3 papers
cond-mat.mtrl-sci2024
Combining Reinforcement Learning with Graph Convolutional Neural Networks for Efficient Design of TiAl/TiAlN Atomic-Scale Interfaces
Xinyu Jiang, Haofan Sun, Qiong Nian +1
Ti/TiN coatings are utilized in a wide variety of engineering applications due to their superior properties such as high hardness and toughness. Doping Al into Ti/TiN can also enha…
cond-mat.mtrl-sci2024
Significantly Enhanced Interfacial Thermal Transport between Single-layer Graphene and Water Through Basal-plane Oxidation
Haoran Cui, Iyyappa Rajan Panneerselvam, Pranay Chakraborty +3
Heat transfer between graphene and water is pivotal for various applications, including solarthermal vapor generation and the advanced manufacturing of graphene-based hierarchical…
cond-mat.mtrl-sci2023
Interpretable Ensemble Learning for Materials Property Prediction with Classical Interatomic Potentials: Carbon as an Example
Xinyu Jiang, Haofan Sun, Kamal Choudhary +2
Machine learning (ML) is widely used to explore crystal materials and predict their properties. However, the training is time-consuming for deep-learning models, and the regression…