Research Topic

Artificial Intelligence Approaches in the Design of Architected Materials

About this Research Topic

Architected materials have been emerged as a class of (mechanical, acoustic, photonic, electromagnetic, etc.) metamaterials whose tailor-made and exotic properties (e.g., negative Poisson’s ratio, negative stiffness and negative thermal expansion) are the consequence of interplay between the geometry and material properties. The success of achieving such unusual properties thus relies on finding rational microarchitectural designs which can also be extremely challenging to explore. The current progress of architected materials, therefore, owes to the thriving synergy between the development of advanced multiphysics computational (e.g., finite element models together with topology optimization algorithms) and analytical models from one hand and advanced manufacturing (e.g., additive manufacturing, AM also known as 3D printing) technologies from another hand.

Recently, artificial intelligence (AI) technology and its corresponding subcategories such as Machine learning (ML) (e.g., via neural networks) as well as Deep Learning (DL) approaches have found their roots in the design of architected materials. These technologies have provided unparallel and powerful tools for engineers to expand the design space of architected materials even further and push the limits of achievable properties and functionalities. AI technology can, therefore, revolutionize the way that architected materials have traditionally been designed and engineered and replace them by smart machines as intelligent designers. This new design paradigm can also be beneficial for many high-tech industries such as biomedical and aeronautical engineering.

This Research Topic aims to provide a comprehensive overview of the recent progress and developments in the field of implementation of AI technology in the design of architected materials. We also aim to present the latest findings of various disciplines such as physics, material science, mechanics, electronics, computer science, and biomedical engineering towards the application of AI technologies in the development of these advanced materials. The fabrication techniques may include but not limited to (multi-material) 3D printing and 4D printing technologies. Therefore, we encourage contributors to submit their most recent studies under the form of Original Research, Reviews, Mini-reviews, communication articles on the following themes:

• AI and their applications in the design and development of architected materials and mechanisms
• AI and their applications in the design and development of (mechanical, electromagnetic, optical, etc.,) metamaterials
• AI and their applications in advanced fabrications techniques such as (multimaterial) 3D printing, 4D printing


Keywords: Artificial intelligence, Machine learning, Neural network, Deep learning, Architected materials, Additive manufacturing, Metamaterials


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Architected materials have been emerged as a class of (mechanical, acoustic, photonic, electromagnetic, etc.) metamaterials whose tailor-made and exotic properties (e.g., negative Poisson’s ratio, negative stiffness and negative thermal expansion) are the consequence of interplay between the geometry and material properties. The success of achieving such unusual properties thus relies on finding rational microarchitectural designs which can also be extremely challenging to explore. The current progress of architected materials, therefore, owes to the thriving synergy between the development of advanced multiphysics computational (e.g., finite element models together with topology optimization algorithms) and analytical models from one hand and advanced manufacturing (e.g., additive manufacturing, AM also known as 3D printing) technologies from another hand.

Recently, artificial intelligence (AI) technology and its corresponding subcategories such as Machine learning (ML) (e.g., via neural networks) as well as Deep Learning (DL) approaches have found their roots in the design of architected materials. These technologies have provided unparallel and powerful tools for engineers to expand the design space of architected materials even further and push the limits of achievable properties and functionalities. AI technology can, therefore, revolutionize the way that architected materials have traditionally been designed and engineered and replace them by smart machines as intelligent designers. This new design paradigm can also be beneficial for many high-tech industries such as biomedical and aeronautical engineering.

This Research Topic aims to provide a comprehensive overview of the recent progress and developments in the field of implementation of AI technology in the design of architected materials. We also aim to present the latest findings of various disciplines such as physics, material science, mechanics, electronics, computer science, and biomedical engineering towards the application of AI technologies in the development of these advanced materials. The fabrication techniques may include but not limited to (multi-material) 3D printing and 4D printing technologies. Therefore, we encourage contributors to submit their most recent studies under the form of Original Research, Reviews, Mini-reviews, communication articles on the following themes:

• AI and their applications in the design and development of architected materials and mechanisms
• AI and their applications in the design and development of (mechanical, electromagnetic, optical, etc.,) metamaterials
• AI and their applications in advanced fabrications techniques such as (multimaterial) 3D printing, 4D printing


Keywords: Artificial intelligence, Machine learning, Neural network, Deep learning, Architected materials, Additive manufacturing, Metamaterials


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

24 September 2021 Abstract
28 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

24 September 2021 Abstract
28 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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