A multi-scale sampling method for accurate and robust deep neural network to predict combustion chemical kinetics. - Tianhan Zhang; Yuxiao Yi; Yifan Xu; Zhi X. Chen; Yaoyu Zhang; Weinan E; Zhi-Qin John Xu (CoRR, 2022)

An integrated framework for accelerating reactive flow simulation using GPU and machine learning models. - Runze Mao; Yingrui Wang; Min Zhang; Han Li; Jiayang Xu; Xinyu Dong; Yan Zhang; Zhi X. Chen (CoRR, 2023)

DeepFlame: A deep learning empowered open-source platform for reacting flow simulations. - Runze Mao; Minqi Lin; Yan Zhang; Tianhan Zhang; Zhi-Qin John Xu; Zhi X. Chen (Comput. Phys. Commun., 2023)

DeepFlame 2.0: A new version for fully GPU-native machine learning accelerated reacting flow simulations under low-Mach conditions. - Runze Mao; Xinyu Dong; Xuan Bai; Ziheng Wu; Guanlin Dang; Han Li; Zhi X. Chen (Comput. Phys. Commun., 2025)