Bioinspired Designs for Additive Manufacturing in Advanced Engineering Applications

Dear Colleagues,

The recent advances and the implementation of research in the areas of bio-inspired design and additive manufacturing have led to applications of various fields, such as aerospace, maritime, nuclear, defense, acoustic, thermal, soft machines, robots, bio-interfaces, and health care applications. Functional materials and systems that imitate the properties or mechanisms of biological tissues, agents, and behaviors are abundant in biology. Additive manufacturing has enabled the fabrication of materials and structures that are prevalent in biology, with lessons learned from nature leading to more lightweight structures. The development of low-cost manufacturing technologies allows various engineering applications of effective bio-inspired structures and the understanding and collection of naturally occurring structures that could further facilitate simulation-driven design and selection of the design outcome most similar to the biological structure will likely be the best solution for the manufacturing technologies. This can further enable the possibility of data-driven methodologies and machine learning (ML) in engineering structural design. Furthermore, the novel paradigm of the ML-based approach can largely accelerate the new material design, boasting orders of magnitude increases in computational efficacy over conventional methods for advanced engineering applications.  

This Special Issue, titled “Bioinspired Designs for Additive Manufacturing in Advanced Engineering Applications”, aims to exhibit new research achievements, findings, perspectives, and ideas for the future development of bioinspired new functional materials. Some of its focal points include but are not limited to the following:

1. Bioinspiration of natural synthetic mechanisms and biomimetic principles for additive manufacturing;
2. Biostructures in the form of lamellar, columnar, coaxial layered, and array structured for bio functions like acoustic, optical, thermal, electrical, mechanical, and magnetic properties;
3. Machine learning-assisted bioinspired designs for superior mechanical performances.

It is our pleasure to invite you to submit a manuscript for this Special Issue. Full papers, short communications, and reviews are welcome.

Dr. Nikhil Kamboj
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• strategies and concepts of bioinspired designs
• additive manufacturing
• applications and performances of bioinspired materials (e.g., aerospace, maritime, nuclear, defense, acoustic, thermal, soft machines, robots, bio-interfaces, and health care)
• processing of bioinspired materials
• functional materials
• simulations-driven design
• simulations of bioinspired materials at all length scales
• machine learning
• mechanical properties