3D printing technology has revolutionized the production of complex and customized polymer structures. However, one of the challenges faced in 3D printing is optimizing the electrical performance of these structures. This is especially important in applications such as electrical circuits, sensors, and electro active devices. To address this challenge, evolutionary algorithms have emerged as a promising approach. These algorithms mimic the process of natural selection and evolution, allowing for the optimization of complex systems with multiple parameters. In the context of 3D-printed polymer structures, evolutionary algorithms can be used to find the optimal arrangement of conductive materials, such as metal or carbon-based fillers, within the polymer matrix. One of the key advantages of using evolutionary algorithms is their ability to explore an ample design space and find optimal solutions that may need to be clarified for human designers. This is particularly beneficial in 3D printing, where the design possibilities are virtually unlimited. It also allows for considering multiple objectives in the optimization process, such as electrical conductivity, mechanical strength, and cost. Applying evolutionary algorithms in the 3D printing polymer structures involves a multi-step process. The design parameters and objectives are defined. Then, the evolutionary algorithm is used to generate a population of potential designs. Using simulation or experimental techniques, these designs are then evaluated for their electrical performance. The algorithm then selects the best-performing designs and combines them to create new, potentially better designs. This process continues until the desired electrical performance is achieved. The use of evolutionary algorithms in the 3D printing of polymer structures holds great promise for optimizing their electrical performance. As this technology continues to evolve, it is expected to enable the production of more efficient and functional polymer structures for various electrical applications.

Target Audience
The target audience is primarily researchers and engineers in materials science, electrical engineering, and additive manufacturing. This includes professionals in electronics, bioengineering, and aerospace industries. More specifically, the special issue would interest those looking to improve the electrical performance of 3D-printed polymer structures through evolutionary algorithms. This could include researchers and engineers looking for new methods and techniques for optimizing the electrical properties of 3D printed materials and those interested in the potential applications of such materials in various industries. It may also attract academics and graduate students in related fields, such as computer science and artificial intelligence, interested in the intersection of evolutionary algorithms and 3D printing technology.
The target audience for this special issue is a niche but growing community of professionals and researchers passionate about pushing the boundaries of 3D printing technology and its potential for various industries.

List of Topics to be covered
1. Material selection for 3D printing electrical components
2. Structural design optimization for electrical performance
3. Multi-objective optimization for electrical and mechanical performance
4. Integration of conductive materials in 3D printing process
5. Optimal placement of electrical components in 3D printed structures
6. Effect of printing parameters on electrical properties
7. Use of evolutionary algorithms in optimizing electrical performance
8. Electrical conductivity measurement and characterization in 3D printed structures
9. Post-processing techniques for improving electrical properties of 3D printed structures
10. Thermal management in 3D printed electrical structures
11. Role of infill patterns in electrical performance of 3D printed parts
12. Optimization of support structures for minimizing electrical interference
13. Use of embedded sensors for monitoring electrical performance in 3D printed parts
14. Novel designs for improving electrical conductivity in 3D printed structures
15. Impact of layer orientation on electrical properties of 3D printed parts
16. Application of topology optimization in improving electrical performance
17. Utilization of Metaheuristic algorithms for optimizing electrical properties
18. Strategies for reducing electromagnetic interference in 3D printed electronics
19. Advancements in conductive filaments for enhanced 3D printing of electrical components
20. Real-time monitoring and control of electrical performance during 3D printing process

Submission Guidelines
We invite original research articles, innovative reviews, and perspectives covering the topics
above. Authors are requested to follow the journal’s guidelines and formatting. All submissions
will undergo a thorough peer-review process to ensure high-quality articles for publication.

Important Deadline
> Deadline for Abstract Submission: April 30, 2024
> Full Paper Submission: May 31, 2024
> Notification of Acceptance: August 10, 2024
> Publication: September 15, 2024

Guest Editors
> Jaganathan Logeshwaran, Sri Eshwar College of Engineering, Coimbatore-641202,
India ( | Google Scholar:
> Dr. S. Raja, Center for Additive Manufacturing, Chennai Institute of Technology,
Chennai, Tamil Nadu, India-600069 ( | Google Scholar: