88 citations · 167 across the 9 of their papers we have counts for
9 papers
AlloyVAE: A generative model for complex probabilistic field-to-field relationships in alloys
Ningyu Yan, Zhuocheng Xie, Kai Guo +3
The inherent compositional heterogeneity of multi-principal element alloys (MPEAs) gives rise to complex, spatially varying mechanical fields that cannot be uniquely determined fro…
Uncertainty-Aware Machine-Learning Framework for Predicting Dislocation Plasticity and Stress-Strain Response in FCC Alloys
Jing Luo, Yejun Gu, Yanfei Wang +2
Machine learning has significantly advanced the understanding and application of structural materials, with an increasing emphasis on integrating existing data and quantifying unce…
A Continuum Model for Dislocation Climb
Chutian Huang, Shuyang Dai, Xiaohua Niu +4
Dislocation climb plays an important role in understanding plastic deformation of metallic materials at high temperature. In this paper, we present a continuum formulation for disl…
A Statistical Perspective for Predicting the Strength of Metals: Revisiting the Hall-Petch Relationship using Machine Learning
Yejun Gu, Christopher D. Stiles, Jaafar A. El-Awady
The mechanical properties of a material are intimately related to its microstructure. This is particularly important for predicting mechanical behavior of polycrystalline metals, w…
The interplay of local chemistry and plasticity in controlling microstructure formation during laser powder bed fusion of metals
Markus Sudmanns, Andrew J. Birnbaum, Yejun Gu +4
Additive manufacturing (AM) of metallic components promises many advantages over conventional manufacturing processes through high design flexibility across multiple length scales…
Continuum Model and Numerical Method for Dislocation Structure and Energy of Grain Boundaries
Xiaoxue Qin, Yejun Gu, Luchan Zhang +1
We present a continuum model to determine the dislocation structure and energy of low angle grain boundaries in three dimensions. The equilibrium dislocation structure is obtained…