Deep learning in mechanical metamaterials: from prediction and generation to inverse design
Mechanical metamaterials are meticulously designed structures with exceptional
mechanical properties determined by their microstructures and constituent materials …
mechanical properties determined by their microstructures and constituent materials …
[HTML][HTML] Biomimetic scaffolds using triply periodic minimal surface-based porous structures for biomedical applications
The design of biomimetic porous scaffolds has been gaining attention in the biomedical
sector lately. Shells, marine sponges, shark teeth, cancellous bone, sea urchin spine, and …
sector lately. Shells, marine sponges, shark teeth, cancellous bone, sea urchin spine, and …
Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling
The rise of machine learning has fueled the discovery of new materials and, especially,
metamaterials—truss lattices being their most prominent class. While their tailorable …
metamaterials—truss lattices being their most prominent class. While their tailorable …
Machine learning predictions on the compressive stress–strain response of lattice-based metamaterials
Predicting the stress–strain curve of lattice-based metamaterials is crucial for their design
and application. However, the complex nonlinear relationship between the mesoscopic …
and application. However, the complex nonlinear relationship between the mesoscopic …
Inverse design of 3D cellular materials with physics-guided machine learning
This paper investigates the feasibility of data-driven methods in automating the engineering
design process, specifically studying inverse design of cellular mechanical metamaterials …
design process, specifically studying inverse design of cellular mechanical metamaterials …
[HTML][HTML] Inverse-designed growth-based cellular metamaterials
Advancements in machine learning have sparked significant interest in designing
mechanical metamaterials, ie, materials that derive their properties from their inherent …
mechanical metamaterials, ie, materials that derive their properties from their inherent …
Machine learning–enabled inverse design of shell-based lattice metamaterials with optimal sound and energy absorption
Currently, the development in shell-based lattice, is increasingly focused on
multifunctionality, with growing interest in combining sound and energy absorption …
multifunctionality, with growing interest in combining sound and energy absorption …
[HTML][HTML] Design of a composite metamaterial toward perfect microwave absorption and excellent load-bearing performance
Z Zhu, J Zhou, Y Li, X Qi, Y Wang, Y Wen - Materials & Design, 2023 - Elsevier
In this paper, an ultrathin layer of arrayed electromagnetic resonators is introduced on the
CFRP laminate to form a meta-CFRP composite. It is quite an exciting and promising design …
CFRP laminate to form a meta-CFRP composite. It is quite an exciting and promising design …
A review of graph neural network applications in mechanics-related domains
Mechanics-related tasks often present unique challenges in achieving accurate geometric
and physical representations, particularly for non-uniform structures. Graph neural networks …
and physical representations, particularly for non-uniform structures. Graph neural networks …
Formation energy prediction of crystalline compounds using deep convolutional network learning on voxel image representation
Emerging machine-learned models have enabled efficient and accurate prediction of
compound formation energy, with the most prevalent models relying on graph structures for …
compound formation energy, with the most prevalent models relying on graph structures for …