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PNAS Nexus|May 31, 2024
Weak-formulated physics-informed modeling and optimization for heterogeneous digital materialsZhizhou Zhang, Jeong-Ho Lee, Lingfeng Sun, et al.ACS Applied Materials & Interfaces|April 27, 2023
Deep Learning Accelerated Design of Mechanically Efficient Architected MaterialsSangryun Lee, Zhizhou Zhang, Grace X GuMaterials Horizons|February 9, 2022
Generative machine learning algorithm for lattice structures with superior mechanical propertiesSangryun Lee, Zhizhou Zhang, Grace X GuACS Biomaterials Science & Engineering|April 22, 2021
Monitoring Anomalies in 3D Bioprinting with Deep Neural NetworksZeqing Jin, Zhizhou Zhang, Xianlin Shao, et al.Materials Horizons|March 13, 2024
Mechanical metamaterials as broadband electromagnetic wave absorbers: investigating relationships between geometrical parameters and electromagnetic responseDahyun Daniel Lim, Sangryun Lee, Jeong-Ho Lee, et al.Biomacromolecules|March 1, 2021
Birefringent Silk Fibroin Hydrogel Constructed via Binary Solvent-Exchange-Induced Self-AssemblyTing Shu, Ke Zheng, Zhizhou Zhang, et al.Nanotechnology|November 5, 2019
Recovery from mechanical degradation of graphene by defect enlargementBowen Zheng, Grace X GuNano-Micro Letters|June 17, 2021
Machine Learning-Based Detection of Graphene Defects with Atomic PrecisionBowen Zheng, Grace X GuProceedings of the National Academy of Sciences of the United States of America|July 30, 2021
Learning hidden elasticity with deep neural networksChun-Teh Chen, Grace X GuAdvanced Science (Weinheim, Baden-Wurttemberg, Germany)|March 11, 2020
Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active LearningChun-Teh Chen, Grace X GuPageof 31