[HTML][HTML] Non-symmetric plate-lattices: Recurrent neural network-based design of optimal metamaterials
The elastic response of plate-lattices with cubic symmetry can reach the upper, isotropic
Hashin-Shtrikman bound. Here, our primary objective is the design of stiff lattices with …
Hashin-Shtrikman bound. Here, our primary objective is the design of stiff lattices with …
[HTML][HTML] Graph neural networks for strut-based architected solids
Abstract Machine learning methods for strut-based architected solids are attractive for
reducing computational costs in optimisation calculations. However, the space of all …
reducing computational costs in optimisation calculations. However, the space of all …
Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction
Data-centric methods have shown great potential in understanding and predicting
spatiotemporal dynamics, enabling better design and control of the object system. However …
spatiotemporal dynamics, enabling better design and control of the object system. However …
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
The ability to perform fast and accurate atomistic simulations is crucial for advancing the
chemical sciences. By learning from high-quality data, machine-learned interatomic …
chemical sciences. By learning from high-quality data, machine-learned interatomic …