex microstructures and molecular systems such as smart dust, microbots, and nanobots. However, the lack of researchers engaged in the enhancement of existing synthetic procedures with AI and those that could bring novel solutions, as a bridge between chemistry and AI engineering, creates a gap in the academic research and a need for interdisciplinary connections in this topic. Therefore, this Special Issue is directed towards research papers and review articles on the following topics: 1) the implementation of machine-learning algorithms and AI for monitoring and controlling the fabrication processes of micro- and nanostructures; 2) novel designs of processes and instruments augmented with AI for material research and chemical synthesis; 3) novel algorithms tailored for applications in chemistry and materials science.
Dr. Zoran Stojanovic
Guest Editor
Manuscript Submission Information
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Keywords
- materials engineering
- materials design
- materials fabrication
- microfabrication
- nanofabrication
- microfluidics
- artificial intelligence (AI)
- machine learning
- reinforcement learning
- deep learning
- automation
- robotics
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