2

Generative design, manufacturing, and molecular modeling of 3D architected materials based on natural language input
We describe a method to generate 3D architected materials based on mathematically parameterized human readable word input, offering a …
Yu-Chuan Hsu, Zhenze Yang, Markus J. Buehler
Cite DOI Paper Link
Generative design, manufacturing, and molecular modeling of 3D architected materials based on natural language input
Water contact angles on charged surfaces in aerosols
Interactions between water and solid substrates are of fundamental importance to various processes in nature and industry. Electric …
Yutian Shen, Ting Lin, Zhenze Yang, Yongfeng Huang, Jiyu Xu, Sheng Meng
Cite DOI Paper Link
Water contact angles on charged surfaces in aerosols
Screening and Understanding Li Adsorption on Two-Dimensional Metallic Materials by Learning Physics and Physics-Simplified Learning
Understanding and broad screening Li interaction energetics with surfaces are key to the development of materials for a wide range of …
Sheng Gong, Shuo Wang, Taishan Zhu, Xi Chen, Zhenze Yang, Markus J. Buehler, Yang Shao-Horn, Jeffrey C. Grossman
Cite DOI Paper Link
Screening and Understanding Li Adsorption on Two-Dimensional Metallic Materials by Learning Physics and Physics-Simplified Learning
Words to Matter: De novo Architected Materials Design Using Transformer Neural Networks
Transformer neural networks have become widely used in a variety of AI applications, enabling significant advances in Natural Language …
Zhenze Yang, Markus J. Buehler
Cite DOI Paper Link
Words to Matter: De novo Architected Materials Design Using Transformer Neural Networks
End-to-end deep learning method to predict complete strain and stress tensors for complex hierarchical composite microstructures
Due to the high demand for materials with superior mechanical properties and diverse functions, designing composite materials is an …
Zhenze Yang, Chi-Hua Yu, Kai Guo, Markus J. Buehler
Cite DOI Paper Link
End-to-end deep learning method to predict complete strain and stress tensors for complex hierarchical composite microstructures
Deep learning model to predict complex stress and strain fields in hierarchical composites
Materials-by-design is a paradigm to develop previously unknown high-performance materials. However, finding materials with superior …
Zhenze Yang, Chi-Hua Yu, Markus J. Buehler
Cite DOI Paper Link
Deep learning model to predict complex stress and strain fields in hierarchical composites
Artificial Intelligence and Machine Learning in Mechanical Design of Materials
Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms, is becoming an important tool in the …
Kai Guo, Zhenze Yang, Chi-Hua Yu, Markus J. Buehler
Cite DOI Paper Link
Artificial Intelligence and Machine Learning in Mechanical Design of Materials
Liquid Metal Corrosion Effects on Conventional Metallic Alloys Exposed to Eutectic Gallium–Indium Alloy Under Various Temperature States
The effects of liquid metal corrosion on the thermophysical properties of three con- ventional metallic alloys, including T2 copper, …
Yuntao Cui, Yujie Ding, Shuo Xu, Zhenze Yang, Pengju Zhang, Wei Rao, Jing Liu
Cite DOI Paper Link
Liquid Metal Corrosion Effects on Conventional Metallic Alloys Exposed to Eutectic Gallium–Indium Alloy Under Various Temperature States
Metallic Bond Enabled Wetting Behavior at the Liquid Ga/CuGa2 Interfaces
Interface interaction can strongly modify contact angle, adsorption energy, interfacial tension, and composition of the contact area. …
Yuntao Cui, Fei Liang, Zhenze Yang, Shuo Xu, Xi Zhao, Yujie Ding, Zheshuai Lin, Jing Liu
Cite DOI Paper Link
Metallic Bond Enabled Wetting Behavior at the Liquid Ga/CuGa2 Interfaces