Machine Learning‐Assisted Property Prediction of Solid‐State Electrolyte

J Li, M Zhou, HH Wu, L Wang, J Zhang… - Advanced Energy …, 2024 - Wiley Online Library
Abstract Machine learning (ML) exhibits substantial potential for predicting the properties of
solid‐state electrolytes (SSEs). By integrating experimental or/and simulation data within ML …

Perspective: Machine learning in design for 3D/4D printing

X Sun, K Zhou, F Demoly… - Journal of Applied …, 2024 - asmedigitalcollection.asme.org
Abstract 3D/4D printing offers significant flexibility in manufacturing complex structures with
a diverse range of mechanical responses, while also posing critical needs in tackling …

Superior Strength, Toughness, and Damage‐Tolerance Observed in Microlattices of Aperiodic Unit Cells

X Wang, X Li, Z Li, Z Wang, W Zhai - Small, 2024 - Wiley Online Library
Characterized by periodic cellular unit cells, microlattices offer exceptional potential as
lightweight and robust materials. However, their inherent periodicity poses the risk of …

Data-driven inverse design of composite triangular lattice structures

XL Peng, BX Xu - International Journal of Mechanical Sciences, 2024 - Elsevier
In this work, we introduce a class of novel bi-material composite triangular lattice structures.
The inverse design of these structures is achieved by using a data-driven method. They …

A multifunctional metastructure with energy dissipation and low-frequency sound-absorption optimized for decoupling by genetic algorithm

Y Huang, C Liu, W Li, X Liu, JH Wu, F Ma - Thin-Walled Structures, 2024 - Elsevier
A multifunctional metastructure has been proposed with the aim of having both energy-
absorbing and sound-absorbing capabilities through the use of a rubber-filled re-entrant …

Three-Dimensional Optical Imaging of Internal Deformations in Polymeric Microscale Mechanical Metamaterials

BW Blankenship, T Meier, N Zhao, S Mavrikos… - Nano Letters, 2024 - ACS Publications
Recent advances in two-photon polymerization fabrication processes are paving the way to
creating macroscopic metamaterials with microscale architectures, which exhibit mechanical …

Additively manufactured foot insoles using body-centered cubic (BCC) and triply periodic minimal surface (TPMS) cellular structures

G Rico-Baeza, GI Pérez-Soto, LA Morales-Hernández… - Applied Sciences, 2023 - mdpi.com
This study presents the development of insoles using 3D scanning and additive
manufacturing; additionally, the feasibility of implementing cellular structures in their design …

GNNs for mechanical properties prediction of strut-based lattice structures

B Jiang, Y Wang, H Niu, X Cheng, P Zhao… - International Journal of …, 2024 - Elsevier
The mechanical properties of strut-based lattice structures are greatly influenced by cell
topology, which can be modified by changing connections between nodes within a single …

Tailoring Stress–Strain Curves of Flexible Snapping Mechanical Metamaterial for On‐Demand Mechanical Responses via Data‐Driven Inverse Design

Z Chai, Z Zong, H Yong, X Ke, J Zhu, H Ding… - Advanced …, 2024 - Wiley Online Library
By incorporating soft materials into the architecture, flexible mechanical metamaterials
enable promising applications, eg, energy modulation, and shape morphing, with a well …

Mechanical characterization and inverse design of stochastic architected metamaterials using neural operators

H Jin, E Zhang, B Zhang, S Krishnaswamy… - arXiv preprint arXiv …, 2023 - arxiv.org
Machine learning (ML) is emerging as a transformative tool for the design of architected
materials, offering properties that far surpass those achievable through lab-based trial-and …