Revealing the predictive power of neural operators for strain evolution in digital composites

MM Rashid, S Chakraborty, NMA Krishnan - Journal of the Mechanics and …, 2023 - Elsevier
The demand for high-performance materials, along with advanced synthesis technologies
such as additive manufacturing and 3D printing, has spurred the development of …

Nonlinear mechanics of horseshoe microstructure-based lattice design

Y Zhang, M Li, Z Qi, R Chen, Y Lin, S Cao, X Li… - International Journal of …, 2025 - Elsevier
Enhancing buffering capacity, flexibility, and energy absorption to withstand large
deformations in structure remains a challenge. Bio-inspired horseshoe lattice structures, with …

Non-Fourier heat conduction in 2D thermal metamaterials

ZY Li, M Mellmann, Y Wang, TX Ma, D Yan… - Materials Today …, 2024 - Elsevier
The challenge of achieving precise control over heat conduction has persisted for years.
Recent advancements in thermal metamaterials have offered a promising avenue for …

A hybrid operator-based multifactorial evolutionary algorithm for inverse-engineering design of soft network materials

S Cao, X Feng, J Chang, Y Yu, X Wang, J Cai, Y Lai… - Thin-Walled …, 2024 - Elsevier
Soft network materials (SNMs) are a class of network materials with periodic thin curved
filaments in lattice patterns, offering excellent physical properties of high stretchability, highly …

[CITATION][C] Special issue on “Advancements in materials for wearable electronics”

Y Wang, MOG Nayeem, S **ong - Materials Today Communications, 2023 - Elsevier